The Research On Pilot Contamination And Energy Efficiency In Massive MIMO Multi-Cell TDD Systems

With the rapid increasing of 5G cellular networks, large-scale MIMO systems are extensively studied for the large capacity and high energy efficiency(EE). Large-scale antenna arrays at base stations afford huge increase in capacity. However, the inter-cell interference arising from pilot reusing, that is pilot contamination, is more and more serious and finally limits the system performance. One solution to this problem is to use effective pilot scheduling schemes. As a crucial criterion for 5G constructing, EE is a necessary factor to consider and its performance closely impacts the practical systems.The topic in this thesis comes from the National Natural Science Foundation undertaken by my supervisor. The thesis firstly studies the communication scheme in the large-scale MIMO multi-cell time division duplexing(TDD) system, and then analyzes the problem of pilot contamination which originates from non-orthogonal pilot sequences in the uplink training. A method of pilot scheduling based on maximum achievable sum rate can relieve this problem. The simulation results demonstrate the harmful effect of pilot contamination and the improvement due to pilot scheduling.The thesis analyzes EE in the single-cell multi-user MIMO system initially. The circuit power consumption model is elaborated at first. It describes how the antenna number and user number influence the circuit power consumption in detail. Then closed-form expression of EE, which depicts the relationship between the influence factors and downlink EE is obtained. The factors include the number of users, the transmit power and the antenna number. Finally the joint optimization algorithm of the factors is given. The simulation shows that optimal EE is acquired with medium numbers of antennas and users.To further understand the problems of pilot contamination and energy efficiency, the thesis considers to maximize EE before handling pilot contamination in the massive MIMO multi-cell TDD system. The models of EE under three linear precoding methods are analyzed and the closed-form expressions are concluded, respectively. Then in the EE-maximized system, a scheduling way based on maximum worst-case signal interference and noise ratio(SINR) is proposed and it largely enhances the bit error rate(BER) performance. The cells in the network are supposed to be symmetric. Using this property along with simulated annealing algorithm, the scheduling scheme is simplified. The simulation shows that EE-maximal antenna number grows with the number of users. Compared with the scheduling system that do not take EE into consideration, the system in which maximal EE is studied before scheduling greatly reduces the computation at the cost of reasonable decrease in system performance.