2017/09/22 by Jihong Park, Park, Jihong, Dong Min Kim +6
Engineering · #Advanced MIMO Systems Optimization #FOS: Computer and information sciences #Full-Duplex Wireless Communications #Information Theory (cs.IT) #Millimeter-Wave Propagation and Modeling
paper · pdf · doi:10.48550/arxiv.1709.07963
openalex publication_date 2017/09/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Cloud RAN (C-RAN) is a promising enabler for distributed massive MIMO\nsystems, yet is vulnerable to its fronthaul congestion. To cope with the\nlimited fronthaul capacity, this paper proposes a hybrid analog-digital\nprecoding design that adaptively adjusts fronthaul compression levels and the\nnumber of active radio-frequency (RF) chains out of the entire RF chains in a\ndownlink distributed massive MIMO system based on C-RAN architecture. Following\nthis structure, we propose an analog beamformer design in pursuit of maximizing\nmulti-user sum average data rate (sum-rate). Each element of the analog\nbeamformer is constructed based on a weighted sum of spatial channel covariance\nmatrices, while the size of the analog beamformer, i.e. the number of active RF\nchains, is optimized so as to maximize the large-scale approximated sum-rate.\nWith these analog beamformer and RF chain activation, a regularized zero-\nforcing (RZF) digital beamformer is jointly optimized based on the\ninstantaneous effective channel information observed through the given analog\nbeamformer. The effectiveness of the proposed hybrid precoding algorithm is\nvalidated by simulation, and its design criterion is clarified by analysis.\n