A New Decomposition Method for Multiuser DC-Programming and Its Applications

作者：Alvarado Alberth^*; Scutari Gesualdo; Pang Jong Shi

来源：IEEE Transactions on Signal Processing, 2014, 62(11): 2984-2998.

DOI：10.1109/TSP.2014.2315167

• Cooperative physical layer security
• cognitive radio
• difference convex program
• distributed algorithms
• successive convex approximation

We propose a novel decomposition framework for the distributed optimization of Difference Convex (DC)-type nonseparable sum-utility functions subject to coupling convex constraints. A major contribution of the paper is to develop for the first time a class of (inexact) best-response-like algorithms with provable convergence, where a suitably convexified version of the original DC program is iteratively solved. The main feature of the proposed successive convex approximation method is its decomposability structure across the users, which leads naturally to distributed algorithms in the primal and/or dual domain. The proposed framework is applicable to a variety of multiuser DC problems in different areas, ranging from signal processing, to communications and networking. As a case study, in the second part of the paper we focus on two examples, namely: i) a novel resource allocation problem in the emerging area of cooperative physical layer security and ii) and the renowned sum-rate maximization of MIMO Cognitive Radio networks. Our contribution in this context is to devise a class of easy-to-implement distributed algorithms with provable convergence to stationary solution of such problems. Numerical results show that the proposed distributed schemes reach performance close to (and sometimes better than) that of centralized methods.

• 出版日期2014-6