Energy efficiency maximisation in downlink multi‐cell networks via coordinated resource allocation. Issue 1 (1st January 2015)

• Record Type: Journal Article
• Authors: Tong, Zhao; Li, Bingbing; Hui, Yongtao
• Is Part Of: IET communications. Volume 9:Issue 1(2015)
• Page Start: 42
• Page End: 54
• Publication Date: 2015-01-01
• Subjects: cellular radio -- energy conservation -- resource allocation -- array signal processing -- iterative methods; cellular networks -- beamforming vectors -- iterative algorithm -- beamforming vectors optimisation -- power allocation -- bit‐per‐joule capacity -- coordinated scheduling -- downlink multicell environment -- environmental conservation -- energy saving -- performance evaluation -- coordinated resource allocation -- downlink multicell networks -- energy efficiency maximisation; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2014.0097
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : There is a great interest in considering the energy efficiency (EE) as an important performance evaluation recently for its contribution to both energy saving and environmental conservation. In this study, the authors focus on the optimal energy‐efficient design for downlink multi‐cell environment with coordinated scheduling and beamforming. The EE is defined as bit‐per‐joule capacity to indicate how efficiently energy is consumed for transmitting information. They set up the optimum model for maximising the EE of coordinated cells subject to a total power constraint at each base station and study the resource allocation (RA) for it, including user selection, power allocation and beamforming vectors optimisation. They consider an equivalent non‐fractional form of the original problem and propose an iterative algorithm to optimise the spectrum RA and beamforming vectors alternatively. In each iteration, the beamforming vectors are updated by the iterative algorithm based on the first‐order optimality conditions, while the user scheduling policy is updated by the enhanced greedy algorithm. Performance studies show that the proposed algorithm has a rapid speed of convergence and achieves significant performance gain in EE for cellular networks.