Convex Approximated Weighted Sum-Rate Maximization for Multicell Multiuser OFDM

TL;DR

This paper introduces two efficient convex approximation methods for maximizing weighted sum-rate in multicell multiuser OFDM systems, achieving faster convergence and near-optimal solutions under power constraints.

Contribution

The paper presents novel convex approximation algorithms for WSRMax in multicell OFDM systems, reducing computational complexity and improving convergence speed.

Findings

Proposed methods converge within few iterations.

Numerical results show superior performance over existing techniques.

Algorithms effectively optimize weighted sum-rate locally.

Abstract

This letter considers the weighted sum-rate maximization (WSRMax) problem in downlink multicell multiuser orthogonal frequency-division multiplexing system. The WSRMax problem under per base station transmit power constraint is known to be NP-hard, and the optimal solution is computationally very expensive. We propose two less-complex suboptimal convex approximated solutions which are based on sequential parametric convex approximation approach. We derive provably faster convergent iterative convex approximation techniques that locally optimize the weighted sum-rate function. Both the iterative solutions are found to converge to the local optimal solution within a few iterations compared to other well-known techniques. The numerical results demonstrate the effectiveness and superiority of the proposed approaches.