When I finished writing the code and running it, I found that cvx had no results, and his status is Infeasible, i dont know why, can you help me?

CVX Warning:

Models involving “log” or other functions in the log, exp, and entropy

family are solved using an experimental successive approximation method.

This method is slower and less reliable than the method CVX employs for

other models. Please see the section of the user’s guide entitled

The successive approximation method

for more details about the approach, and for instructions on how to

suppress this warning message in the future.

## Successive approximation method to be employed.

For improved efficiency, SDPT3 is solving the dual problem.

SDPT3 will be called several times to refine the solution.

Original size: 91 variables, 24 equality constraints

4 exponentials add 32 variables, 20 equality constraints

## Cones | Errors |

Mov/Act | Centering Exp cone Poly cone | Status

--------±--------------------------------±--------

0/ 0 | 0.000e+00 0.000e+00 0.000e+00 | Unbounded

Status: Infeasible

Optimal value (cvx_optval): +Inf

here is my source code

clear all;

clc;

%%

B = 20 ; %

L = 150; %

p = 100 ; %

sigma = sqrt(10*10^-14)*10^3; %

b = 5 ; % xita n =5

d = 1 ; %yita n =1

derta = 2 ; %derta n =2

N = 2; %

Kn = 2; %

F = 100;%F 100GHz

D = 1 ;%D 1000Megacycles=1GHz

fl = 0.7 ; %fl=0.7GHz

lamda = 100;

e = zeros(N,Kn); %

e_ele = log2(1+p/sigma); %

e = e+e_ele;

fai = b*B*e_ele - derta*B - d*B*e_ele;

%%

%

rou = 0.4;

a = zeros(2,2,100);

c = zeros(2,2,100);

sigma = zeros(2,2,100); %

omega = zeros(2,2,100);

sigma(:,:,1) =[0.3 0.5; -0.3 -0.5] ;

omega(:,:,1) =[0.5 0.7; -0.5 -0.7] ;

a(:,:,1)=[1 0 ;0 0]; %

c(:,:,1)=[1 0 ;0 0];

for t=1:1

cvx_begin

% Step1

variable a_copy(2,2,100) nonnegative %

variable s(2,2,100) nonnegative %s

variable c_copy(2,2,100) nonnegative %

s(:,:,1)==[1 0 ;0 0];

y=0;

for j=1:2

for i=1:2

y=y-log(1+s(i,j,1)*fai+c_copy(i,j,1) lamdaF/D)+sigma(i,j,t)a_copy(i,j,1)+rou/2(a_copy(i,j,1)-a(i,j,t))^2+omega(i,j,t)c(i,j,1)+rou/2(c_copy(i,j,1)-c(i,j,t))^2;*F/D - a_copy*fl/D >=0;

end

end

%

minimize(y);

subject to

%%

sum(s,1) <= min(1,L/(B * e_ele) ) ;

%%

sum( c_copy( ) <= 1;

%%

c_copy

%%

0 <= a_copy <= 1

0 <= s <= 1

0 <= c_copy <= 1

%%

a_copy >= s ;

a_copy >= c_copy ;

cvx_end

end