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Energy Efficiency of Downlink Cell-Free Massive MIMO System with Full-Pilot Zero-Forcing

机译:具有全导频迫零的下行无蜂窝大规模MIMO系统的能效

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This paper investigates the downlink energy efficiency (EE) of cell-free massive multiple-input multiple-output (MIMO) system, where all the geographically distributed access points (APs) with large numbers of antennas coherently serve a number of independent users. In contrast to conventional zero-forcing (ZF) precoding scheme, this paper aims at suppressing the inter-cell interference by leveraging on the full-pilot ZF(fpZF) precoding strategy. In particular, the fpZF precoding can be implemented at the APs–in a distributed manner, there is no channel state information (CSI) exchange between the APs and the central processing unit (CPU). In this work, based on the obtained EE, a downlink EE maximization problem is explored under each user’s quality-of-service (QoS) requirement and each AP’s power constraint. Considering the proposed EE maximization problem is non-convex, a sub-optimal sequential convex approximation (SCA) algorithm is presented. Simulation results demonstrate that the proposed SCA algorithm can converge to a stable value after a few iterations and outperform the full power transmission counterpart.
机译:本文研究了无蜂窝大规模多输入多输出(MIMO)系统的下行链路能量效率(EE),在该系统中,所有具有大量天线的地理分布式接入点(AP)一致地为多个独立用户提供服务。与传统的零强制(ZF)预编码方案相比,本文旨在通过利用全导频ZF(fpZF)预编码策略来抑制小区间干扰。特别是,可以在AP上实现fpZF预编码-以分布式方式,在AP与中央处理单元(CPU)之间没有信道状态信息(CSI)交换。在这项工作中,基于获得的EE,在每个用户的服务质量(QoS)要求和每个AP的功率约束下探索下行链路EE最大化问题。考虑到所提出的EE最大化问题是非凸的,提出了次优的序列凸逼近(SCA)算法。仿真结果表明,提出的SCA算法经过几次迭代即可收敛到稳定值,并且性能优于全功率传输系统。

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