Energy Efficiency Maximization for C-RANs: Discrete Monotonic Optimization, Penalty, and ℓ0-Approximation Methods
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|Title:||Energy Efficiency Maximization for C-RANs: Discrete Monotonic Optimization, Penalty, and ℓ0-Approximation Methods||Authors:||Nguyen, Kien-Giang
|Permanent link:||http://hdl.handle.net/10197/10540||Date:||25-Jun-2018||Online since:||2019-05-20T12:48:21Z||Abstract:||We study downlink of multiantenna cloud radio access networks with finite-capacity fronthaul links. The aim is to propose joint designs of beamforming and remote radio head (RRH)-user association, subject to constraints on users' quality-of-service, limited capacity of fronthaul links and transmit power, to maximize the system energy efficiency. To cope with the limited-capacity fronthaul we consider the problem of RRH-user association to select a subset of users that can be served by each RRH. Moreover, different to the conventional power consumption models, we take into account the dependence of the baseband signal processing power on the data rate, as well as the dynamics of the efficiency of power amplifiers. The considered problem leads to a mixed binary integer program which is difficult to solve. Our first contribution is to derive a globally optimal solution for the considered problem by customizing a discrete branch-reduce-and-bound approach. Since the global optimization method requires a high computational effort, we further propose two suboptimal solutions able to achieve the near optimal performance but with much reduced complexity. To this end, we transform the design problem into continuous (but inherently nonconvex) programs by two approaches: penalty and l 0 -approximation methods. These resulting continuous nonconvex problems are then solved by the successive convex approximation framework. Numerical results are provided to evaluate the effectiveness of the proposed approaches.||Funding Details:||Science Foundation Ireland||Type of material:||Journal Article||Publisher:||IEEE||Journal:||IEEE Transactions on Signal Processing||Volume:||66||Issue:||17||Start page:||4435||End page:||4449||Copyright (published version):||2018 IEEE||Keywords:||Energy efficiency; Cloud radio access network; Limited fronthaul capacity; Rate-dependent signal processing power; Nonlinear power amplifier; Beamforming; Mixed binary integer program; Discrete branch-reduce-and-bound; Successive convex approximation||DOI:||10.1109/tsp.2018.2849746||Language:||en||Status of Item:||Peer reviewed||Conference Details:||Also presented at: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018), Alberta, Canada, April 15-20 2018|
|Appears in Collections:||Electrical and Electronic Engineering Research Collection|
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