I used dichotomy to approximate `f_n(k,s)`

, who should be in the range between `'F_max'`

and `'F_min'`

, i.e. between 100 and 0.01. But due to the process, the cvx variable `p`

went negative and did not satisfy one of my constraints `p(k)＞0`

, making the value of `f_n(k,s)`

worth to 10^5

Is there something wrong with my code? Why does it go negative when it’s clearly restricted to `p(k)＞0`

```
while F_max - F_min > convergence_factor %convergence_factor = 0.01;
F_next = (F_max +F_min) / 2;
cvx_begin quiet
variable p(K,1)
expression f_n(K,M)
expression f_n_part1(K,M)
for s = 1:M
for k = 1:K
f_n_part1(k,s)=0;
for i = 1:K
for m = 1:M
if i == k && m==s
f_n_part1(k,s) = f_n_part1(k,s) + 0;
else
f_n_part1(k,s) = f_n_part1(k,s) + p(i)*(abs(weight_n(:,k,s)'*dki(:,k,i,s,m)))^2;
end
end
end
f_n(k,s) = a_bar(k,s) - (p_n(k)*(abs(weight_n(:,k,s)'*b(:,k)))^2) * inv_pos(2 * real(sqrt(p_n(k))*(weight_n(:,k,s)'*b(:,k))'*(weight_n(:,k,s)'*b(:,k))*sqrt(p(k))) - p_n(k)*(abs(weight_n(:,k,s)'*b(:,k)))^2)...
- b_bar(k,s) * abs(weight_n(:,k,s)'*b(:,k))^2 * p(k)...
- c_bar(k,s) * f_n_part1(k,s);
end
end
f_last = 0;
maximize (0)
subject to
for k = 1:K
p(k) <= p_max;
end
for k = 1:K
p(k) >= 0;
end
for s = 1:M
for k = 1:K
f_n(k,s) >= F_next;
end
end
for s = 1:M
for k = 1:K
2 * sqrt(p_n(k))*real((weight_n(:,k,s)'*b(:,k))'*(weight_n(:,k,s)'*b(:,k)) )*sqrt(p(k)) - p_n(k)*(abs(weight_n(:,k,s)'*b(:,k)))^2>= 0;%**eq(6)
end
end
cvx_end
%%
if strfind(cvx_status,'Solved')
F_min = F_next;
p_final = p;
else
F_max = F_next;
end
end
```