├── .DS_Store ├── Codes ├── .DS_Store ├── Fan2018TSP │ ├── .DS_Store │ ├── Codes for DFRC Waveform Design │ │ ├── .DS_Store │ │ ├── Constant Modulus │ │ │ ├── QCQP_LB1.zip │ │ │ ├── QPSK_mapper.m │ │ │ ├── CE_similarity_ComRad.zip │ │ │ ├── ComRad_Constant_Modulus.zip │ │ │ ├── objval_func.m │ │ │ ├── PSLRindB.m │ │ │ ├── pc_freqwin.m │ │ │ ├── chirp_generator.m │ │ │ ├── normalize_UB.m │ │ │ ├── QCQP_UB.m │ │ │ ├── QCQP_LB1.m │ │ │ ├── QCQP_LB2.m │ │ │ ├── CE_similarity_ComRad_benchmark.m │ │ │ ├── CE_similarity_bb_BRS.m │ │ │ ├── CE_similarity_bb_final_minModulus.m │ │ │ ├── CE_similarity_bb_ARS.m │ │ │ ├── CE_similarity_ComRad.m │ │ │ └── CE_similarity_sumrate.m │ │ └── Waveform Design With Given Radar Beampatterns │ │ │ ├── QPSK_mapper.m │ │ │ ├── Arbitrary_Com_Rad.m │ │ │ ├── PD_Orthogonal.m │ │ │ ├── Orthogonal_Com_Rad.m │ │ │ ├── waveform_design_multibm_covmat.m │ │ │ ├── QPSK_demod.m │ │ │ ├── tradeoff_comrad.m │ │ │ ├── LineSearchGoldenSection.m │ │ │ ├── tradeoff_comrad_per_ant.m │ │ │ ├── waveform_mainbm_covmat.m │ │ │ ├── sumrate_PD_tradeoff.m │ │ │ ├── multi_opt_comparison_sumrate.m │ │ │ └── multi_opt_comparison_SER.m │ └── README.md ├── README.md ├── Fan2018TWC by Nate Raymondi │ ├── README.md │ ├── SeparatedDeployment_BPmatching.m │ └── SeparatedDeployment_SidelobeMin.m └── Fan2020TCOM by Nate Raymondi │ ├── README.md │ └── Fan_DFRC.m ├── LICENSE └── README.md /.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/.DS_Store -------------------------------------------------------------------------------- /Codes/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/Codes/.DS_Store -------------------------------------------------------------------------------- /Codes/Fan2018TSP/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/Codes/Fan2018TSP/.DS_Store -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/Codes/Fan2018TSP/Codes for DFRC Waveform Design/.DS_Store -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/QCQP_LB1.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/QCQP_LB1.zip -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/QPSK_mapper.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/QPSK_mapper.m -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/CE_similarity_ComRad.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/CE_similarity_ComRad.zip -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/ComRad_Constant_Modulus.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/ComRad_Constant_Modulus.zip -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/objval_func.m: -------------------------------------------------------------------------------- 1 | function [ objval ] = objval_func(x,H_wave,y_wave) 2 | %UNTITLED9 Summary of this function goes here 3 | % Detailed explanation goes here 4 | objval = norm(H_wave.'*x-y_wave,2)^2; 5 | end 6 | 7 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/QPSK_mapper.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yuanhao-cui/Must-Reading-on-ISAC/HEAD/Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/QPSK_mapper.m -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/PSLRindB.m: -------------------------------------------------------------------------------- 1 | function [ PSLR ] = PSLRindB( x0 ) 2 | %UNTITLED7 Summary of this function goes here 3 | % Detailed explanation goes here 4 | f = pc_freqwin( x0 ); 5 | pks = findpeaks(f); 6 | pks = sort(pks); 7 | PSLR = pks(length(pks))-pks(length(pks)-1); 8 | end 9 | 10 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/pc_freqwin.m: -------------------------------------------------------------------------------- 1 | function [ f ] = pc_freqwin( x0 ) 2 | %UNTITLED6 Summary of this function goes here 3 | % Detailed explanation goes here 4 | w = taylorwin(length(x0)).'; 5 | s = x0.*w; 6 | f1 = abs(fftshift((ifft(fft(s).*conj(fft(s)))))); 7 | f = 20*log10(f1/max(f1)); 8 | end 9 | 10 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/Arbitrary_Com_Rad.m: -------------------------------------------------------------------------------- 1 | function [ X ] = Arbitrary_Com_Rad( H,Y,power,F ) 2 | %UNTITLED5 Summary of this function goes here 3 | % Detailed explanation goes here 4 | [N,K] = size(H); 5 | [~,L] = size(Y); 6 | H_wave = H.'*F; 7 | [U,S,V] = svd(sqrt(L*power)*H_wave'*Y); 8 | X = sqrt(L)*F*U*eye(N,L)*V'; 9 | end -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/PD_Orthogonal.m: -------------------------------------------------------------------------------- 1 | function [ PD ] = PD_Orthogonal( X,a,SNR ) 2 | %UNTITLED2 Summary of this function goes here 3 | % Detailed explanation goes here 4 | [N,L] = size(X); 5 | Rs = X*X'/L; 6 | rou = SNR*abs(a'*Rs.'*a)^2; 7 | Pfa = 1e-7; 8 | ita = chi2inv(1-Pfa,2); 9 | PD = 1-ncx2cdf(ita,2,rou); 10 | end 11 | 12 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/chirp_generator.m: -------------------------------------------------------------------------------- 1 | function [ X0 ] = chirp_generator( N,fc,Tp,B ) 2 | %UNTITLED5 Summary of this function goes here 3 | % Detailed explanation goes here 4 | u = B/Tp; 5 | fs = 4*B; 6 | sp_num = fs*Tp; 7 | t = linspace(0,Tp,sp_num); 8 | for ii = 1:N 9 | X0(ii,:) = exp(j*2*pi*10*ii*fc*(t-1)).*exp(j*pi*u*(t-1).^2); 10 | end 11 | end 12 | 13 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/Orthogonal_Com_Rad.m: -------------------------------------------------------------------------------- 1 | function [ X ] = Orthogonal_Com_Rad( H,Y,power ) 2 | %UNTITLED5 Summary of this function goes here 3 | % Detailed explanation goes here 4 | [N,K] = size(H); 5 | [~,L] = size(Y); 6 | u = sqrt(power/N); 7 | [U,S,V] = svd(sqrt(L/N)*power*conj(H)*Y); 8 | X = u*sqrt(L)*U*eye(N,L)*V'; 9 | end 10 | 11 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/waveform_design_multibm_covmat.m: -------------------------------------------------------------------------------- 1 | function [ R ] = waveform_design_multibm_covmat( Pd_theta,N,L,a,theta,power) 2 | %UNTITLED2 Summary of this function goes here 3 | % Detailed explanation goes here 4 | cvx_solver sedumi 5 | cvx_begin quiet 6 | variable bt 7 | variable R(N,N) hermitian semidefinite 8 | expression u(length(theta)) 9 | for i=1:length(theta) 10 | u(i)=(bt*Pd_theta(i)-a(:,i)'*R*a(:,i)); 11 | end 12 | minimize norm(u,2) 13 | subject to 14 | % diag(R)==ones(N,1)*power/N; 15 | trace(R)==power; 16 | cvx_end 17 | end 18 | 19 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/QPSK_demod.m: -------------------------------------------------------------------------------- 1 | function [ symbol_demod ] = QPSK_demod_mat(y) 2 | %UNTITLED2 Summary of this function goes here 3 | % Detailed explanation goes here 4 | [M,N]=size(y); 5 | for ii = 1:M 6 | for jj = 1:N 7 | if real(y(ii,jj))>0 8 | if imag(y(ii,jj))>0 9 | symbol_demod(ii,jj)=(1+j)/sqrt(2); 10 | else 11 | symbol_demod(ii,jj)=(1-j)/sqrt(2); 12 | end 13 | else 14 | if imag(y(ii,jj))>0 15 | symbol_demod(ii,jj)=(-1+j)/sqrt(2); 16 | else 17 | symbol_demod(ii,jj)=(-1-j)/sqrt(2); 18 | end 19 | end 20 | end 21 | end 22 | 23 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/tradeoff_comrad.m: -------------------------------------------------------------------------------- 1 | function [X] = tradeoff_comrad( rou,H,Y,power,X_arbi ) 2 | %UNTITLED4 Summary of this function goes here 3 | % Detailed explanation goes here 4 | [N,~] = size(H); 5 | [~,L] = size(Y); 6 | p1 = sqrt(rou); 7 | p2 = sqrt(1-rou); 8 | A = [p1*H,p2*eye(N)].'; 9 | B = [p1*sqrt(power)*Y;p2*X_arbi]; 10 | Q = A'*A; 11 | G = A'*B; 12 | %G_inv = inv(G*G'); 13 | e = eig(Q); 14 | [V,~] = eig(Q); 15 | l_min = min(e); 16 | for i = 1:N 17 | tr_fe(i) = real(trace (G*G'*V(:,i)*V(:,i)')); 18 | end 19 | func = @(xx)sum(tr_fe'./(e+xx*ones(N,1)))+xx*power*L; 20 | LB = -l_min; 21 | UB = 1; 22 | EPSILON = 10^-4; 23 | l = LineSearchGoldenSection(func,LB,UB,EPSILON); 24 | X = pinv(Q+l*eye(N))*G; 25 | end 26 | 27 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/normalize_UB.m: -------------------------------------------------------------------------------- 1 | function [x_nml_wave,UB] = normalize_UB( H_wave,y_wave,x,N,l,u) 2 | %UNTITLED9 Summary of this function goes here 3 | % Detailed explanation goes here 4 | x_cplx = x(1:N)+j*x(N+1:2*N); 5 | x_temp = x_cplx./abs(x_cplx); 6 | for ii = 1:N 7 | delta = u(ii)-l(ii); 8 | if delta <=pi 9 | x_nml(ii,1) = x_temp(ii); 10 | else 11 | if ((angle(x_temp(ii))<=u(ii))&&(angle(x_temp(ii))>=l(ii))) 12 | x_nml(ii,1) = x_temp(ii); 13 | else 14 | d_l = abs(x_cplx(ii)-exp(j*l(ii))); 15 | d_u = abs(x_cplx(ii)-exp(j*u(ii))); 16 | if d_l <= d_u 17 | x_nml(ii,1) = exp(j*l(ii)); 18 | else 19 | x_nml(ii,1) = exp(j*u(ii)); 20 | end 21 | end 22 | end 23 | end 24 | x_nml_wave = [real(x_nml);imag(x_nml)]; 25 | UB = objval_func(x_nml_wave,H_wave,y_wave); 26 | end 27 | 28 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/LineSearchGoldenSection.m: -------------------------------------------------------------------------------- 1 | function [t] = LineSearchGoldenSection(func,LB,UB,EPSILON) 2 | % 3 | % Golden Section search for an approximate minimum of unimodal 4 | % function f(t) using only function evaluations 5 | % 6 | % length of location interval is reduced by 0.318 each iteration 7 | % 8 | 9 | narginchk(3,4); 10 | if nargin == 3 11 | EPSILON = max(abs(UB) + abs(LB),2)*0.5e-4; 12 | end 13 | GR = (sqrt(5)-1)/2; % 0.618 14 | 15 | l = UB - (UB-LB)*GR; 16 | r = LB + (UB-LB)*GR; 17 | fl = func(l); 18 | fr = func(r); 19 | while UB - LB >= EPSILON 20 | if fl < fr 21 | UB = r; 22 | r = l; 23 | fr = fl; 24 | l = UB - (UB-LB)*GR; 25 | fl = func(l); 26 | else 27 | LB = l; 28 | l = r; 29 | fl = fr; 30 | r = LB + (UB-LB)*GR; 31 | fr = func(r); 32 | end 33 | end 34 | 35 | t = (UB+LB)/2; 36 | 37 | end -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/tradeoff_comrad_per_ant.m: -------------------------------------------------------------------------------- 1 | function [X_trdoff] = tradeoff_comrad_per_ant(rou,H,Y,power,X_arbi) 2 | [N,K] = size(H); 3 | [~,L] = size(Y); 4 | p1 = sqrt(rou); 5 | p2 = sqrt(1-rou); 6 | A = sqrt((L*power)/N)*[p1*H,p2*eye(N)].'; 7 | A = A'; 8 | B = [p1*sqrt(power)*Y;p2*X_arbi]; 9 | B = B'; 10 | 11 | 12 | % Create the problem structure. 13 | M = obliquecomplexfactory(L,N); 14 | problem.M = M; 15 | 16 | % Define the problem cost function and its gradient. 17 | 18 | problem.cost = @cost; 19 | function f=cost(X) 20 | f = norm(X*A-B,'fro')^2; 21 | end 22 | problem.grad = @(X) problem.M.egrad2rgrad(X,egrad(X)); 23 | function g = egrad(X) 24 | g = 2*(X*A-B)*A'; 25 | end 26 | % figure; 27 | % checkgradient(problem); 28 | % Execute the optimization 29 | X_temp = conjugategradient(problem); 30 | X_trdoff = sqrt((L*power)/N)*X_temp'; 31 | end -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/waveform_mainbm_covmat.m: -------------------------------------------------------------------------------- 1 | function [ R ] = waveform_mainbm_covmat( N,a,theta_target,theta,power ) 2 | %UNTITLED4 Summary of this function goes here 3 | % Detailed explanation goes here 4 | delta=theta(2)-theta(1); 5 | l=ceil((theta_target+pi/2*ones(1,5))/delta+ones(1,5)); 6 | cvx_solver sedumi 7 | cvx_begin quiet 8 | variable t 9 | variable R(N,N) hermitian semidefinite 10 | minimize -t 11 | subject to 12 | for i=1:l(1)-1 13 | real(a(:,l(3))'*R*a(:,l(3))-a(:,i)'*R*a(:,i))>=t; 14 | end 15 | for ii=l(5)+1:length(theta) 16 | real(a(:,l(3))'*R*a(:,l(3))-a(:,ii)'*R*a(:,ii))>=t; 17 | end 18 | for i=l(3):l(5)-1 19 | real(a(:,i)'*R*a(:,i)-a(:,i+1)'*R*a(:,i+1))>=0.001*i; 20 | end 21 | for i=l(1):l(3)-1 22 | real(a(:,i+1)'*R*a(:,i+1)-a(:,i)'*R*a(:,i))>=0.001*i; 23 | end 24 | a(:,l(2))'*R*a(:,l(2)) == 0.5*a(:,l(3))'*R*a(:,l(3)); 25 | a(:,l(4))'*R*a(:,l(4)) == 0.5*a(:,l(3))'*R*a(:,l(3)); 26 | diag(R) == ones(N,1)*power/N; 27 | % trace(R)==power; 28 | cvx_end 29 | end 30 | 31 | -------------------------------------------------------------------------------- /Codes/README.md: -------------------------------------------------------------------------------- 1 | # Codes for some papers on ISAC (2021/8/1) 2 | 3 | - Many thanks to every contrbutors of those codes on ISAC papers. You can be free to share those codes and create a `pull request` to contribute your own codes for corresponding ISAC papers. 4 | - **Please cite related papers if those codes are helpful to you.** 5 | - Let us build a mysterious and wonderful ISAC world together. :-) 6 | 7 | # Contributors 8 | - Fan Liu (SUSTech) 9 | - Nate Raymondi (Rice University) 10 | 11 | # Paper list 12 | 1. **Toward Dual-functional Radar-Communication Systems: Optimal Waveform Design, IEEE TSP, 2018. (ranked 8th most popular article in IEEE TSP) [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=838666)** 13 | 14 | *F. Liu, L. Zhou, C. Masouros, A. Li, W. Luo and A. Petropulu* 15 | 16 | 2. **MU-MIMO Communications With MIMO Radar: From Co-Existence to Joint Transmission, IEEE TWC, 2018.[[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8288677)** 17 | 18 | *F. Liu, C. Masouros, A. Li, H. Sun and L. Hanzo* 19 | 20 | 3. **Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead, IEEE TCOM, 2020. [[PDF]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8999605)** 21 | 22 | *F. Liu, C. Masouros, A. P. Petropulu, H. Griffiths and L. Hanzo* 23 | 24 | # Software platform 25 | - MATLAB 2016/2018/2020 26 | - To run those codes, please download and install [CVX](http://cvxr.com/cvx/) & [Manopt](https://www.manopt.org/) 27 | 28 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/QCQP_UB.m: -------------------------------------------------------------------------------- 1 | function [ x, obj_val ] = QCQP_UB( H_wave,y_wave,N,l,u,x1) 2 | %UNTITLED9 Summary of this function goes here 3 | % Detailed explanation goes here 4 | Q = 2*H_wave*H_wave.'; 5 | f = -2*H_wave*y_wave; 6 | c = y_wave.'*y_wave; 7 | A = zeros(N,2*N); 8 | for ii = 1:N 9 | A(ii,ii) = cos((l(ii)+u(ii))/2); 10 | A(ii,ii+N) = sin((l(ii)+u(ii))/2); %Linear Constraint 11 | end 12 | 13 | 14 | function [y,grady] = quadobj(x,Q,f,c) %Objective Function 15 | y = 1/2*x.'*Q*x+f.'*x+c; 16 | if nargout>1 17 | grady = Q*x + f; 18 | end 19 | end 20 | 21 | function [y_con,yeq,grady,gradyeq] = quadconstr(x) %Nonlinear Constraint 22 | for nn = 1:N 23 | yeq(nn) = x(nn)^2+x(nn+N)^2 - 1; 24 | end 25 | y_con = []; 26 | if nargout>2 27 | gradyeq = zeros(length(x),N); 28 | for nn = 1:N 29 | gradyeq(nn,nn) = 2*x(nn); 30 | gradyeq(nn+N,nn) = 2*x(nn+N); 31 | end 32 | end 33 | grady = []; 34 | end 35 | 36 | Acon = -A; 37 | 38 | for ii = 1:N 39 | b(ii) = -cos((u(ii)-l(ii))/2); 40 | end 41 | 42 | 43 | 44 | % options = optimoptions(@fmincon,'Algorithm','sqp',... 45 | % 'SpecifyObjectiveGradient',true,'SpecifyConstraintGradient',true,... 46 | % 'Display','off','OptimalityTolerance',1e-6,'MaxIterations',400); 47 | 48 | options = optimoptions('fmincon','Algorithm','sqp', 'GradObj','on'); 49 | 50 | 51 | fun = @(x)quadobj(x,Q,f,c); 52 | nonlconstr = @(x)quadconstr(x); 53 | % x1 = ones(2*N,1); 54 | x = fmincon(fun,x1,Acon,b,[],[],[],[],nonlconstr,options); 55 | obj_val = objval_func(x,H_wave,y_wave); 56 | end 57 | 58 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/QCQP_LB1.m: -------------------------------------------------------------------------------- 1 | function [ x, obj_val] = QCQP_LB1( H_wave,y_wave,N,l,u) 2 | %UNTITLED9 Summary of this function goes here 3 | % Detailed explanation goes here 4 | Q = 2*H_wave*H_wave.'; 5 | f = -2*H_wave*y_wave; 6 | c = y_wave.'*y_wave; 7 | A = zeros(N,2*N); 8 | for ii = 1:N 9 | A(ii,ii) = cos((l(ii)+u(ii))/2); 10 | A(ii,ii+N) = sin((l(ii)+u(ii))/2); %Linear Constraint 11 | end 12 | 13 | 14 | function [y,grady] = quadobj(x,Q,f,c) %Objective Function 15 | y = 1/2*x.'*Q*x+f.'*x+c; 16 | if nargout>1 17 | grady = Q*x + f; 18 | end 19 | end 20 | 21 | function [y_con,yeq,grady,gradyeq] = quadconstr(x) %Nonlinear Constraint 22 | for nn = 1:N 23 | y_con(nn) = x(nn)^2+x(nn+N)^2 - 1; 24 | end 25 | yeq = []; 26 | if nargout>2 27 | gradyeq = zeros(length(x),N); 28 | for nn = 1:N 29 | grady(nn,nn) = 2*x(nn); 30 | grady(nn+N,nn) = 2*x(nn+N); 31 | end 32 | end 33 | gradyeq = []; 34 | end 35 | 36 | Acon = -A; 37 | 38 | for ii = 1:N 39 | b(ii) = -cos((u(ii)-l(ii))/2); 40 | end 41 | 42 | 43 | % options = optimoptions(@fmincon,'Algorithm','sqp',... 44 | % 'SpecifyObjectiveGradient',true,'SpecifyConstraintGradient',true,... 45 | % 'Display','off','OptimalityTolerance',1e-6,'MaxIterations',400); 46 | 47 | 48 | options = optimoptions('fmincon','Algorithm','sqp', 'GradObj','on'); 49 | 50 | fun = @(x)quadobj(x,Q,f,c); 51 | nonlconstr = @(x)quadconstr(x); 52 | x1 = ones(2*N,1); 53 | x = fmincon(fun,x1,Acon,b,[],[],[],[],nonlconstr,options); 54 | obj_val = objval_func(x,H_wave,y_wave); 55 | end 56 | 57 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/QCQP_LB2.m: -------------------------------------------------------------------------------- 1 | function [ x, obj_val,exitflag ] = QCQP_LB2( H_wave,y_wave,N,l,u,obj_prev) 2 | %UNTITLED9 Summary of this function goes here 3 | % Detailed explanation goes here 4 | Q = 2*H_wave*H_wave.'; 5 | f = -2*H_wave*y_wave; 6 | c = y_wave.'*y_wave; 7 | A = zeros(N,2*N); 8 | for ii = 1:N 9 | A(ii,ii) = cos((l(ii)+u(ii))/2); 10 | A(ii,ii+N) = sin((l(ii)+u(ii))/2); %Linear Constraint 11 | end 12 | 13 | 14 | function [y,grady] = quadobj(x,Q,f,c) %Objective Function 15 | y = 1/2*x.'*Q*x+f.'*x+c; 16 | if nargout>1 17 | grady = Q*x + f; 18 | end 19 | end 20 | 21 | function [y_con,yeq,grady,gradyeq] = quadconstr(x) %Nonlinear Constraint 22 | for nn = 1:N 23 | y_con(nn) = x(nn)^2+x(nn+N)^2 - 1; 24 | end 25 | y_con(N+1) = 1/2*x.'*Q*x+f.'*x+c-obj_prev; 26 | yeq = []; 27 | if nargout>2 28 | gradyeq = zeros(length(x),N+1); 29 | for nn = 1:N 30 | grady(nn,nn) = 2*x(nn); 31 | grady(nn+N,nn) = 2*x(nn+N); 32 | end 33 | grady(:,N+1) = Q*x + f; 34 | end 35 | gradyeq = []; 36 | end 37 | 38 | Acon = -A; 39 | 40 | for ii = 1:N 41 | b(ii) = -cos((u(ii)-l(ii))/2); 42 | end 43 | 44 | 45 | % options = optimoptions(@fmincon,'Algorithm','sqp',... 46 | % 'SpecifyObjectiveGradient',true,'SpecifyConstraintGradient',true,... 47 | % 'Display','off','OptimalityTolerance',1e-6,'MaxIterations',400); 48 | 49 | options = optimoptions('fmincon','Algorithm','sqp', 'GradObj','on'); 50 | 51 | fun = @(x)quadobj(x,Q,f,c); 52 | nonlconstr = @(x)quadconstr(x); 53 | x1 = ones(2*N,1); 54 | [x,ignore,exitflag] = fmincon(fun,x1,Acon,b,[],[],[],[],nonlconstr,options); 55 | obj_val = objval_func(x,H_wave,y_wave); 56 | end 57 | 58 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/README.md: -------------------------------------------------------------------------------- 1 | # Paper 2 | > F. Liu, L. Zhou, C. Masouros, A. Li, W. Luo and A. Petropulu, "Toward Dual-functional Radar-Communication Systems: Optimal Waveform Design," in IEEE Transactions on Signal Processing, vol. 66, no. 16, pp. 4264-4279, Aug. 2018. (ranked 8th most popular article in IEEE TSP, Feb 2021) 3 | 4 | - All codes are contributed by Fan Liu, SUSTech 5 | - [Click here to preview this paper in IEEE](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8386661) 6 | 7 | 8 | # Abstract 9 | We focus on a dual-functional multi-input-multioutput (MIMO) radar-communication (RadCom) system, where a single transmitter with multiple antennas communicates with downlink cellular users and detects radar targets simultaneously. Several design criteria are considered forminimizing the downlink multiuser interference. First, we consider both omnidirectional and directional beampattern design problems, where the closedform globally optimal solutions are obtained. Based on the derived waveforms, we further consider weighted optimizations targeting a flexible tradeoff between radar and communications performance and introduce low-complexity algorithms. Moreover, to address the more practical constant modulus waveform design problem, we propose a branch-and-bound algorithm that obtains a globally optimal solution, and derive its worst-case complexity as function of the maximum iteration number. Finally, we assess the effectiveness of the proposed waveform design approaches via numerical results. 10 | 11 | # About this code 12 | ### Software platform 13 | - MATLAB 2016/2018/2020 14 | - To run those codes, please download and install [CVX](http://cvxr.com/cvx/) & [Manopt](https://www.manopt.org/) 15 | ### Content 16 | - The folder `Waveform Design With Given Radar Beampatterns` is provided to produuct Fig.3-Fig.7 17 | - The folder `Constant modulus` is provided to product Fig.8-Fig.10 18 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/CE_similarity_ComRad_benchmark.m: -------------------------------------------------------------------------------- 1 | function [x_cplx,opt_val] = CE_similarity_ComRad_benchmark( H,y,power,ee,x0,cle ) 2 | % Branch and Bound Method for ComRad CEP 3 | % Detailed explanation goes here 4 | N = length(x0); 5 | amp = sqrt(power/N); % Amplitude of the Transmit Signal 6 | y_wave = sqrt(power*cle)*[real(y);imag(y)]; % Equivalent Real Desired Symbol 7 | H_wave = amp*[real(H),imag(H);-imag(H),real(H)]; % Equivalent Real Channel 8 | x0_wave = [real(x0);imag(x0)]; 9 | delta = acos(1-ee^2/2); 10 | for ii = 1:N 11 | l(ii,1) = angle(x0(ii))-delta; 12 | u(ii,1) = angle(x0(ii))+delta; %Initialized Upper and Lower Bound 13 | end 14 | l0 = l; 15 | u0 = u; 16 | 17 | A = zeros(N,2*N); 18 | for ii = 1:N 19 | A(ii,ii) = cos((l(ii)+u(ii))/2)/cos(delta); 20 | A(ii,ii+N) = sin((l(ii)+u(ii))/2)/cos(delta); 21 | end 22 | 23 | max_iternum = 200; %Maximum Iteration Number 24 | epsl = 1e-3; %Tolerence 25 | epsl1 = 1e-6; 26 | %-------------Parameter Initialization 27 | [x,obj_val] = QCQP_LB1( H_wave,y_wave,N,l,u); %Initialized LB and x 28 | iter = 1; 29 | 30 | while iter<=max_iternum 31 | tr = (l+u)/2; 32 | x_cplx = x(1:N)+j*x(N+1:2*N); 33 | obj_prev = obj_val; 34 | obj(iter) = obj_val; 35 | for ii = 1:N 36 | theta = angle(x_cplx(ii)); 37 | if theta>=tr(ii) 38 | l(ii) = tr(ii); 39 | else 40 | u(ii) = tr(ii); 41 | end 42 | end 43 | [x,obj_val,exitflag] = QCQP_LB2( H_wave,y_wave,N,l,u,obj_prev); 44 | iter = iter+1; 45 | if exitflag == -2 46 | x_opt = [real(x_cplx);imag(x_cplx)]; 47 | break; 48 | elseif (abs(obj_prev/obj_val-1)<=epsl)||(abs(obj_prev-obj_val)<=epsl1) 49 | x_opt = x; 50 | break; 51 | end 52 | end 53 | 54 | x_opt1 = normalize_UB( H_wave,y_wave,x_opt,N,l,u); 55 | x_cplx = x_opt1(1:N)+j*x_opt1(N+1:2*N); 56 | opt_val = objval_func(x_opt1,H_wave,y_wave); 57 | 58 | 59 | 60 | end 61 | 62 | -------------------------------------------------------------------------------- /Codes/Fan2018TWC by Nate Raymondi/README.md: -------------------------------------------------------------------------------- 1 | # Paper 2 | > F. Liu, C. Masouros, A. Li, H. Sun and L. Hanzo, "MU-MIMO Communications With MIMO Radar: From Co-Existence to Joint Transmission," in IEEE Transactions on Wireless Communications, vol. 17, no. 4, pp. 2755-2770, April 2018. 3 | 4 | - All codes are contributed by Nate Raymondi (Graduate Student, Rice University), 8/13/2020 5 | - [Click here to preview this paper in IEEE](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8288677) 6 | 7 | 8 | # Abstract 9 | Beamforming techniques are proposed for a joint multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single device acts as radar and a communication base station (BS) by simultaneously communicating with downlink users and detecting radar targets. Two operational options are considered, where we first split the antennas into two groups, one for radar and the other for communication. Under this deployment, the radar signal is designed to fall into the nullspace of the downlink channel. The communication beamformer is optimized such that the beampattern obtained matches the radar s beampattern while satisfying the communication performance requirements. To reduce the optimizations constraints, we consider a second operational option, where all the antennas transmit a joint waveform that is shared by both radar and communications. In this case, we formulate an appropriate probing beampattern, while guaranteeing the performance of the downlink communications. By incorporating the SINR constraints into objective functions as penalty terms, we further simplify the original beamforming designs to weighted optimizations, and solve them by efficient manifold algorithms. Numerical results show that the shared deployment outperforms the separated case significantly, and the proposed weighted optimizations achieve a similar performance to the original optimizations, despite their significantly lower computational complexity. 10 | 11 | # About this code 12 | ### Software platform 13 | - MATLAB 2014/2016/2018/2020 14 | - To run those codes, please download and install [CVX](http://cvxr.com/cvx/) 15 | 16 | ### Content 17 | - To product Fig.3-Fig.4 in this paper 18 | 19 | ### Usage 20 | 1. Due to the version of your MATLAB, variable name "sigma" is the name of an existing MATLAB function or directory. You need choose a different name (sigma_temp for example) 21 | 2. Run `SeparatedDeployment_BPmatching.m` 22 | 3. Run `SeparatedDeployment_SidelobeMin.m` 23 | -------------------------------------------------------------------------------- /Codes/Fan2020TCOM by Nate Raymondi/README.md: -------------------------------------------------------------------------------- 1 | # Paper 2 | > F. Liu, C. Masouros, A. P. Petropulu, H. Griffiths and L. Hanzo, "Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead," in IEEE Transactions on Communications, vol. 68, no. 6, pp. 3834-3862, June 2020. 3 | 4 | - All codes are contributed by Nate Raymondi (Graduate Student, Rice University), 1/23/2020 5 | - [Click here to preview this paper in IEEE](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8999605) 6 | 7 | 8 | # Abstract 9 | Sharing of the frequency bands between radar and communication systems has attracted substantial attention, as it can avoid under-utilization of otherwise permanently allocated spectral resources, thus improving efficiency. Further, there is increasing demand for radar and communication systems that share the hardware platform as well as the frequency band, as this not only decongests the spectrum, but also benefits both sensing and signaling operations via the full cooperation between both functionalities. Nevertheless, the success of spectrum and hardware sharing between radar and communication systems critically depends on high-quality joint radar and communication designs. In the first part of this paper, we overview the research progress in the areas of radar-communication coexistence and dual-functional radar-communication (DFRC) systems, with particular emphasis on application scenarios and technical approaches. In the second part, we propose a novel transceiver architecture and frame structure for a DFRC base station (BS) operating in the millimeter wave (mmWave) band, using the hybrid analog-digital (HAD) beamforming technique. We assume that the BS is serving a multi-antenna user equipment (UE) over a mmWave channel, and at the same time it actively detects targets. The targets also play the role of scatterers for the communication signal. In that framework, we propose a novel scheme for joint target search and communication channel estimation, which relies on omni-directional pilot signals generated by the HAD structure. Given a fully-digital communication precoder and a desired radar transmit beampattern, we propose to design the analog and digital precoders under non-convex constant-modulus (CM) and power constraints, such that the BS can formulate narrow beams towards all the targets, while pre-equalizing the impact of the communication channel. Furthermore, we design a HAD receiver that can simultaneously process signals from the UE and echo waves from the targets. By tracking the angular variation of the targets, we show that it is possible to recover the target echoes and mitigate the resulting interference to the UE signals, even when the radar and communication signals share the same signal-to-noise ratio (SNR). The feasibility and efficiency of the proposed approaches in realizing DFRC are verified via numerical simulations. Finally, the paper concludes with an overview of the open problems in the research field of communication and radar spectrum sharing (CRSS). 10 | 11 | # About this code 12 | ### Software platform 13 | - MATLAB 2014/2016/2018/2020 14 | - To run those codes, please download and install [CVX](http://cvxr.com/cvx/) 15 | 16 | ### Content 17 | - To product BS ZF Transmit Beampattern & BS DFRC Transmit Beampatternin in this paper 18 | 19 | ### Usage 20 | - Run `Fan_DFRC.m` 21 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Waveform Design With Given Radar Beampatterns/sumrate_PD_tradeoff.m: -------------------------------------------------------------------------------- 1 | %%Producing Fig. 5 2 | clc; 3 | clear all; 4 | close all; 5 | warning off; 6 | N = 16; 7 | % K = 4; 8 | L = 20; 9 | power = 10^(0/10); 10 | amp = sqrt(power); 11 | N_montecarlo = 100; 12 | SNRdB = 10; 13 | %%-------------Radar Parameters------------------- 14 | delta=pi/180; 15 | theta=-pi/2:delta:pi/2; 16 | theta_target=[-pi*10/180,-pi*5/180,0,pi*5/180,pi*10/180]; 17 | target_DoA=[-pi/3,0,pi/3]; 18 | beam_width=9; 19 | l=ceil((target_DoA+pi/2*ones(1,length(target_DoA)))/(delta)+ones(1,length(target_DoA))); 20 | Pd_theta=zeros(length(theta),1); 21 | for ii=1:length(target_DoA) 22 | Pd_theta(l(ii)-(beam_width-1)/2:l(ii)+(beam_width-1)/2,1)=ones(beam_width,1); 23 | end 24 | c=3e8; 25 | fc=3.2e9; 26 | lamda=c/fc; 27 | spacing=lamda/2; 28 | for tt=1:N 29 | for jj=1:length(theta) 30 | a(tt,jj)=exp(j*pi*(tt-ceil((N)/2))*sin(theta(jj))); 31 | end 32 | end 33 | SNRr = 10^(-6/10); 34 | uu = 36; 35 | 36 | % H = (randn(N,K)+j*randn(N,K))/sqrt(2); 37 | % N_pbits = 2*K*L; 38 | % msg_bits = randint(1,N_pbits); 39 | % Y = reshape(QPSK_mapper(msg_bits),[K,L]); 40 | % X1 = sqrt(N)*Orthogonal_Com_Rad( H,Y,power ); 41 | % RMSE = CRB_Orthogonal( X1,a(:,uu),theta(uu),SNR ); 42 | 43 | Nii = 20; 44 | N0 = power/(10^(SNRdB/10)); 45 | Nkk = 3; 46 | for kk = 1:Nkk 47 | K= 4+(kk-1)*2; 48 | for nn = 1:N_montecarlo 49 | H = (randn(N,K)+j*randn(N,K))/sqrt(2); 50 | N_pbits = 2*K*L; 51 | msg_bits = randi([0,1],1,N_pbits); 52 | Y = reshape(QPSK_mapper(msg_bits),[K,L]); 53 | X1 = Orthogonal_Com_Rad( H,Y,power ); 54 | % RMSE1 = CRB_Orthogonal( X1,a(:,uu),theta(uu),SNRr ); 55 | % H_pinv = pinv(H.'); 56 | % tt = trace(H_pinv*Y*Y'*H_pinv'); 57 | % X3 = sqrt(N*power/tt)*H_pinv*Y; 58 | for ii = 1:Nii-1 59 | rou = ii/Nii; 60 | X2 = sqrt(N)*tradeoff_comrad(rou,H,Y,power,X1); 61 | % for mm = 1:L 62 | % MUI1(:,mm) = abs(H.'*X1(:,mm)/sqrt(N)-amp*Y(:,mm)).^2; 63 | % MUI2(:,mm) = abs(H.'*X2(:,mm)/sqrt(N)-amp*Y(:,mm)).^2; 64 | % MUI3(:,mm) = abs(H.'*X3(:,mm)/sqrt(N)-amp*Y(:,mm)).^2; 65 | % end 66 | % MUI1 = abs(H.'*X1/sqrt(N)-amp*Y).^2; 67 | MUI2 = abs(H.'*X2/sqrt(N)-amp*Y).^2; 68 | % MUI3 = abs(H.'*X3/sqrt(N)-amp*Y).^2; 69 | % EMUI1 = mean(MUI1,2); 70 | EMUI2 = mean(MUI2,2); 71 | % EMUI3 = mean(MUI3,2); 72 | % sumrate1(ii,kk,nn) = sum(log2(1+power./(EMUI1+N0*ones(K,1)))); 73 | sumrate2(ii,kk,nn) = sum(log2(1+power./(EMUI2+N0*ones(K,1))))/K; 74 | % sumrate3(ii,kk,nn) = sum(log2(1+power./(EMUI3+N0*ones(K,1)))); 75 | % RMSE1(ii,kk,nn) = CRB_Orthogonal( X1,a(:,uu),theta(uu),SNRr ); 76 | PD2(ii,kk,nn) = PD_Orthogonal( X2,a(:,uu),SNRr ); 77 | % RMSE3(ii,kk,nn) = CRB_Orthogonal( X3,a(:,uu),theta(uu),SNRr ); 78 | clc 79 | disp(['Progress - ',num2str((kk-1)*N_montecarlo*Nii+(nn-1)*Nii+ii),'/',num2str(Nii*N_montecarlo*Nkk)]); 80 | end 81 | end 82 | end 83 | %% 84 | figure(1); 85 | % plot(mean(sumrate2,2),mean(RMSE1,2),'x-','LineWidth',1.5,'MarkerSize',8);hold on; 86 | for kk = 1:Nkk 87 | plot(mean(sumrate2(:,kk,:),3),mean(PD2(:,kk,:),3),'-','LineWidth',1.5,'MarkerSize',8);hold on; 88 | end 89 | % plot(mean(sumrate2,2),mean(RMSE3,2),'^-','LineWidth',1.5,'MarkerSize',8);hold on; 90 | grid on; 91 | legend('K = 4','K = 6','K = 8'); 92 | xlabel('Average achievable rate (bps/Hz/user)'); 93 | ylabel('P_D'); 94 | 95 | 96 | 97 | -------------------------------------------------------------------------------- /Codes/Fan2018TSP/Codes for DFRC Waveform Design/Constant Modulus/CE_similarity_bb_BRS.m: -------------------------------------------------------------------------------- 1 | %% Producing Fig. 8 BRS 2 | clc; 3 | clear all; 4 | close all; 5 | warning off; 6 | N = 16; % Antenna Number 7 | K = 4; % Users Number 8 | L = 20; % Length of Frame 9 | power = 10^(0/10); % Total Transmit Power 10 | amp = sqrt(power/N); % Amplitude of the Transmit Signal 11 | 12 | randn('state',2); 13 | H = (randn(N,K)+j*randn(N,K))/sqrt(2); % Channel 14 | N_pbits = 2*K; 15 | msg_bits = randi([0,1],1,N_pbits); 16 | % y = QPSK_mapper(msg_bits).'; % Desired Symbol 17 | y = QPSK_mapper([0,0,0,1,1,1,1,0]).'; 18 | y_wave = sqrt(power)*[real(y);imag(y)]; % Equivalent Real Desired Symbol 19 | 20 | for ii = 1:N 21 | for nn = 1:L 22 | X0(ii,nn) = exp(j*2*pi*ii*(nn-1)/L)*exp(j*pi*(nn-1)^2/L); % Reference Radar Signal (LFM) 23 | end 24 | end 25 | ee = 1; % Inf Norm Similarity 26 | H_wave = amp*[real(H),imag(H);-imag(H),real(H)]; % Equivalent Real Channel 27 | x0 = X0(:,4); %Reference Radar Signal Vector 28 | x0_wave = [real(x0);imag(x0)]; % Equivalent Real Radar Signal 29 | delta = acos(1-ee^2/2); 30 | for ii = 1:N 31 | l(ii,1) = angle(x0(ii))-delta; 32 | u(ii,1) = angle(x0(ii))+delta; %Initialized Upper and Lower Bound 33 | end 34 | A = zeros(N,2*N); 35 | for ii = 1:N 36 | A(ii,ii) = cos((l(ii)+u(ii))/2)/cos(delta); 37 | A(ii,ii+N) = sin((l(ii)+u(ii))/2)/cos(delta); 38 | end %Initialized Linear Constraints 39 | 40 | max_iternum = 1000; %Maximum Iteration Number 41 | epsl = 1e-4; %Tolerence 42 | epsl1 = 1e-6; 43 | %-------------Parameter Initialization 44 | [x,LB] = QCQP_LB1( H_wave,y_wave,N,l,u); %Initialized LB and x 45 | [x_nml1,UB1] = normalize_UB( H_wave,y_wave,x,N,l,u); %Initialized Normalization UB 46 | [x_nml2,UB2] = QCQP_UB( H_wave,y_wave,N,l,u,x_nml1); % fmincon UB 47 | [x_nml,UB] = QCQP_UB( H_wave,y_wave,N,l,u,x_nml2); % fmincon UB 48 | LB_start = LB; 49 | UB_start = UB; 50 | 51 | prob_list = zeros(max_iternum+100,4*N+1); 52 | prob_list(1,:)=[x',l',u',LB]; 53 | used = 1; 54 | lbest = LB; 55 | ubest = UB; 56 | x_opt = x_nml; 57 | 58 | lb_seq = lbest; 59 | ub_seq = ubest; 60 | 61 | if (ubest-lbest)/abs(ubest)= 0; 92 | for n = 1:N 93 | trace( conj(f(:,n)) * transpose(f(:,n)) * R1 ) == 0; 94 | end 95 | R1 == semidefinite(Nr); 96 | cvx_end 97 | % NOTE: I am fairly certain the expression of Eq.12 in the paper is 98 | % incorrect. The 'a' in the objective function should be 'a1' 99 | 100 | 101 | % substitute R1 into Eq.19 and solve 102 | % must be solved jointly since Wi depends on all other Wj 103 | cvx_begin quiet 104 | variable W1opt(Nc,Nc) hermitian 105 | variable W2opt(Nc,Nc) hermitian 106 | variable sigma_temp 107 | minimize( square_pos(norm( diag( a2'*(W1opt+W2opt)*a2 - sigma_temp*(a1'*R1*a1) ) ,2)) ); 108 | subject to 109 | % SINR constraints for each user 110 | %abs(trace( conj(g(:,1))*transpose(g(:,1))*W1 ))/abs(( trace( conj(g(:,2))*transpose(g(:,2))*W1 ) + ... 111 | %trace( conj(f(:,1))*transpose(f(:,1))*R1 ) + N0 )) >= Gamma(1); 112 | real(trace( conj(g(:,1))*transpose(g(:,1))*W1opt ) - Gamma(1)*( trace( conj(g(:,2))*transpose(g(:,2))*W1opt ) + ... 113 | trace( conj(f(:,1))*transpose(f(:,1))*R1 ) )) >= N0*Gamma(1); 114 | real(trace( conj(g(:,2))*transpose(g(:,2))*W2opt ) - Gamma(2)*( trace( conj(g(:,1))*transpose(g(:,1))*W2opt ) + ... 115 | trace( conj(f(:,2))*transpose(f(:,2))*R1 ) )) >= N0*Gamma(2); 116 | % Power constraint 117 | trace(W1opt + W2opt) <= Pc; 118 | sigma_temp >= 0; 119 | W1opt == semidefinite(Nc); 120 | W2opt == semidefinite(Nc); 121 | cvx_end 122 | % NOTE - we are solving the SDR for W1 and W2, so we will have to recover 123 | % w1 and w2 124 | 125 | 126 | % Do randomization to get our feasible beamforming vectors w1 and w2------- 127 | nRand = 10; 128 | w1 = zeros(Nc,nRand); w2 = zeros(Nc,nRand); 129 | W1cov = zeros(Nc,Nc,nRand); W2cov = zeros(Nc,Nc,nRand); 130 | clear u1F; clear u2F; 131 | 132 | % generate and scale to meet power constraints 133 | for L = 1:nRand 134 | % generate nRand 135 | w1(:,L) = mvnrnd(zeros(Nc,1),W1opt) + 1i*mvnrnd(zeros(Nc,1),W1opt); 136 | w2(:,L) = mvnrnd(zeros(Nc,1),W2opt) + 1i*mvnrnd(zeros(Nc,1),W2opt); 137 | 138 | % scale them so they all adhere to norm constraint 139 | w1(:,L) = sqrt(trace(W1opt))*w1(:,L)/sqrt(w1(:,L)'*w1(:,L)); 140 | w2(:,L) = sqrt(trace(W2opt))*w2(:,L)/sqrt(w2(:,L)'*w2(:,L)); 141 | 142 | W1cov(:,:,L) = w1(:,L)*w1(:,L)'; 143 | W2cov(:,:,L) = w2(:,L)*w2(:,L)'; 144 | end 145 | 146 | % check all pairs to see if user 1 SINR constraints are met 147 | index1 = 1; index2 = 1; 148 | for i = 1:nRand 149 | for j = 1:nRand 150 | if real(trace( conj(g(:,1))*transpose(g(:,1))*W1cov(:,:,i) ) - Gamma(1)*( trace( conj(g(:,2))*transpose(g(:,2))*W1cov(:,:,i) ) + ... 151 | trace( conj(f(:,1))*transpose(f(:,1))*R1 ) )) >= N0*Gamma(1) 152 | % save this pair as feasible for user 1 153 | u1F(:,1,index1) = w1(:,i); u1F(:,2,index1) = w2(:,j); 154 | index1 = index1 + 1; 155 | end 156 | end 157 | end 158 | 159 | % check all user 1 feasible pairs to see if they're user 2 feasible 160 | for i = 1:size(u1F,3) 161 | if real(trace( conj(g(:,2))*transpose(g(:,2))*(u1F(:,2,i)*u1F(:,2,i)') ) - Gamma(2)*( trace( conj(g(:,2))*transpose(g(:,2))*(u1F(:,1,i)*u1F(:,1,i)') ) + ... 162 | trace( conj(f(:,2))*transpose(f(:,2))*R1 ) )) >= N0*Gamma(2) 163 | % save this pair as feasible for user 2 164 | u2F(:,1,index2) = u1F(:,1,i); u2F(:,2,index2) = u1F(:,2,i); 165 | index2 = index2 + 1; 166 | end 167 | end 168 | 169 | % find how many feasible sets we have, choose the one with the smallest 170 | % objective function value 171 | numFeasible = size(u2F,3); % this number better be [0,nRand^N] lol. Yes there are repeats but who cares 172 | WcovSum = zeros(Nc,Nc,numFeasible); obj = zeros(1,numFeasible); 173 | for i = 1:size(u2F,3) 174 | WcovSum(:,:,i) = (u2F(:,1,i)*u2F(:,1,i)') + (u2F(:,2,i)*u2F(:,2,i)'); 175 | obj(i) = ( norm( diag( a2'*WcovSum(:,:,i)*a2 - sigma_temp*a1'*R1*a1 ) ) )^2; 176 | end 177 | [minVal,minIndex] = min(obj); 178 | w1 = u2F(:,1,minIndex); W1 = (w1*w1'); 179 | w2 = u2F(:,2,minIndex); W2 = (w2*w2'); 180 | Wsum = W1 + W2; 181 | 182 | 183 | % the overall transmitted covariance Eq.14 -------------------------------- 184 | C = blkdiag(R1,Wsum); % should be size (Nr+Nc) x (Nr+Nc) 185 | 186 | % overall transmitted beampattern gain Eq.15 187 | Pd = zeros(size(angleSpace)); BPrad = zeros(size(angleSpace)); BPcomm = zeros(size(angleSpace)); 188 | for i = 1:length(angleSpace) 189 | Pd(i) = abs( a(:,i)' * C * a(:,i) ); 190 | BPrad(i) = abs( a1(:,i)' * R1 * a1(:,i) ); 191 | BPcomm(i) = abs( a2(:,i)' * Wsum * a2(:,i) ); 192 | end 193 | 194 | 195 | % Plot Beampattern 196 | figure; plot(angleSpaceDeg,Pdesired); hold on 197 | plot(angleSpaceDeg, Pd, 'LineWidth', 2); hold on; 198 | plot(angleSpaceDeg, BPrad, 'LineWidth', 2); hold on; 199 | plot(angleSpaceDeg, BPcomm, 'LineWidth', 2); hold on; 200 | for n = 1:N 201 | line([commAngles(n) commAngles(n)], [0 10],'LineStyle', '--'); 202 | hold on 203 | end 204 | hold off; title('Beampattern 1'); 205 | legend('Desired','Sep1','Rad Only','Comm Only','Comm Angles'); grid on 206 | 207 | 208 | 209 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | 227 | 228 | 229 | 230 | 231 | 232 | 233 | 234 | -------------------------------------------------------------------------------- /Codes/Fan2018TWC by Nate Raymondi/SeparatedDeployment_SidelobeMin.m: -------------------------------------------------------------------------------- 1 | % Simulating the Separated Deployment beamformers presented in 2 | % "MU-MIMO Communications with MIMO Radar: From Co-existence to Joint 3 | % Transmission" - Liu et. al. 2018 4 | 5 | % Nate Raymondi, 8/13/2020 6 | 7 | % Set up the system ------------------------------------------------------- 8 | Nc = 16; % number of comms Tx antennas 9 | Nr = 16; % number of radar Tx antennas 10 | fc = 5e9; % assumed center freq 11 | c = 3e8; 12 | lamb = c/fc; 13 | spacing = lamb/2; 14 | radAntLoc = spacing*[0:Nr-1]; 15 | commAntLoc = spacing*[0:Nc-1]; 16 | Pc = 5; % comms power budget 17 | Pr = 5; % rad power budget 18 | N0 = 1; % noise variance 19 | 20 | 21 | % create ALL steering vectors --------------------------------------------- 22 | M = 181; % number of points on the angular grid 23 | angleSpace = linspace(-pi/2, pi/2, M); 24 | angleSpaceDeg = linspace(-90, 90, M); 25 | 26 | % rad --------------------------------------------------------------------- 27 | a1 = zeros(Nr, length(angleSpace)); % radar antenna steering vecs 28 | for j = 1:Nr 29 | a1(j,:) = exp((1i * 2 * pi * radAntLoc(j) / lamb) .* sin(angleSpace)); 30 | end 31 | 32 | % get the actual target steering vecs for convenience 33 | K = 2; % number of radar targets 34 | radAngles = [25 50]; 35 | aRad = zeros(Nr,K); R = zeros(Nr,Nr,K); alpha = zeros(1,K); 36 | for k = 1:K 37 | aRad(:,k) = a1(:,90+radAngles(k)); 38 | R(:,:,k) = aRad(:,k) * aRad(:,k)'; 39 | %alpha(k) = rand + 1i*rand; % target and channel coeffs if necessary 40 | end 41 | 42 | % comm -------------------------------------------------------------------- 43 | a2 = zeros(Nc, length(angleSpace)); % comm antenna steering vecs 44 | for j = 1:Nc 45 | a2(j,:) = exp((1i * 2 * pi * commAntLoc(j) / lamb) .* sin(angleSpace)); 46 | end 47 | 48 | % get the actual user steering vecs for convenience 49 | N = 2; % number of comms users 50 | commAngles = [90 -15]; 51 | Gamma = Pc*[0.5 0.2]; 52 | g = zeros(Nc,N); G = zeros(Nc,Nc,N); % channel from comms antennas to users 53 | f = zeros(Nr,N); F = zeros(Nr,Nr,N); % channel from rad antennas to users 54 | for n = 1:N 55 | g(:,n) = a2(:,90+commAngles(n)); 56 | G(:,:,n) = g(:,n) * g(:,n)'; 57 | 58 | f(:,n) = a1(:,90+commAngles(n)); 59 | F(:,:,n) = f(:,n) * f(:,n)'; 60 | end 61 | 62 | % introduce some further notation ----------------------------------------- 63 | a = [a1; a2]; % size Nr+Nc x M 64 | % NOTE: the way we have contructed our steering vectors and stacked them 65 | % into the matrices a, a1, a2 - these are equal to the A, A1, A2 from Eq.17 66 | 67 | 68 | 69 | % SECOND METHOD - SIDELOBE MINIMIZATION ----------------------------------- 70 | % first we specify the sidelobe region \Omega 71 | isSidelobeRegion = zeros(length(angleSpace),1); index = 1; 72 | beamwidth = 5; 73 | for i = -90:90 74 | if min(abs(i-radAngles(:))) >= beamwidth 75 | isSidelobeRegion(index) = 1; 76 | else 77 | isSidelobeRegion(index) = 0; 78 | end 79 | index = index+1; 80 | end 81 | %figure; plot(angleSpaceDeg,isSidelobeRegion); title('Check Target Directions') 82 | 83 | 84 | % solve the optimization in Eq.12 85 | index = 1; 86 | cvx_begin quiet 87 | variable R1(Nr,Nr) hermitian 88 | variable t 89 | minimize( -t ); 90 | subject to 91 | for i = -90:90 92 | if isSidelobeRegion(index) == 1 93 | (a1(:,90+radAngles(1))'*R1*a1(:,90+radAngles(1))) - (a1(:,index)'*R1*a1(:,index)) >= t; 94 | (a1(:,90+radAngles(2))'*R1*a1(:,90+radAngles(2))) - (a1(:,index)'*R1*a1(:,index)) >= t; 95 | end 96 | index = index+1; 97 | end 98 | (a1(:,90+radAngles(1)-beamwidth)'*R1*a1(:,90+radAngles(1)-beamwidth)) == ... 99 | (a1(:,90+radAngles(1))'*R1*a1(:,90+radAngles(1)))/2; 100 | (a1(:,90+radAngles(1)+beamwidth)'*R1*a1(:,90+radAngles(1)+beamwidth)) == ... 101 | (a1(:,90+radAngles(1))'*R1*a1(:,90+radAngles(1)))/2; 102 | (a1(:,90+radAngles(2)-beamwidth)'*R1*a1(:,90+radAngles(2)-beamwidth)) == ... 103 | (a1(:,90+radAngles(2))'*R1*a1(:,90+radAngles(2)))/2; 104 | (a1(:,90+radAngles(2)+beamwidth)'*R1*a1(:,90+radAngles(2)+beamwidth)) == ... 105 | (a1(:,90+radAngles(2))'*R1*a1(:,90+radAngles(2)))/2; 106 | diag(R1) == Pr*ones(Nr,1)/Nr; 107 | R1 == semidefinite(Nr); 108 | cvx_end 109 | 110 | 111 | % substitute R1 into Eq.19 and solve 112 | % must be solved jointly since Wi depends on all other Wj 113 | cvx_begin quiet 114 | variable W1opt(Nc,Nc) hermitian 115 | variable W2opt(Nc,Nc) hermitian 116 | variable sigma_temp 117 | minimize( square_pos(norm( diag( a2'*(W1opt+W2opt)*a2 - sigma_temp*(a1'*R1*a1) ) ,2)) ); 118 | subject to 119 | % SINR constraints for each user 120 | %abs(trace( conj(g(:,1))*transpose(g(:,1))*W1 ))/abs(( trace( conj(g(:,2))*transpose(g(:,2))*W1 ) + ... 121 | %trace( conj(f(:,1))*transpose(f(:,1))*R1 ) + N0 )) >= Gamma(1); 122 | real(trace( conj(g(:,1))*transpose(g(:,1))*W1opt ) - Gamma(1)*( trace( conj(g(:,2))*transpose(g(:,2))*W1opt ) + ... 123 | trace( conj(f(:,1))*transpose(f(:,1))*R1 ) )) >= N0*Gamma(1); 124 | real(trace( conj(g(:,2))*transpose(g(:,2))*W2opt ) - Gamma(2)*( trace( conj(g(:,1))*transpose(g(:,1))*W2opt ) + ... 125 | trace( conj(f(:,2))*transpose(f(:,2))*R1 ) )) >= N0*Gamma(2); 126 | % Power constraint 127 | trace(W1opt + W2opt) <= Pc; 128 | sigma_temp >= 0; 129 | W1opt == semidefinite(Nc); 130 | W2opt == semidefinite(Nc); 131 | cvx_end 132 | % NOTE - we are solving the SDR for W1 and W2, so we will have to recover 133 | % w1 and w2 134 | 135 | 136 | % Do randomization to get our feasible beamforming vectors w1 and w2------- 137 | nRand = 10; 138 | w1 = zeros(Nc,nRand); w2 = zeros(Nc,nRand); 139 | W1cov = zeros(Nc,Nc,nRand); W2cov = zeros(Nc,Nc,nRand); 140 | clear u1F; clear u2F; 141 | 142 | % generate and scale to meet power constraints 143 | for L = 1:nRand 144 | % generate nRand 145 | w1(:,L) = mvnrnd(zeros(Nc,1),W1opt) + 1i*mvnrnd(zeros(Nc,1),W1opt); 146 | w2(:,L) = mvnrnd(zeros(Nc,1),W2opt) + 1i*mvnrnd(zeros(Nc,1),W2opt); 147 | 148 | % scale them so they all adhere to norm constraint 149 | w1(:,L) = sqrt(trace(W1opt))*w1(:,L)/sqrt(w1(:,L)'*w1(:,L)); 150 | w2(:,L) = sqrt(trace(W2opt))*w2(:,L)/sqrt(w2(:,L)'*w2(:,L)); 151 | 152 | W1cov(:,:,L) = w1(:,L)*w1(:,L)'; 153 | W2cov(:,:,L) = w2(:,L)*w2(:,L)'; 154 | end 155 | 156 | % check all pairs to see if user 1 SINR constraints are met 157 | index1 = 1; index2 = 1; 158 | for i = 1:nRand 159 | for j = 1:nRand 160 | if real(trace( conj(g(:,1))*transpose(g(:,1))*W1cov(:,:,i) ) - Gamma(1)*( trace( conj(g(:,2))*transpose(g(:,2))*W1cov(:,:,i) ) + ... 161 | trace( conj(f(:,1))*transpose(f(:,1))*R1 ) )) >= N0*Gamma(1) 162 | % save this pair as feasible for user 1 163 | u1F(:,1,index1) = w1(:,i); u1F(:,2,index1) = w2(:,j); 164 | index1 = index1 + 1; 165 | end 166 | end 167 | end 168 | 169 | % check all user 1 feasible pairs to see if they're user 2 feasible 170 | for i = 1:size(u1F,3) 171 | if real(trace( conj(g(:,2))*transpose(g(:,2))*(u1F(:,2,i)*u1F(:,2,i)') ) - Gamma(2)*( trace( conj(g(:,2))*transpose(g(:,2))*(u1F(:,1,i)*u1F(:,1,i)') ) + ... 172 | trace( conj(f(:,2))*transpose(f(:,2))*R1 ) )) >= N0*Gamma(2) 173 | % save this pair as feasible for user 2 174 | u2F(:,1,index2) = u1F(:,1,i); u2F(:,2,index2) = u1F(:,2,i); 175 | index2 = index2 + 1; 176 | end 177 | end 178 | 179 | % find how many feasible sets we have, choose the one with the smallest 180 | % objective function value 181 | numFeasible = size(u2F,3); % this number better be [0,nRand^N] lol. Yes there are repeats but who cares 182 | WcovSum = zeros(Nc,Nc,numFeasible); obj = zeros(1,numFeasible); 183 | for i = 1:size(u2F,3) 184 | WcovSum(:,:,i) = (u2F(:,1,i)*u2F(:,1,i)') + (u2F(:,2,i)*u2F(:,2,i)'); 185 | obj(i) = ( norm( diag( a2'*WcovSum(:,:,i)*a2 - sigma_temp*a1'*R1*a1 ) ) )^2; 186 | end 187 | [minVal,minIndex] = min(obj); 188 | w1 = u2F(:,1,minIndex); W1 = (w1*w1'); 189 | w2 = u2F(:,2,minIndex); W2 = (w2*w2'); 190 | Wsum = W1 + W2; 191 | 192 | 193 | % the overall transmitted covariance Eq.14 -------------------------------- 194 | C = blkdiag(R1,Wsum); % should be size (Nr+Nc) x (Nr+Nc) 195 | 196 | % overall transmitted beampattern gain Eq.15 197 | Pd = zeros(size(angleSpace)); BPrad = zeros(size(angleSpace)); BPcomm = zeros(size(angleSpace)); 198 | for i = 1:length(angleSpace) 199 | Pd(i) = abs( a(:,i)' * C * a(:,i) ); 200 | BPrad(i) = abs( a1(:,i)' * R1 * a1(:,i) ); 201 | BPcomm(i) = abs( a2(:,i)' * Wsum * a2(:,i) ); 202 | end 203 | 204 | 205 | % Plot Beampattern 206 | figure; plot(angleSpaceDeg,Pdesired); hold on 207 | plot(angleSpaceDeg, Pd, 'LineWidth', 2); hold on; 208 | plot(angleSpaceDeg, BPrad, 'LineWidth', 2); hold on; 209 | plot(angleSpaceDeg, BPcomm, 'LineWidth', 2); hold on; 210 | for n = 1:N 211 | line([commAngles(n) commAngles(n)], [0 10],'LineStyle', '--'); 212 | hold on 213 | end 214 | hold off; title('Beampattern 1'); 215 | legend('Desired','Sep1','Rad Only','Comm Only','Comm Angles'); grid on -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Must-Reading Papers on Integrated Sensing and Communications (ISAC) 2 | Other Terms : Joint Radar Communications (JRC) / Joint Communication and Radar Sensing (JCAS) / Dual-Functional Radar Communications (DFRC) 3 | 4 | Definition: A design paradigm and corresponding enabling technologies, in which sensing and comms systems are integrated to efficiently utilize congested wireless/hardware resources, and even to pursue mutual benefits. 5 | 6 | *Aims: include reproducible codes, good papers and a research libary.* 7 | 8 | Contributed by Yuanhao Cui, BUPT, and Fan Liu, SUSTech 9 | 10 | Supported by IEEE ComSoc ISAC Emerging Technology Inititive (ETI) & IEEE SPS ISAC Technical Working Group (TWG) 11 | 12 | ## [Content](#content) 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 |
1. Surveys and Tutorials
 1.1 Basic Concept 1.2 Signal Processing
 1.3 Communication and Networking 1.4 Mobile Computing
2. Fundamental Theory and Performance Analysis
3. Signal Processing - Communication Centric
 3.1 Standardized Waveform 3.2 Transceiver Design
 3.3 Infrastracture Enhancement 3.4 Resource and Interference Management
4. Signal Processing - Sensing Centric
 4.1 Waveform Design 4.2 Sensing Data Processing
5. Signal Processing - Joint Design
6. Networking
 6.1 Radar Networking 6.2 Sensor Networking
 6.3 ISAC Networking
7. Specturm Sharing
8. Mobile Computing - WiFi Sensing
 8.1 Human Activity Recognition 8.2 Wireless Imaging
 8.3 Control Flow
9. Applications and Demonstrations
 9.1 Environmental Monitoring 9.2 Multi-Functional Network
 9.3 Health and Elderly Care 9.4 Remote Sensing
 9.5 Site-Specified Radio Map 9.6 Simultaneous Localization and Mapping
 9.7 Security and Privacy 9.8 Demonstrations
73 | 74 | 75 | 76 | 77 | ## [1. Surveys and Tutorials](#1-surveys-and-tutorials) 78 | 79 | ### [1.1 Basic Concept](##11-basic-concept) 80 | 81 | 1. **Integrated Sensing and Communications: Towards Dual-functional Wireless Networks for 6G and Beyond.** IEEE JSAC, 2022. [Journal](https://ieeexplore.ieee.org/document/9737357). 82 | 83 | *F. Liu, Y. Cui, C. Masouros, J. Xu, T. X. Han, Y. C. Eldar, S. Buzzi* 84 | 85 | 1. **Integrating Sensing and Communications for Ubiquitous IoT: Applications, Trends and Challenges.** IEEE Network, 2021. [Magazine](https://ieeexplore.ieee.org/document/9606831/). 86 | 87 | *Y. Cui, F. Liu, X. Jing, J. Mu* 88 | 89 | 1. **Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead.** IEEE TCOM, 2020. [Journal](https://ieeexplore.ieee.org/document/8999605). [Code](https://github.com/yuanhao-cui/Must-Reading-on-ISAC/blob/main/Codes/Fan2020TCOM/Fan_DFRC.m) 90 | 91 | *F. Liu, C. Masouros, A. P. Petropulu, H. Griffiths, L. Hanzo* 92 | 93 | 1. **Waveform Design and Signal Processing Aspects for Fusion of Wireless Communications and Radar Sensing.** Proceedings of the IEEE, 2011. [Magazine](https://ieeexplore.ieee.org/document/5776640). 94 | 95 | *C. Sturm, W. Wiesbeck* 96 | 97 | 1. **Seventy Years of Radar and Communications: The road from separation to integration.** IEEE SPM, 2023.[Magazine](https://ieeexplore.ieee.org/document/10188491). 98 | 99 | *F. Liu, L. Zheng, Y. Cui, C. Masouros, A. P. Petropulu, H. Griffiths, Y. C. Eldar* 100 | 101 | 1. **Dual-Function Radar Communication Systems: A Solution to the Spectrum Congestion Problem.** IEEE SPM, 2019. [Magazine](https://ieeexplore.ieee.org/document/8828023). 102 | 103 | *A. Hassanien, M. G. Amin, E. Aboutanios, B. Himed* 104 | 105 | 1. **Radar-Communications Convergence: Coexistence, Cooperation, and Co-Design.** IEEE TCCN, 2017. [Journal](https://ieeexplore.ieee.org/document/7855671) 106 | 107 | *A. R. Chiriyath, B. Paul, D. W. Bliss* 108 | 109 | 110 | 111 | ### [1.2 Signal Processing](#1.2) 112 | 113 | 1. **An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing.** IEEE JSTSP, 2021. [Journal](https://ieeexplore.ieee.org/document/9540344/). 114 | 115 | *J. A. Zhang, F. Liu, C. Masouros, R. W. Heath, Z. Feng, L. Zhang, A. Petropulu* 116 | 117 | 1. **Toward Millimeter-Wave Joint Radar Communications: A Signal Processing Perspective.** IEEE SPM, 2019. [Magazine](https://ieeexplore.ieee.org/document/8828030). 118 | 119 | *K. V. Mishra, M. R. Bhavani Shankar, V. Koivunen, B. Ottersten, S. A. Vorobyov* 120 | 121 | 1. **Joint Radar-Communications Strategies for Autonomous Vehicles Combining Two Key Automotive Technologies.** IEEE SPM, 2020. [Magazine](https://ieeexplore.ieee.org/document/9127852). 122 | 123 | *D. Ma, N. Shlezinger, T. Huang, Y. Liu, Y. C. Eldar* 124 | 125 | 1. **Signaling Strategies for Dual-function Radar Communications: An Overview.** IEEE AESM, 2016. [Magazine](https://ieeexplore.ieee.org/document/7746569). 126 | 127 | *A. Hassanien, M. G. Amin, Y. D. Zhang, F. Ahmad* 128 | 129 | 1. **Radar and Communication Coexistence: An Overview: A Review of Recent Methods.** IEEE SPM, 2019. [Magazine](https://ieeexplore.ieee.org/document/8828016). 130 | 131 | *L. Zheng, M. Lops, Y. C. Eldar, X. Wang* 132 | 133 | 1. **MIMO Radar for Advanced Driver-Assistance Systems and Autonomous Driving: Advantages and Challenges.** IEEE SPM, 2020. [Magazine](https://ieeexplore.ieee.org/document/9127853). 134 | 135 | *S. Sun, A. P. Petropulu, H. V. Poor* 136 | 137 | 1. **Survey of RF Communications and Sensing Convergence Research.** IEEE ACCESS, 2016. [Journal](https://ieeexplore.ieee.org/document/7782415). 138 | 139 | *B. Paul, A. R. Chiriyath, D. W. Bliss* 140 | 141 | 142 | 143 | ### [1.3 Communication and Networking](#1.3) 144 | 145 | 1. **Enabling Joint Communication and Radio Sensing in Mobile Networks--A Survey.** IEEE COMST, 2022. [Journal](https://ieeexplore.ieee.org/abstract/document/9585321). 146 | 147 | *J. Zhang, Md. Rahman, K. Wu, X. Huang, Y. Guo, S. Chen, J. Yuan* 148 | 149 | 1. **A Tutorial on Joint Radar and Communication Transmission for Vehicular Networks - Part I, II, and III.** IEEE COMML, 2020. [Letter](https://ieeexplore.ieee.org/document/9201513), [Letter](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9201355), [Letter](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9201311). 150 | 151 | *F. Liu, C. Masouros* 152 | 153 | 1. **Perceptive Mobile Network: Cellular Networks With Radio Vision via Joint Communication and Radar Sensing.** IEEE VTM, 2020. [Magazine](https://ieeexplore.ieee.org/document/9296833). 154 | 155 | *A. Zhang, M. L. Rahman, X. Huang, Y. J. Guo, S. Chen, R. W. Heath* 156 | 157 | 1. **Leveraging Sensing at the Infrastructure for mmWave Communication.** IEEE COMMAG, 2020. [Magazine](https://ieeexplore.ieee.org/document/9162000). 158 | 159 | *A. Ali, N. Gonzalez-Prelcic, R. W. Heath, A. Ghosh* 160 | 161 | 1. **Internet of Radars: Sensing versus Sending with Joint Radar-Communications.** IEEE COMMAG, 2020. [Magazine](https://ieeexplore.ieee.org/document/9214381). 162 | 163 | *O. B. Akan, M. Arik* 164 | 165 | 1. **Full Duplex Radio/ Radar Technology: The Enabler for Advanced Joint Communication and Sensing.** IEEE WCM, 2021. [Magazine](https://ieeexplore.ieee.org/abstract/document/9363029). 166 | 167 | *C. B. Barneto, S. D. Liyanaarachchi, M. Heino, T. Riihonen, M. Valkama* 168 | 169 | 1. **Communications and Sensing: An Opportunity for Automotive Systems.** IEEE SPM, 2020. [Magazine](https://ieeexplore.ieee.org/document/9129848) 170 | 171 | *R. W. Heath* 172 | 173 | 174 | 175 | ### [1.4 Mobile Computing](#1.4) 176 | 177 | 1. **WiFi Sensing with Channel State Information: A Survey.** ACM CSUR, 2019. [Journal](https://dl.acm.org/doi/abs/10.1145/3310194). 178 | 179 | *Y. Ma, G. Zhou, S. Wang* 180 | 181 | 1. **Wireless Sensing for Human Activity: A Survey.** IEEE COMST, 2019. [Journal](https://ieeexplore.ieee.org/document/8794643) 182 | 183 | *J. Liu, H. Liu, Y. Chen, Y. Wang, C. Wang* 184 | 185 | 1. **Future Millimeter-Wave Indoor Systems: A Blueprint for Joint Communication and Sensing.** IEEE Computer, 2019. [Magazine](https://ieeexplore.ieee.org/document/8747215) 186 | 187 | *M. Alloulah, H. Huang* 188 | 189 | 1. **Joint Design of Sensing and Communication Systems for Smart Homes.** IEEE Network, 2020. [Magazine](https://ieeexplore.ieee.org/document/9143269) 190 | 191 | *Q. Huang, H. Chen, Q. Zhang* 192 | 193 | 1. **Device-Free Wireless Sensing: Challenges, Opportunities, and Applications.** IEEE Network, 2018. [Magazine](https://ieeexplore.ieee.org/abstract/document/8284052) 194 | 195 | *J. Wang, Q. Gao, M. Pan, Y. Fang* 196 | 197 | 198 | 199 | ## [2. Fundamental Theory and Performance Analysis](#2) 200 | 201 | 1. **On the Fundamental Tradeoff of Integrated Sensing and Communications Under Gaussian Channels.*[Journal](https://ieeexplore.ieee.org/abstract/document/10147248)* 202 | 203 | *Y. Xiong, F. Liu, Y. Cui, W. Yuan, T. X. Han, G. Caire* 204 | 205 | 1. **Joint State Sensing and Communication: Optimal Tradeoff for a Memoryless Case.** IEEE ISIT, 2018. [Conference](https://ieeexplore.ieee.org/document/8437621) 206 | 207 | *M. Kobayashi, G. Caire, G. Kramer* 208 | 209 | 1. **Joint Sensing and Communication over Memoryless Broadcast Channels.** IEEE ISIT, 2020. [Conference](https://ieeexplore.ieee.org/abstract/document/9457571) 210 | 211 | *M.Ahmadipour, M.Wigger, M. Kobayashi* 212 | 213 | 1. **A Survey on Fundamental Limits of Integrated Sensing and Communication.** Arxiv, 2021. [Journal](https://arxiv.org/abs/2104.09954) 214 | 215 | *A. Liu, Z. Huang, M. Li, Y. Wan, W. Li, T. X. Han, C. Liu, R. Du, D. T. K. Ping, J. Liu, Y. Shen, F. Colone, K. Chetty* 216 | 217 | 1. **Joint Transmission and State Estimation: A Constrained Channel Coding Approach.** IEEE TIT, 2011. [Journal](https://ieeexplore.ieee.org/document/6034756) 218 | 219 | *W. Zhang, S. Vedantam, U. Mitra* 220 | 221 | 1. **Inner Bounds on Performance of Radar and Communications Co-Existence.** IEEE TSP, 2016. [Journal](https://ieeexplore.ieee.org/document/7279172) 222 | 223 | *A. R. Chiriyath, B. Paul, G. M. Jacyna, D. W. Bliss* 224 | 225 | 1. **On the Capacity of the AWGN Channel With Additive Radar Interference.** IEEE TCOM, 2017. [Journal](https://ieeexplore.ieee.org/document/8070342) 226 | 227 | *S. Shahi, D. Tuninetti, N. Devroye* 228 | 229 | 1. **Performance Gains From Cooperative MIMO Radar and MIMO Communication Systems.** IEEE SPL, 2018. [Letter](https://ieeexplore.ieee.org/document/8531782) 230 | 231 | *Q. He, Z. Wang, J. Hu, R. S. Blum* 232 | 233 | 1. **A Perspective on Degrees of Freedom for Radar in Radar-Communication Interference Channel.** IEEE ACSSC, 2018. [Conference](https://ieeexplore.ieee.org/document/8645069) 234 | 235 | *Y. Cui, V. Koivunen, X. Jing* 236 | 237 | 1. **Performance Tradeoffs of Joint Radar-Communication Networks.** IEEE WCL, 2018. [Letter](https://ieeexplore.ieee.org/document/8436015) 238 | 239 | *P. Ren, A. Munari, M. Petrova* 240 | 241 | 1. **Analysis of An LTE Waveform for Radar Applications.** IEEE RADAR, 2014. [Conference](https://ieeexplore.ieee.org/document/6875584) 242 | 243 | *A. Evers, J. A. Jackson* 244 | 245 | 1. **Performance Tradeoff in a Unified Passive Radar and Communications System.** IEEE SPL, 2017. [Journal](https://ieeexplore.ieee.org/document/7962141) 246 | 247 | *B. K. Chalise, M. G. Amin, B. Himed* 248 | 249 | 1. **Massive MIMO Radar for Target Detection.** IEEE TSP, 2020. [Journal](https://ieeexplore.ieee.org/document/8962251) 250 | 251 | *S. Fortunati, L. 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Wymeersch, M. Win* 626 | 627 | 628 | ### [6.3 ISAC Networking](#6.3) 629 | 630 | 1. **RadChat: Spectrum Sharing for Automotive Radar Interference Mitigation.** IEEE TITS, 2021. [Journal](https://ieeexplore.ieee.org/abstract/document/8943325) 631 | 632 | *C. Aydogdu, M. F. Keskin, N. Garcia, H. Wymeersch, D. W. Bliss* 633 | 634 | 1. **Sensing and Communication Co-Design for Status Update in Multiaccess Wireless Networks.** IEEE TMC, 2021. [Journal](https://ieeexplore.ieee.org/abstract/document/9525223) 635 | 636 | *F. Peng, Z. Jiang, S. Zhou, Z. Niu, S. Zhang* 637 | 638 | 639 | ## [7. Specturm Sharing](#7) 640 | 641 | 1. **Optimum Co-Design for Spectrum Sharing between Matrix Completion Based MIMO Radars and a MIMO Communication System.** IEEE TSP, 2016. [Journal](https://ieeexplore.ieee.org/document/7470514) 642 | 643 | *B. Li, A. P. Petropulu, W. Trappe* 644 | 645 | 1. **Joint Design of Overlaid Communication Systems and Pulsed Radars.** IEEE TSP, 2017. [Journal](https://ieeexplore.ieee.org/document/8114253) 646 | 647 | *L. Zheng, M. Lops, X. Wang, E. Grossi* 648 | 649 | 1. **MIMO Radar and Cellular Coexistence: A Power-Efficient Approach Enabled by Interference Exploitation.** IEEE TSP, 2018. [Journal](https://ieeexplore.ieee.org/document/8355705) 650 | 651 | *F. Liu, C. Masouros, A. Li, T. Ratnarajah, J. Zhou* 652 | 653 | 1. **Cognitive Radar: A Way of the Future.** IEEE SPM, 2006. [Journal](https://ieeexplore.ieee.org/document/1593335) 654 | 655 | *S. Haykin* 656 | 657 | 1. **Radar Spectrum Engineering and Management: Technical and Regulatory Issues.** Proceedings of the IEEE, 2014. [Magazine](https://ieeexplore.ieee.org/document/6967722) 658 | 659 | *H. Griffiths, L. Cohen, S. Watts, E, Mokole, C. Baker, M. Wicks, S. Blunt.* 660 | 661 | 1. **Co-Design for Overlaid MIMO Radar and Downlink MISO Communication Systems via Cramér–Rao Bound Minimization.** IEEE TSP, 2019. [Journal](https://ieeexplore.ieee.org/document/8892631) 662 | 663 | *Z. Cheng, B. Liao, S. Shi, Z. He, J. Li* 664 | 665 | 1. **Joint Transmit Designs for Coexistence of MIMO Wireless Communications and Sparse Sensing Radars in Clutter.** IEEE TAES, 2017. [Journal](https://ieeexplore.ieee.org/document/7950274) 666 | 667 | *B. Li, A. P. Petropulu* 668 | 669 | 1. **Joint System Design for Coexistence of MIMO Radar and MIMO Communication.** IEEE TSP, 2018. [Journal](https://ieeexplore.ieee.org/document/8352726) 670 | 671 | *J. Qian, M. Lops, Le Zheng, X. Wang, Z. He* 672 | 673 | 1. **Opportunistic Sharing Between Rotating Radar and Cellular.** IEEE JSAC, 2012. [Journal](https://ieeexplore.ieee.org/document/6331681) 674 | 675 | *R. Saruthirathanaworakun, J. M. Peha, L. M. Correia* 676 | 677 | 1. **Mutual Information based Radar Waveform Design for Joint Radar and Cellular Communication Systems.** IEEE ICASSP, 2016. [Conference](https://ieeexplore.ieee.org/document/7472362) 678 | 679 | *M. Bica, K. Huang, V. Koivunen, U. Mitra* 680 | 681 | 1. **Spectral Coexistence of MIMO Radar and MIMO Cellular System.** IEEE TAES, 2017. [Journal](https://ieeexplore.ieee.org/document/7814210) 682 | 683 | *J. A. Mahal, A. Khawar, A. Abdelhadi, T. C. Clancy* 684 | 685 | 1. **Adaptive Interference Removal for Uncoordinated Radar/Communication Coexistence.** IEEE JSTSP, 2017. [Journal](https://ieeexplore.ieee.org/document/8233171) 686 | 687 | *L. Zheng, M. Lops, X. Wang* 688 | 689 | 1. **Joint Design of Surveillance Radar and MIMO Communication in Cluttered Environments.** IEEE TSP, 2020. [Journal](https://ieeexplore.ieee.org/document/9001239) 690 | 691 | *E. Grossi, M. Lops, L. Venturino* 692 | 693 | 1. **Interference Alignment Based Precoder-Decoder Design for Radar Communication Co-existence.** IEEE ACSSC, 2018. [Conference](https://ieeexplore.ieee.org/document/8335561) 694 | 695 | *Y. Cui, V. Koivunen, X. Jing* 696 | 697 | 1. **Information Theoretic Approach for Waveform Design in Coexisting MIMO Radar and MIMO Communications.** IEEE ICASSP, 2020. [Conference](https://ieeexplore.ieee.org/document/9053048) 698 | 699 | *M. Alaee-Kerharoodi, S. M. R. Bhavani, K. V. Mishra and B. Ottersten* 700 | 701 | 1. **Multi-constraint Spectral Co-design for Colocated MIMO Radar and MIMO Communications.** IEEE ICASSP, 2020. [Conference](https://ieeexplore.ieee.org/document/9054680) 702 | 703 | *S. H. Dokhanchi, M. R. Bhavani Shankar, K. V. Mishra, B. Ottersten* 704 | 705 | 1. **Communications and Radar Coexistence in the Massive MIMO Regime: Uplink Analysis.** IEEE TWC, 2019. [Journal](https://ieeexplore.ieee.org/document/8871348) 706 | 707 | *C. D’Andrea, S. Buzzi, M. Lops* 708 | 709 | 1. **Interference Removal for Radar/Communication Co-Existence: The Random Scattering Case.** IEEE TWC, 2019. [Journal](https://ieeexplore.ieee.org/document/8777296) 710 | 711 | *Y. Li, L. Zheng, M. Lops, X. Wang* 712 | 713 | 1. **Power Allocation and Co-Design of Multicarrier Communication and Radar Systems for Spectral Coexistence.** IEEE TSP, 2019. [Journal](https://ieeexplore.ieee.org/document/8728046) 714 | 715 | *F. Wang, H. Li, M. A. Govoni* 716 | 717 |
718 | more 719 | 720 | 1. **Integrated Waveform for a Joint Radar-Communication System With High-Speed Transmission.** IEEE WCL, 2019. [Letter](https://ieeexplore.ieee.org/document/8693859) 721 | 722 | *Q. Li, K. Dai, Y. Zhang, H. Zhang* 723 | 724 | 1. **Deep Learning Constellation Design for the AWGN Channel with Additive Radar Interference.** IEEE TCOM, 2018. [Journal](https://ieeexplore.ieee.org/document/8490882) 725 | 726 | *F. Alberge* 727 | 728 | 1. **Coexistence of MIMO Radar and FD MIMO Cellular Systems With QoS Considerations.** IEEE TWC, 2018. [Journal](https://ieeexplore.ieee.org/document/8447442) 729 | 730 | *S. Biswas, K. Singh, O. Taghizadeh, T. Ratnarajah* 731 | 732 | 1. **Opportunistic Radar in IEEE 802.11ad Networks.** IEEE TSP, 2018. [Journal](https://ieeexplore.ieee.org/document/8309274) 733 | 734 | *E. Grossi, M. Lops, L. Venturino, A. Zappone* 735 | 736 | 1. **Transmit Designs for Spectral Coexistence of MIMO Radar and MIMO Communication Systems.** IEEE TCSII, 2018. [Journal](https://ieeexplore.ieee.org/document/8331117) 737 | 738 | *J. Qian, Z. He, N. Huang, B. Li* 739 | 740 | 1. **Robust MIMO Beamforming for Cellular and Radar Coexistence.** IEEE WCL, 2017. [Letterl](https://ieeexplore.ieee.org/document/7898445) 741 | 742 | *F. Liu, C. Masouros, A. Li, T. Ratnarajah* 743 | 744 | 1. **Spectral Coexistence of MIMO Radar and MIMO Cellular System.** IEEE TAES, 2017. [Journal](https://ieeexplore.ieee.org/document/7814210) 745 | 746 | *J. A. Mahal, A. Khawar, A. Abdelhadi, T. C. Clancy* 747 | 748 | 1. **Spectrum Sharing between a Surveillance Radar and Secondary Wi-Fi Networks.** IEEE TAES, 2016. [Journal](https://ieeexplore.ieee.org/document/7511869) 749 | 750 | *F. Hessar, S. Roy* 751 | 752 | 1. **On the Co-Existence of TD-LTE and Radar Over 3.5 GHz Band: An Experimental Study.** IEEE WCL, 2016. [Letter](https://ieeexplore.ieee.org/document/7462190) 753 | 754 | *J. H. Reed et al.* 755 | 756 | 1. **Spectrum Sharing of Radar and Wi-Fi Networks: The Sensing/Throughput Tradeoff.** IEEE TCCN, 2015. [Journal](https://ieeexplore.ieee.org/document/7460082) 757 | 758 | *H. Safavi-Naeini, S. Roy, S. Ashrafi* 759 | 760 | 1. **MIMO OFDM Radar with Communication and Interference Cancellation Features.** IEEE RADAR, 2014. [Conference](https://ieeexplore.ieee.org/document/6875596) 761 | 762 | *Y. L. Sit, T. Zwick* 763 | 764 | 1. **Radar Waveform Design in a Spectrally Crowded Environment Via Nonconvex Quadratic Optimization.** IEEE TAES, 2014. [Journal](https://ieeexplore.ieee.org/document/6850145) 765 | 766 | *A. Aubry, A. De Maio, M. Piezzo, A. Farina* 767 | 768 | 1. **Interference Mitigation Processing for Spectrum-Sharing Between Radar and Wireless Communications Systems.** IEEE TAES, 2013. [Journal](https://ieeexplore.ieee.org/document/6933960) 769 | 770 | *H. Deng, B. Himed* 771 | 772 |
773 | 774 | 775 | 776 | ## [8. Mobile Computing - WiFi Sensing](#8) 777 | 778 | ### [8.1 Human Activity Recognition](#8.1) 779 | 780 | 1. **We Can Hear You with Wi-Fi!.** IEEE TMC, 2016. [Journal](https://ieeexplore.ieee.org/document/7384744) 781 | 782 | *G. Wang, Y. Zou, Z. Zhou, K. Wu, L. M. Ni* 783 | 784 | 2. **WiFall: Device-Free Fall Detection by Wireless Networks.** IEEE TMC, 2016. [Journal](https://ieeexplore.ieee.org/document/7458186) 785 | 786 | *Y. Wang, K. Wu, L. M. Ni* 787 | 788 | 3. **Recognizing Keystrokes Using WiFi Devices.** IEEE JSAC, 2017. [Journal](https://ieeexplore.ieee.org/document/7875144) 789 | 790 | *YK. Ali, A. X. Liu, W. Wang, M. Shahzad* 791 | 792 | 4. **Device-Free Human Activity Recognition Using Commercial WiFi Devices.** IEEE JSAC, 2017. [Journal](https://ieeexplore.ieee.org/document/7875144) 793 | 794 | *W. Wang, A. X. Liu, M. Shahzad, K. Ling, S. Lu* 795 | 796 | 5. **Toward Centimeter-Scale Human Activity Sensing with Wi-Fi Signals.** IEEE Computer, 2018. [Magazine](https://ieeexplore.ieee.org/document/7807197/) 797 | 798 | *D. Zhang, H. Wang, D. Wu* 799 | 800 | 6. **A Survey on Behavior Recognition Using WiFi Channel State Information.** IEEE COMMAG, 2017. [Journal](https://ieeexplore.ieee.org/document/8067693) 801 | 802 | *S. Yousefi, H. Narui, S. Dayal, S. Ermon, S. Valaee* 803 | 804 | 805 | ### [8.2 Wireless Imaging](#8.2) 806 | 807 | 1. **See through Walls with WiFi!.** MobiCom, 2013. [Conference](https://dl.acm.org/doi/pdf/10.1145/2486001.2486039) 808 | 809 | *A. Fadel, D. Katabi* 810 | 811 | 2. **Through-the-Wall Sensing of Personnel Using Passive Bistatic WiFi Radar at Standoff Distances.** IEEE TGRS, 2011. [Journal](https://ieeexplore.ieee.org/document/6020778) 812 | 813 | *K. Chetty, G. E. Smith, K. Woodbridge* 814 | 815 | 816 | 817 | ### [8.3. Control Flow](#8.4) 818 | 819 | 1. **Coordinated Cognitive Risk Control for Bridging Vehicular Radar and Communication Systems.** IEEE TITS, 2020. [Journal](https://ieeexplore.ieee.org/document/9292428) 820 | 821 | *S. Feng, S. Haykin* 822 | 823 | 824 | ## [9. Applications and Demonstrations](#9) 825 | 826 | ### [9.1 Environmental Monitoring](#9.1) 827 | 828 | 1. **Environmental Monitoring by Wireless Communication Networks.** Science, 2006. [Magazine](https://www.tau.ac.il/~pinhas/papers/2006/Messer_et_al_SCIENCE_2006.pdf) 829 | 830 | *H. Messer, A. Zinevich, P. Alpert* 831 | 832 | 2. **Country-wide rainfall maps from cellular communication networks.** PNAS, 2013. [Magazine](https://www.pnas.org/content/pnas/110/8/2741.full.pdf) 833 | 834 | *A. Overeem, H. Leijnse, R. Uijlenhoet* 835 | 836 | 3. **Rain Rate Estimation Using Measurements From Commercial Telecommunications Links.** IEEE TSP, 2009. [Journal](https://ieeexplore.ieee.org/abstract/document/4749357) 837 | 838 | *O. Goldshtein, H. Messer, A. Zinevich* 839 | 840 | 4. **Recurrent Neural Network for Rain Estimation Using Commercial Microwave Links.** IEEE TGRS, 2020. [Journal](https://ieeexplore.ieee.org/document/9153027?denied=) 841 | 842 | *H. V. Habi, H. Messer* 843 | 844 | 845 | ### [9.2 Multi-Functional Network](#9.2) 846 | 847 | 1. **Vehicular RF Convergence: Simultaneous Radar, Communications, and PNT for Urban Air Mobility and Automotive Applications.** IEEE RadarConf, 2020. [Conference](https://ieeexplore.ieee.org/abstract/document/9266507) 848 | 849 | *A. Herschfelt, A. Chiriyath, D. W. Bliss, C. D. Richmond, U. Mitra, S. D. Blunt* 850 | 851 | 2. **Convergent Communication, Sensing and Localization in 6G Systems: An Overview of Technologies, Opportunities and Challenges.** IEEE ACESS, 2021. [Journal](https://ieeexplore.ieee.org/abstract/document/9330512) 852 | 853 | *C. De Lima et al.* 854 | 855 | 3. **Integrated Sensing, Computation and Communication in B5G Cellular Internet of Things.** IEEE TWC, 2021. [Journal](https://ieeexplore.ieee.org/abstract/document/9206051) 856 | 857 | *Q. Qi, X. Chen, C. Zhong, Z. Zhang* 858 | 859 | 4. **Overview of Naval Multifunction RF Systems.** IEEE EURAD, 2018. [Conference](https://ieeexplore.ieee.org/document/8546521) 860 | 861 | *P. W. Moo, D. J. DiFilippo* 862 | 863 | 5. **The Advanced Multifunction RF Concept.** IEEE TMTT, 2005. [Journal](https://ieeexplore.ieee.org/document/1406306) 864 | 865 | *G. C. Tavik et al.* 866 | 867 | 6. **Overview of Advanced Multifunction RF System (AMRFS).** IEEE PAST, 2002. [Conference](https://ieeexplore.ieee.org/document/858893) 868 | 869 | *P. K. Hughes, J. Y. Choe* 870 | 871 | 872 | ### [9.3 Health and Elderly Care](#8.3) 873 | 874 | 1. **Assessment of Medication Self-administration using Artificial Intelligence.** Nature Med, 2021. [Magazine](https://www.nature.com/articles/s41591-021-01273-1.pdf) 875 | 876 | *M. Zhao, K. Hoti, H. Wang, A. Raghu, D. Katabi* 877 | 878 | 2. **Vital-sign Monitoring and Spatial Tracking of Multiple People using a Contactless Radar-based Sensor.** Nature Electronics, 2019. [Magazine](https://www.nature.com/articles/s41928-019-0258-6) 879 | 880 | *M. Mercuri, I. R. Lorato, Y-H. Liu, F. Wieringa, C. V. Hoof, T. Torfs* 881 | 882 | 3. **Radar Signal Processing for Sensing in Assisted Living: The Challenges Associated With Real-Time Implementation of Emerging Algorithms.** IEEE SPM, 2019. [Magazine](https://ieeexplore.ieee.org/document/8746868) 883 | 884 | *J.L. Kernec, F. Fioranelli, C. Ding, H. Zhao, L. Sun, H. Hong, J. Lorandel, O. Romain* 885 | 886 | 4. **Exploiting WiFi Channel State Information for Residential Healthcare Informatics.** IEEE COMMAG, 2018. [Magazine](https://ieeexplore.ieee.org/document/8360863) 887 | 888 | *B. Tan, Q. Chen, K. Chetty, K. Woodbridge, W. Li, R. Piechocki* 889 | 890 | 5. **Radar Signal Processing for Elderly Fall Detection: The Future for In-home Monitoring.** IEEE SPM, 2016. [Magazine](https://ieeexplore.ieee.org/document/7421368) 891 | 892 | *M. G. Amin, Y. D. Zhang, F. Ahmad, K. C. D. Ho* 893 | 894 | 895 | ### [9.4 Remote Sensing](#9.3) 896 | 897 | 1. **Noncontact Vital Sign Detection With UAV-Borne Radars: An Overview of Recent Advances.** IEEE VTM, 2021. [Magazine](https://ieeexplore.ieee.org/abstract/document/9478877) 898 | 899 | *Y. Rong, R. Gutierrez, K. V. Mishra, D. W. Bliss* 900 | 901 | 2. **First Demonstration of Joint Wireless Communication and High-Resolution SAR Imaging Using Airborne MIMO Radar System.** IEEE TGRS, 2019. [Journal](https://ieeexplore.ieee.org/document/8718390) 902 | 903 | *J. Wang, X. Liang, L. Chen, L. Wang, K. Li* 904 | 905 | 906 | 907 | 908 | ### [9.5 Site-Specified Radio Map](#9.4) 909 | 910 | 1. **Toward Environment-Aware 6G Communications via Channel Knowledge Map.** IEEE WCM, 2021. [Magazine](https://ieeexplore.ieee.org/abstract/document/9373011) 911 | 912 | *Y. Zeng, X. Xu* 913 | 914 | 915 | 916 | ### [9.6 Simultaneous Localization and Mapping](#9.5) 917 | 918 | 1. **Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation.** Arxiv, 2021. [Journal](https://arxiv.org/pdf/2102.11593.pdf) 919 | 920 | *C. B. Barneto, E. R. Foi, M. F. Keskin, T. Riihonen, M. Turunen, J. Talvitie, H. Wymeersch, M. Valkama* 921 | 922 | 923 | 924 | ### [9.7 Security and Privacy](#9.6) 925 | 926 | 1. **Secure Radar-Communication Systems With Malicious Targets: Integrating Radar, Communications and Jamming Functionalities.** IEEE TWC, 2020. [Journal](https://ieeexplore.ieee.org/abstract/document/9199556) 927 | 928 | *N. Su, F. Liu, C. Masouros* 929 | 930 | 2. **Secrecy Rate Optimizations for MIMO Communication Radar.** IEEE TAES, 2018. [Journal](https://ieeexplore.ieee.org/document/8327462) 931 | 932 | *A. Deligiannis, A. Daniyan, S. Lambotharan, J. A. Chambers* 933 | 934 | 3. **Intrapulse Radar-Embedded Communications.** IEEE TAES, 2010. [Journal](https://ieeexplore.ieee.org/document/5545182) 935 | 936 | *S. D. Blunt, P. Yatham, J. Stiles* 937 | 938 | 4. **Intrapulse Radar-embedded Communications Via Multiobjective Optimization.** IEEE TAES, 2015. [Journal](https://ieeexplore.ieee.org/document/7376230) 939 | 940 | *D. Ciuonzo, A. De Maio, G. Foglia, M. Piezzo* 941 | 942 | 5. **On Radar Privacy in Shared Spectrum Scenarios.** IEEE ICASSP, 2019. [Conference](https://ieeexplore.ieee.org/document/8682745) 943 | 944 | *A. Dimas, M. A. Clark, B. Li, K. Psounis, A. P. Petropulu* 945 | 946 | 947 | ### [9.8 Demonstrations](#9.7) 948 | 949 | 1. **JCR70: A Low-Complexity Millimeter-Wave Proof-of-Concept Platform for A Fully-Digital MIMO Joint Communication-Radar.** IEEE OJVT, 2021. [Journal](https://ieeexplore.ieee.org/abstract/document/9392306) 950 | 951 | *P. Kumari, A. Mezghani, R. W. Heath Jr* 952 | 953 | 1. **Simultaneous Radar and Communications Emissions from a Common Aperture, Part I,II.** IEEE RadarConf, 2017. [Conference](https://ieeexplore.ieee.org/document/7944478), [Conference](https://ieeexplore.ieee.org/abstract/document/7944480) 954 | 955 | *P. M. McCormick, S. D. Blunt, J. G. Metcalf* 956 | 957 | 1. **First Demonstration of Joint Wireless Communication and High-Resolution SAR Imaging Using Airborne MIMO Radar System.** IEEE TGRS, 2019. [Journal](https://ieeexplore.ieee.org/document/8718390) 958 | 959 | *J. Wang, X. Liang, L. Chen, L. Wang, K. Li* 960 | 961 | 1. **Sensing and Communication Integrated System for Autonomous Driving Vehicles.** IEEE InfocomWorkshop, 2020. [Conference](https://ieeexplore.ieee.org/document/9162963) 962 | 963 | *Q. Zhang, H. Sun, Z. Wei, Z. Feng* 964 | 965 | 966 | --------------------------------------------------------------------------------