Research On Channel Estimation And Green Energy Efficiency Of Massive MIMO

Under the impetus of the two trends,the Mobile Internet and the Internet of Things,the sharp increase of mobile data services,the increasingly scarce spectrum resources and the rapid growth of the energy consumption put forward higher requirements on the next generation mobile communication system,the 5G system.As a key technology of 5G,the massive MIMO system can significantly improve the spectrum efficiency and the power efficiency just by configuring the large-scale antenna array in the base station.This paper mainly focuses on the study of some main problems in the transmission technology of the massive MIMO system,and the detailed contents are as follows:First of all,the huge number of antenna in the base station of the massive MIMO leads to the considerable complexity of extracting instantaneous state information of the channel.In this paper,due to the sparse characteristics of wireless channel state information,a low complexity sparse channel estimation algorithm is proposed based on the traditional DFT channel estimation algorithm,which is suitable for the massive MIMO system.Simulation results show that the algorithm can get an optimal system performance which tends to be close to that of the MMSE channel estimation algorithm.Secondly,with the increase of the number of antenna,the system capacity is almost completely limited by the pilot reusing of adjacent cells,which is the most serious challenge for system designing in the massive MIMO system.Considering the pilot pollution characteristics in the multi-cell multi-user system,this paper analyses the most serious pilot pollution,which comes from the cell edge users sharing the same pilot.Further,an intelligent pilot allocation scheme based on the distance between the users and the base stations is proposed,taking advantage of the characteristics that the state information of different users is non-orthogonal.The theoretical analysis shows that the scheme can make the system downlink converge to the optimal signal noise interference ratio.Simulation results show that the proposed intelligent pilot allocation scheme effectively improves the performance of the downlink in the massive MIMO system.Finally,a large number of A/D converters are used to quantify the signal in the massive MIMO system and the quantization accuracy greatly affects the energy efficiency of the system.According to the relationship among the quantization accuracy of A/D converter in the uplink,the system energy consumption and the loss of information,a quantitative model of the massive MIMO system is established and the relationship expression among the quantitative bits of A/D converter and the number of antenna in base station together with the system spectrum efficiency and energy efficiency is deduced.Moreover,ensuring the maximum energy efficiency,the best selective group quantization scheme based on PSO algorithm is put forward.Simulation results show that the low precision quantity of the A/D converter can achieve the best energy efficiency and considering the large scale fading coefficients of adjacent cells changing,the use of the best value from PSO algorithm can ensure the remarkable robustness for the massive MIMO system.