2014/03/27 by Lei Deng, Deng, Lei, Wenjie Zhang +5
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Advanced Wireless Network Optimization #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT) #Networking and Internet Architecture (cs.NI) #cs.IT #cs.NI #math.IT
paper · pdf · doi:10.48550/arxiv.1403.6977
openalex publication_date 2014/03/27 · arxiv created 2016/05/07 · arxiv updated 2016/05/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Driven by green communications, energy efficiency (EE) has become a new important criterion for designing wireless communication systems. However, high EE often leads to low spectral efficiency (SE), which spurs the research on EE-SE tradeoff. In this paper, we focus on how to maximize the utility in physical layer for an uplink multi-user multiple-input multipleoutput (MU-MIMO) system, where we will not only consider EE-SE tradeoff in a unified way, but also ensure user fairness. We first formulate the utility maximization problem, but it turns out to be non-convex. By exploiting the structure of this problem, we find a convexization procedure to convert the original nonconvex problem into an equivalent convex problem, which has the same global optimum with the original problem. Following the convexization procedure, we present a centralized algorithm to solve the utility maximization problem, but it requires the global information of all users. Thus we propose a primal-dual distributed algorithm which does not need global information and just consumes a small amount of overhead. Furthermore, we have proved that the distributed algorithm can converge to the global optimum. Finally, the numerical results show that our approach can both capture user diversity for EE-SE tradeoff and ensure user fairness, and they also validate the effectiveness of our primal-dual distributed algorithm.