Energy Efficiency Maximization for Full Duplex MIMO Cloud Radio Access Networks

T. Ha, Xuan-Xinh Nguyen, Hoang Kha Ha
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引用次数: 1

Abstract

This paper studies a joint precoder and fronthaul compression design for full-duplex (FD) miltiple-input-multiple-output (MIMO) cloud radio access networks (CRANs). A cloud control unit (CU) communicates with multiple downlink and uplink users through FD radio units (RUs) connected to the CU through fronthaul links which are limited capacity. We address the energy efficiency (EE) maximization problem subject to the transmit power constraints at each RU, each user and the limited capacity of fronthaul links. Since the formulated design problem is a highly non-convex problem in design variables, we exploit a successive convex approximation (SCA) method to obtain the concave lower bound of the achievable sum rate and a convex upper bound of limited capacity fronthaul link functions. Then, we apply the Dinkelbach method to develop an efficient iterative algorithm guaranteeing convergence in which the convex optimization problems are solved. Numerical results are provided to investigate the EE of the proposed algorithm.
全双工MIMO云无线接入网络的能源效率最大化
研究了全双工(FD)多输入多输出(MIMO)云无线接入网(CRANs)的联合预编码器和前传压缩设计。一个云控制单元(CU)通过FD无线电单元(ru)与多个下行和上行用户通信,这些无线电单元通过容量有限的前传链路连接到CU上。我们解决了在每个RU、每个用户和前传链路有限容量的发射功率约束下的能源效率(EE)最大化问题。由于公式化设计问题是包含设计变量的高度非凸问题,我们利用连续凸逼近(SCA)方法得到了可实现和速率的凹下界和有限容量前传链路函数的凸上界。然后,我们应用Dinkelbach方法开发了一种保证收敛的高效迭代算法,该算法求解凸优化问题。数值结果验证了该算法的EE。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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