Distributed Coordinated Multicell Beamforming for Wireless Cellular Networks Powered by Renewables: A Stochastic ADMM Approach

The integration of renewable energy sources (RES) has facilitated efficient and sustainable resource allocation for wireless communication systems. In this paper, a novel framework is introduced to develop coordinated multicell beamforming (CMBF) design for wireless cellular networks powered by a smart microgrid, where the BSs are equipped with RES harvesting devices and can perform two-way (i.e., buying/selling) energy trading with the main grid. To this end, new models are put forth to account for the stochastic RES harvesting, two-way energy trading, and conditional value-at-risk (CVaR) based energy transaction cost. Capitalizing on these models, we propose a distributed CMBF solution to minimize the grid-wide transaction cost subject to user quality-of-service (QoS) constraints. Specifically, relying on state-of-the-art optimization tools, we show that the relevant task can be formulated as a convex problem that is well suited for development of a distributed solver. To cope with stochastic availability of the RES, the stochastic alternating direction method of multipliers (ADMM) is then leveraged to develop a novel distributed CMBF scheme. It is established that the proposed scheme is guaranteed to This work was supported by the National Natural Science Foundation of China Grants No. 61671154, No. 61501123, and the Innovation Program of Shanghai Municipal Education Commission. Part of the work was presented at ICCS 2016 [1]. S. Hu, C. Xu, and X. Wang are with the Shanghai Institute for Advanced Communication and Data Science, Key Laboratory for Information Science of Electromagnetic Waves (MoE), Department of Communication Science and Engineering, Fudan University, Shanghai, China (emails: {syhu14, chbinxu, xwang11}@fudan.edu.cn). Y. Huang is with the School of Information Engineering, Guangdong University of Technology, Guangzhou, China (email: [email protected]). S. Zhang is with the Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China (email: [email protected]). October 18, 2017 DRAFT