User Management in Cell-Free Massive MIMO Systems with Limited Fronthaul Capacity

Siminfar Samakoush Galougah, H. Masoumi, M. Emadi
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引用次数: 1

Abstract

In cell-free (CF) massive multiple-input multiple-output (mMIMO) architecture, large number of access points (APs) collaboratively serve much smaller number of users. Conventionally, it is assumed that each AP serves all users. In this work, however, to lessen the computational and hardware costs, instead of serving all users, each AP serves limited number of them. We propose an algorithm for assigning users to each AP. Besides, we assume each AP is connected to a central processing unit (CPU) via limited capacity fronthaul link. To efficiently address the fronthaul capacity constraints, three strategies for sending signals from APs to the CPU are employed; namely: compress-forward-estimate (CFE), estimate-compress-forward (ECF), and estimate-multiply compress-forward (EMCF). We drive the capacity of the aforementioned systems with user management constraint. It is shown that the proposed user management improves the performance of the ECF and EMCF from both sum spectral efficiency (SE) and per user SE aspects.
有限前传容量无小区大规模MIMO系统中的用户管理
在无蜂窝(CF)大规模多输入多输出(mMIMO)架构中,大量接入点(ap)协同为数量少得多的用户提供服务。通常,假设每个AP为所有用户提供服务。然而,在这项工作中,为了减少计算和硬件成本,每个AP不是为所有用户服务,而是为有限数量的用户服务。我们提出了一种为每个AP分配用户的算法。此外,我们假设每个AP通过有限容量的前传链路连接到中央处理器(CPU)。为了有效地解决前传容量的限制,采用了三种策略将ap的信号发送到CPU;即:压缩-前向估计(CFE)、估计-前向压缩(ECF)和估计-多重前向压缩(EMCF)。我们通过用户管理约束来驱动上述系统的容量。结果表明,所提出的用户管理从和频谱效率(SE)和每个用户SE方面提高了ECF和EMCF的性能。
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