Spectral and energy efficiency maximization for content-centric C-RANs with edge caching

Tung Thanh Vu*, Duy Trong Ngo, Minh Ngoc Dao, Salman Durrani, Richard H. Middleton

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    27 Citations (Scopus)


    This paper aims to maximize the spectral and energy efficiencies of a content-centric cloud radio access network (C-RAN), where users requesting the same contents are grouped together. Data are transferred from a central baseband unit to multiple remote radio heads (RRHs) equipped with local caches. The RRHs then send the received data to each group's user. Both multicast and unicast schemes are considered for data transmission. We formulate mixed-integer nonlinear problems in which user association, RRH activation, data rate allocation, and signal precoding are jointly designed. These challenging problems are subject to minimum data rate requirements, limited fronthaul capacity, and maximum RRH transmit power. Employing successive convex quadratic programming, we propose iterative algorithms with guaranteed convergence to Fritz John solutions. Numerical results confirm that the proposed joint designs markedly improve the spectral and energy efficiencies of the considered content-centric C-RAN compared to benchmark schemes. Importantly, they show that unicasting outperforms multicasting in terms of spectral efficiency in both cache and cache-less scenarios. In terms of energy efficiency, multicasting is the best choice for the system without cache whereas unicasting is best for the system with cache. Finally, edge caching is shown to improve both spectral and energy efficiencies.

    Original languageEnglish
    Article number8443418
    Pages (from-to)6628-6642
    Number of pages15
    JournalIEEE Transactions on Communications
    Issue number12
    Publication statusPublished - Dec 2018


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