Transmit Power Optimisation in Wireless Network

Abstract

Transmit power optimisation in wireless networks based on beamforming have emerged as a promising technique to enhance the spectrum efficiency of present and future wireless communication systems. The aim of this study is to minimise the access point power consumption in cellular networks while maintaining a targeted quality of service (QoS) for the mobile terminals. In this study, the targeted quality of service is delivered to a mobile station by providing a desired level of Signal to Interference and Noise Ratio (SINR). Base-stations are coordinated across multiple cells in a multi-antenna beamforming system. This study focuses on a multi-cell multi-antenna downlink scenario where each mobile user is equipped with a single antenna, but where multiple mobile users may be active simultaneously in each cell and are separated via spatial multiplexing using beamforming. The design criteria is to minimize the total weighted transmitted power across the base-stations subject to SINR constraints at the mobile users. The main contribution of this study is to define an iterative algorithm that is capable of finding the joint optimal beamformers for all basestations, based on a correlation-based channel model, the full-correlation model. Among all correlated channel models, the correlated channel model used in this study is the most accurate, giving the best performance in terms of power consumption. The environment here in this study is chosen to be Non-Light of- Sight (NLOS) condition, where a signal from a wireless transmitter passes several obstructions before arriving at a wireless receiver. Moreover there are many scatterers local to the mobile, and multiple reflections can occur among them before energy arrives at the mobile. The proposed algorithm is based on uplink-downlink duality using the Lagrangian duality theory. Time-Division Duplex (TDD) is chosen as the platform for this study since it has been adopted to the latest technologies in Fourth Generation (4G) wireless communication systems. Monte Carlo simulation results and discussions are also provided to complement the analysis.