In this paper, an analytical framework for evaluating the performance of scalable cell-free massive MIMO (SCF-mMIMO) systems in which all user equipments (UEs) and access points (APs) employ finite resolution digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) and operates under correlated Rician fading, is presented. By using maximal-ratio combining (MRC) detection, generic expressions for the uplink (UL) spectral efficiency (SE) for both distributed and centralized schemes are derived. In order to further reduce the computational complexity (CC) of the original local partial MMSE (LP-MMSE) and partial MMSE (P-MMSE) detectors, two novel scalable low complexity MMSE detectors are proposed for distributed and centralized schemes respectively, which achieves very similar SE performance. Furthermore, for the distributed scheme a novel partial large-scale fading decoding (P-LSFD) weighting vector is introduced and its analytical SE performance is very similar to the performance of an equivalent unscalable LSFD vector. Finally, a scalable algorithm jointly consisting of AP cluster formation, pilot assignment, and power control is proposed, which outperforms the conventional random pilot assignment and user-group based pilot assignment policies and, contrary to an equal power transmit strategy, it guarantees quality of service (QoS) fairness for all accessing UEs.
翻译:本文介绍了一个分析框架,用于评价可伸缩的无细胞大规模MIMO(SCF-MMIMIM)系统(该系统中所有用户设备(UES)和接入点(APs)使用有限分辨率数字对分析转换器(DACs)和模拟对数字转换器(ADCs),在相连接的Rician退退退化下运行;通过使用最大-大鼠结合检测(MRC)检测,为分布式和集中式计划生成了可扩缩无细胞大缩缩放(UL)光谱效率(SE)通用表示(ULL-LSFD)通用表示;为了进一步降低当地部分MMSE(LP-MMSE)和部分MMSE(P-MMSS)使用有限分辨率数字转换器和模拟数字数字转换器(ADCs)的计算复杂性(ULP-MS-MMIMIM)系统(AD)和部分MMSE(P-ME)探测器(ADS-MES),分别为分布式和集中式计划提出两个新的可缩放散式和集中式MMEE;SFLFA、AF、AF、AF、A、AF、AF、AF、AF、A、AF、A、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、A、A、A、A、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、AF、A、A、A、A、A、AF、A、A、A、A、A、A、A、AF、A、A、A、A、A、A、AF、AF、AF、AF、AF、A、AF、AF、A、A、AF、A、A、AF、AF、A、A、AF、A、A、AF、A、AF、AF、A、A、AF、AF、A、AF、A、AF、