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Rate Splitting Multiple Access for Multigroup Multicast Beamforming in Cache-Enabled C-RAN.

Authors :
Zhou, Jiasi
Sun, Yanjing
Chen, Ruirui
Tellambura, Chintha
Source :
IEEE Transactions on Vehicular Technology. Dec2021, Vol. 70 Issue 12, p12758-12770. 13p.
Publication Year :
2021

Abstract

This paper investigates rate splitting multiple access (RSMA) for multigroup multicast beamforming in a cache-enabled cloud radio access network (C $^2$ -RAN). To maximize the minimum weighted rate among all users and ensure the base station (BS) transmit power and backhaul capacity constraints, we jointly optimize the dynamic BS clustering, message splitting, and beamforming vectors. More specifically, users requesting the same content are collected to a multicast group and served by a cluster of BSs. Each BS has limited storage space and connects to the central processor (CP) via a backhaul link. However, the resulting optimization problem is discrete and nonconvex and has a non-smooth objective function. To alleviate these problems, we construct two surrogates to approximate the objective function locally. These surrogates are strictly lower bounds and concave. Also, we build an upper-bound convex surrogate function to handle the backhaul cost constraint and derive a minorization-maximization (MM)-based iterative algorithm. Besides, we adopt a quadratic transform method to recast the achievable rate and binary BS selection problems to a more tractable form to reduce time cost. We transform the resulting problem into a two-tier alternating optimization problem; the outer-tier problem is handled with closed-form expressions while the inner-tier one is solved by a convex framework. We thus develop a quadratic transform-based alternating (QTA) algorithm. Extensive simulation results confirm the superiority of our proposed transmit strategy and algorithms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189545
Volume :
70
Issue :
12
Database :
Academic Search Index
Journal :
IEEE Transactions on Vehicular Technology
Publication Type :
Academic Journal
Accession number :
154240446
Full Text :
https://doi.org/10.1109/TVT.2021.3120093