Efficient 5G Small Cell Planning With eMBMS for Optimal Demand Response in Smart Grids

Abstract

Smart Grids (SGs) are emerging cyber-physical systems, equipped with sophisticated communication and information technologies, for efficient and large-scale power supply and management. SGs demand advanced communication technologies between energy providers and consumers, for enabling a control-feedback loop, by using time-dependent pricing. In this paper, we propose an efficient planning of 5G small cells, with evolved multimedia broadcast and multicast communication, between aggregators (small cells) and SG consumers, for efficient demand-response (DR) programs. After pointing out that optimal multicast scheduling and radio resource management problem is NP-complete, we propose two different solutions, based on dynamic programming (DP) and greedy heuristics, for minimizing the energy cost for DR customers. We also analyze the performance of SG user capacity for 5G single cell multicast and multicast broadcast single frequency network. Extensive OPNET simulation results, over actual energy data and real wireless trace, demonstrate that our proposed 5G small cell planning and multicast solutions are capable of reducing energy production cost by $30\%$ , with up to $35\%$ shift in peak energy load, low latency and packet drop.