Research On The Performance Of Massive Mimo Systems Based On Low-Resolution ADC Receivers

To meet the rapid and continuing growth of mobile traffic, the 5th generation (5G) mobile communication system requires the ability to provide 1000-fold capacity increase and high data rate of up to several thousand megabit per second. With scare radio resources, massive multiple input multiple output (MIMO) has become a crucial technology of 5G, since it can fully exploit spatial resources and allow for significant improvement in spectral and energy efficiency. While massive MIMO improves the system performance dramatically, it also faces entirely new problems:the challenge of mass data processing, expensive hardware cost and high total power consumption. A promising approach to solve these problems is to reduce the resolution of analog-to-digital converter (ADC) in receivers, which make the low cost, low power consumption and low complexity deployment of massive MIMO systems possible. In this thesis, we will investigate how low precision quantization affects the system performance and channel estimation in the massive MIMO systems with low resolution receivers.First, research on achievable rate and energy efficiency in the massive MIMO systems with low resolu-tion quantization is carried out based on the ideal channel state information (CSI). According to the investi-gation and research, an additive quantization noise model is to analyze the effects of quantization is chosen. Then we derive an approximate expression for the uplink achievable rate of quantized massive MIMO sys-tems, using maximum ratio combining receivers, assuming ideal CSI at receivers. Based upon the analytical result, we study the relationship among achievable rate, quantization bit and transmit power to understand the difference between finite resolution quantization and perfect quantization. Furthermore, we adopt a sim-ple energy consumption model to investigate the relationship between energy efficiency and quantization bit. Simulation results show that the application of low resolution ADCs in massive MIMO can enhance the efficiency tremendously while guaranteeing the little loss of achievable rate.Subsequently, we study the channel estimation and optimize the duration and transmit power of pilot symbols in quantized massive MIMO systems. Focusing on a quantized massive MIMO systems in time division duplex mode, in which both the minimum mean-square error channel estimator and MRC receivers are used, the users'ergodic rates are defined. After a proper approximation, an explicit achievable sum rate formula is derived. Utilizing it, we analyze some special scenarios and propose three different schemes to allocate resources in terms of time and power to uplink training. Numerical results demonstrate that the quantization of ADC will bring about great influence on channel estimation and pilot optimization. Especially in the case of extremely low precision quantization, increasing the length of pilot sequences can get more accurate channel estimate and higher achievable rate, compared with assigning more transmit power to pilot symbols.Finally, we investigate the achievable rate and energy efficiency in the massive MIMO systems with mixed resolution ADC receivers. Under the assumption of ideal CSI and MRC receiving at base station, a closed-form expression of achievable rate is presented. Then, we develop an energy consumption model for all the key component in receivers to study the energy efficiency. Simulation results show that, the mixed-ADC architecture with a relatively small number of high-resolution ADCs is able to achieve a large fraction of the achievable rate without output quantization while getting higher energy efficiency, which is a promising receiver paradigm for low cost massive MIMO systems.