Power Optimization of Massive MIMO in Heterogeneous Network for 5G System

Abstract

In future wireless networks, there is an increasing demand of high quality of service, high data rates, network coverage and low latency. However, the existing network is limited in capacity to address the requirements of the data rate in the order of gigabits. Massive MIMO and small cells are the foremost technologies to address such challenges for the next generation (5G) wireless systems. Massive MIMO is a technique that deploying a large number of antennas at the base station, and thus, improving energy efficiency and spectral efficiency of wireless networks. Small cell provides high data rate and good coverage with reduced transmit power by reducing the distance between base station and user. Since, the number of users are increasing, which give a rise to a lot of problems like increased interference, complexity and power consumption in the processing and transmission. This can be analyzed to enhance the data rate and EE by combining massive MIMO base station and small cell base stations with higher spatial reuse. To provide resource aware energy saving technique with a low complexity algorithm based on classical regularized zero force (RZF) beamforming is used and compared with optimal solution cases. The simulation result is conducted to prove that, the total power consumption can be greatly improved more than 1.2 % by combining massive MIMO and small cells, this is possible with both optimal beamforming and low-complexity beamforming. Based on the result obtained, it is better to use the heterogeneous system of massive MIMO macro cell with low power complementary small cells can achieve a greater EE (EE) than massive MIMO macro cell alone.