Transmit Antenna Selection, Power and Energy Efficient Algorithm for Massive MIMO Applications

Massive MIMO is a multi-user MIMO (multiple-input multiple output) technology that has the ability to provide uniformly better service to wireless terminals in high-mobility environs. The major concept behind this is to equip base stations with arrays of more antennas that are utilized to serve various terminals simultaneously. The term “massive” refers to the count of antennas and not the physical size. However, deployment of multiple antennas at each node obviously maximizes the hardware cost, system complexity, and transmitter power. Particularly, in MIMO systems, each antenna needs a specific radio frequency chain that rapidly increases the system complexity and is unpleasant since the antenna count increases. Therefore, it is disincentive to employ multiple antennas at all the nodes. As a solution to this, transmit antenna strategy (T AS) is evolved that minimizes system complexity, hardware cost and so on. Still, the problem rises in the selection criteria of transmit antenna. Recently, more research works have been focusing on this issue by offering advanced algorithms or models. Such a way that, this research work concentrates on optimal transmit antenna selection to solve the problems like system complexity, cost, etc. In this paper an improved optimization model is introduced for the optimal selection of antenna. The proposed algorithm is named as Modified Velocity vector-based GSA (MV -GSA), which is the enhanced version of Gravitational Search Algorithm (GSA) that defines the count of antenna. This work goes on with the determination of solving multi-objective problem that increases the capacity and relative Energy Efficiency (EE) as well. At last, this model proved as better performer compared over conventional models, like Artificial Bee Colony (ABC), Genetic Algorithm (GA), Firefly (FF) Particle Swarm Optimization (PSO), and conventional GSA, respectively.