```
for i =1:10
cvx_begin quiet
cvx_solver mosek
variable Pi %optimization variables
variable Pj
variable mu_n nonnegative
dual variables nu rho eta phi
minimize -(Mn-mu_n.*(1+exp(-an.*(gnx(1,i).*(Pi+Pj)-bn)))) % optimizing Pi and Pj (optimal allocated power)
subject to
nu: (Pi*hix(1,1))-Omega_i*((Pj.*hix(1,1))+Ni) >= 0;
rho: Pi*hjx(1,1)-Omega_j*Nj >= 0;
eta: (Pi*hjx(1,1))-Omega_t*((Pj*hjx(1,1))+Nj) >= 0; % Rth = R1 + R2
phi: Gamma_m-qmx(1,i).*(Pi+Pj) >= 0;
cvx_end
nu = nu+0.1*i; % all dual variables are iteratively increased by step size 0.1
rho = rho+0.1*i;
eta = eta+0.1*i;
phi = phi+0.1*i;
end
```

# If dual variables are non negative, Is there need to initialized?

**neelu_gupta**(Neelu Gupta) #1

**neelu_gupta**(Neelu Gupta) #3

okay, Thankyou

one more problem with my objective function of “real affine.* log convex”, how to resolved it

If i am using rel_entr, It is not working because it is working for affine and concave.

**Mark_L_Stone**(Mark L. Stone) #5

Leaving side the `-Mn`

term, which is a constant, the minimum possible objective value appears to be zero, and that is achieved with `mu_n = 0`

and any feasible `Pi`

and `P`

j. Therefore, because `mu_n`

does not appear in any constraints other than being nonnegative, It looks like `mu_n`

= 0 is optimal, together with any value of `Pi`

and `Pj`

which satisfy the constraints

Am I missing something?

Log of sigmoid function

**neelu_gupta**(Neelu Gupta) #6

You are right sir about taking non-negative parameter value as zero or minimum,