Queue-aware energy minimisation through sparse beamforming in C-RAN

This paper considers the queue-aware optimal energy minimisation sparse beamforming design (QESB) in a downlink cloud radio access network (C-RAN) system where multi-RRH communicates with multi-user through a central computing cloud via digital front-haul links. The problem is formulated as the joint optimisation problem of the transmission energy consumption, system queue length and front-haul cost with sparse beamforming design. As we know, the beamforming design adaptive to both QSI and CSI is challenging because of the high complexity. Apart from previous works that take queue length as constraints, in this paper we directly minimise the queue length state involved joint optimisation problem with SINR constraints. A smooth function is proposed to approximate the l 0 -norm function which is discrete and non-convex. To overcome the challenge due to the non-convexity of the optimisation problem, the semidefinite relaxation (SDR) technology is utilised to convert the primitive problem into the difference of convex (DC) programming problem, and convex and concave procedure (CCP) algorithm is used to induce the sparsity of the beamforming control. The simulation results show that the scheme proposed by this paper can obtain a good tradeoff between system energy consumption, queue length and front-haul cost with SINR constraints in C-RAN system.