Although the status shows field but it can solve for the correct value and there is a slight drop in the output value when convergence is near, what are the reasons for these problems and how can they be solved?

[Mark_L_Stone]

As with @Erling , I’m not sure what you are talking about.

But I will make a guess that you are calling CVX in an iterative manner, such as SCA, and do not find the overall SCA algorithm to be performing as you would like. For instance, the optimal objective value (per SCA iteration) is not monotonically increasing (i.e., improving, given that you are performing maximization) . If so, see

The result obtained using the SeDuMi solver is inaccurate. The optimal solution is not as good as before the optimization.

Unsafeguarded (no line search or trust region)Successive Convex Approximation (SCA) or generally, alternating variables optimization are unreliable. It might not descend (for minimization problem), i.e., iterates could get worse. It might not converge to anything; and if it does converge, it might not be to a local optimum of the original problem, let alone a global optimum. The solution of successive iterations, and therefore subproblem inputs, can become wilder and wilder, until at some point …