Binary-PSO-based energy-efficient small cell deployment in 5G ultra-dense network

The energy-efficient deployment of small cells helps to reduce environmental pollution in an ultra-dense network. In contrast, demand for massive connectivity and higher data rate are the promise of the present cellular system and small cell networks. Hence, energy consumption is reduced if base stations are optimally used. One way to improve the energy efficiency is by shutting down the redundant BSs while sustaining the Quality of Service for each user. This paper proposes an efficient cell modeling (ECM) algorithm for small cell formation, and binary particle swarm optimization-based small cell deployment (BPSD) to optimize the deployment of small base stations in the small cell network. The small base stations (s-BSs) exist in two modes: active and sleep which is decided by the proposed algorithm without compromising the network performance. The proposed ECM and BPSD algorithms are implemented and evaluated in MATLAB. The results demonstrate that the proposed approaches improve the energy efficiency and connectivity in the ultra-dense small cell network.