Fast Convergence Solution for Weighted Sum-Rate Maximization in Downlink Multicell MISO
We consider the problem of weighted sum-rate maximization (WSRM) under base station transmit power constraints in multicell downlink multiple-input single-output systems. The WSRM problem is known to be NP-hard, therefore, numerically finding the global optimal solution is very difficult. We propose a computationally efficient and fast convergent solution, based on sequential parametric convex approximation approach, which solves locally the nonconvex WSRM problem. In particular, we obtain a second-order cone program formulation of the convex approximated WSRM prob- lem and iteratively solve it by judiciously updating the variables involved in the optimization process. The proposed method exhibits faster convergence to the local optimal solution within a few iterations compared to the other well-known iterative WSRM methods. The efficiency of our proposed convex approximated WSRM method is demonstrated by numerical simulations.
This algorithm is useful for future wireless communication systems.
|Mirza Golam Kibria||通信情報システム専攻||ディジタル通信||博士2回生|