论文标题

全双工无单元格MMIMO系统:分析和分散优化

Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization

论文作者

Datta, Soumyadeep, Amudala, Dheeraj Naidu, Sharma, Ekant, Budhiraja, Rohit, Panwar, Shivendra S.

论文摘要

通常,通常使用半双链节点和高容量的fronthaul链接研究了无细胞(CF)大规模多输入 - 多输出(MMIMO)部署。为了利用全双工(FD)通信的吞吐量和能源效率(EE)的可能提高,我们考虑使用具有实际有限容量的Fronthaul链接的FD CF MMIMO系统。我们通过最大比率组合/最大比率传输处理和最佳均匀量化来得出该系统的闭合光谱效率(SE)下限。然后,我们通过使用两层方法通过下行链路和上行链路功率控制来优化加权总和EE(WSEE):第一层将优化作为广义凸程序进行了配方,而{第二层}使用交替的乘数方法来求解优化。我们分析表明,提出的两层配方产生了原始WSEE优化的karush-kuhn-tucker点。我们从数值上显示了权重对用户单个EE的影响,这证明了WSEE指标的实用性以纳入用户的异质EE要求。我们表明,低领aul容量减少了每个AP可以支持的用户数量,因此,无单元的系统以用户为中心。

Cell-free (CF) massive multiple-input-multiple-output (mMIMO) deployments are usually investigated with half-duplex nodes and high-capacity fronthaul links. To leverage the possible gains in throughput and energy efficiency (EE) of full-duplex (FD) communications, we consider a FD CF mMIMO system with practical limited-capacity fronthaul links. We derive closed-form spectral efficiency (SE) lower bounds for this system with maximum-ratio combining/maximum-ratio transmission processing and optimal uniform quantization. We then optimize the weighted sum EE (WSEE) via downlink and uplink power control by using a two-layered approach: the first layer formulates the optimization as a generalized convex program, while the {second layer} solves the optimization decentrally using the alternating direction method of multipliers. We analytically show that the proposed two-layered formulation yields a Karush-Kuhn-Tucker point of the original WSEE optimization. We numerically show the influence of weights on the individual EE of the users, which demonstrates the utility of the WSEE metric to incorporate heterogeneous EE requirements of users. We show that low fronthaul capacity reduces the number of users each AP can support, and the cell-free system, consequently, becomes user-centric.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源