2017/04/05 by Thuy M. Pham, Pham, Thuy M., Ronan Farrell +3
Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #FOS: Computer and information sciences #Information Theory (cs.IT) #Satellite Communication Systems
paper · pdf · doi:10.48550/arxiv.1704.01473
openalex publication_date 2017/04/05 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
This paper characterizes the capacity region of Gaussian MIMO broadcast\nchannels (BCs) with per-antenna power constraint (PAPC). While the capacity\nregion of MIMO BCs with a sum power constraint (SPC) was extensively studied,\nthat under PAPC has received less attention. A reason is that efficient\nsolutions for this problem are hard to find. The goal of this paper is to\ndevise an efficient algorithm for determining the capacity region of Gaussian\nMIMO BCs subject to PAPC, which is scalable to the problem size. To this end,\nwe first transform the weighted sum capacity maximization problem, which is\ninherently nonconvex with the input covariance matrices, into a convex\nformulation in the dual multiple access channel by minimax duality. Then we\nderive a computationally efficient algorithm combining the concept of\nalternating optimization and successive convex approximation. The proposed\nalgorithm achieves much lower complexity compared to an existing interiorpoint\nmethod. Moreover, numerical results demonstrate that the proposed algorithm\nconverges very fast under various scenarios.\n