Sparse beamforming for real-time energy trading in CoMP-SWIPT networks

In this paper, we propose a coordinated base-station energy management (CoBEM) technique in which the BSs in a coordinated multipoint (CoMP) with rate-limited backhaul links collaborate to keep the demand and supply balanced using local renewable energies. We formulate two sparse beamforming techniques as ?0-norm optimisation problems and apply a method that can replace l0-norm with l1-norm and iteratively updated the weight factors to obtain a sufficient sparsity solution called reweighted l1-norm minimisation. For user-centric clustering technique, each user terminal selects a cluster of BSs, whereas, for BS-centric clustering technique, the BSs with a shortage of power budget are authorised to select an optimal number of user terminals based on their available energy budget. In both techniques, we investigate the optimal tradeoff between the BS-receiver cooperation links, the overall energy consumption by the BSs and the energy purchased by the retailer from the realtime market, whilst accounting for the quality-of-service (QoS) requirements for simultaneous wireless information and power transfer (SWIPT). Extensive simulation results confirm that the proposed sparse beamforming techniques significantly improve the infeasibility of a full cooperation in CoMP-SWIPT networks and reveal that the BS-centric clustering is more profitable than the user-centric clustering in real-time energy balancing.