Content-Centric Sparse Multicast Beamforming for Cache-Enabled Cloud RAN

• Published in: IEEE transactions on wireless communications Vol. 15; no. 9; pp. 6118 - 6131
• Main Authors: Tao, Meixia, Chen, Erkai, Zhou, Hao, Yu, Wei
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Array signal processing; caching; Cloud radio access network (Cloud RAN); content-centric wireless networks; Mobile communication; Multicast communication; multicasting; Nonlinear programming; Programming; Quality of service; Radio access networks; sparse beamforming; Wireless communication
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2016.2578922

This paper presents a content-centric transmission design in a cloud radio access network by incorporating multicasting and caching. Users requesting the same content form a multicast group and are served by a same cluster of base stations (BSs) cooperatively. Each BS has a local cache, and it acquires the requested contents either from its local cache or from the central processor via backhaul links. We investigate the dynamic content-centric BS clustering and multicast beamforming with respect to both channel condition and caching status. We first formulate a mixed-integer nonlinear programming problem of minimizing the weighted sum of backhaul cost and transmit power under the quality-of-service constraint for each multicast group. Theoretical analysis reveals that all the BSs caching a requested content can be included in the BS cluster of this content, regardless of the channel conditions. Then, we reformulate an equivalent sparse multicast beamforming (SBF) problem. By adopting smoothed ℓ 0 -norm approximation and other techniques, the SBF problem is transformed into the difference of convex programs and effectively solved using the convex-concave procedure algorithms. Simulation results demonstrate significant advantage of the proposed content-centric transmission. The effects of heuristic caching strategies are also evaluated.