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Joint Power Control and Access Point Scheduling in Fronthaul-Constrained Uplink Cell-Free Massive MIMO Systems
IEEE Transactions on Communications ( IF 7.2 ) Pub Date : 2020-12-28 , DOI: 10.1109/tcomm.2020.3047801
Mamoun Guenach 1 , Ali A. Gorji 1 , Andre Bourdoux 1
Affiliation  

Cell-free (CF) massive Multiple-Input Multiple-Output (MIMO) with large number of distributed access points (APs) has emerged as a new paradigm allowing higher macro diversity for randomly distributed users. However, the fronthaul traffic bandwidth between central processing unit and the APs can explode in particular in the uplink, requiring expensive star-topology with point-to-point fronthaul links. To achieve a scalable CF massive MIMO architecture and a cost-effective fronthauling solution, we consider, in this paper, a point-to-multipoint fronthaul topology where (a subset of) the APs share a serial fronthaul link offering a per-user limited fronthaul bandwidth. We develop a novel unified optimization framework for iterative power control and AP scheduling that provides a systematic user-centric solution towards scalable uplink CF massive MIMO. Experimental results show that power control is not sufficient to guarantee the best objective and, therefore, the appropriate association of the users to the APs is required to improve the overall system signal-to-noise ratio. Under the stringent fronthaul bandwidth, the proposed joint optimization framework results in i) significant 5% outage data rate increase ii) near uniform distribution of the served users per APs and, hence, an increased diversity and iii) fast convergence of the algorithm within a few iterations.

中文翻译:

前传约束上行链路无蜂窝大规模MIMO系统中的联合功率控制和接入点调度

具有大量分布式接入点(AP)的无单元(CF)大规模多输入多输出(MIMO)已经成为一种新范例,可以为随机分布的用户提供更高的宏分集。但是,中央处理单元与AP之间的前传流量带宽可能会爆炸,尤其是在上行链路中,这需要具有点对点前传链路的昂贵的星形拓扑。为了实现可扩展的CF大规模MIMO架构和经济高效的前传解决方案,我们在本文中考虑了点对多点前传拓扑,其中AP(的一个子集)共享一个串行前传链路,从而为每个用户提供有限的前传带宽。我们为迭代功率控制和AP调度开发了一个新颖的统一优化框架,该框架为可扩展的上行链路CF大规模MIMO提供了一个以用户为中心的系统解决方案。实验结果表明,功率控制不足以保证最佳目标,因此,需要用户与AP进行适当的关联才能提高整个系统的信噪比。在严格的前传带宽下,所提出的联合优化框架导致:i)中断数据率显着提高5%; ii)每个AP的服务用户的分布接近均匀,因此,多样性增加; iii)在a范围内算法的快速收敛几次迭代。需要将用户与AP进行适当的关联,以提高整个系统的信噪比。在严格的前传带宽下,提出的联合优化框架导致i)显着提高5%的中断数据速率ii)每个AP的服务用户的分布接近均匀,因此增加了多样性,并且iii)算法在a内快速收敛。几次迭代。需要将用户与AP进行适当的关联,以提高整个系统的信噪比。在严格的前传带宽下,所提出的联合优化框架导致:i)中断数据率显着提高5%; ii)每个AP的服务用户的分布接近均匀,因此,多样性增加; iii)在a范围内算法的快速收敛几次迭代。
更新日期:2020-12-28
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