Research On Key Technologies For Low Complexity Massive MIMO Systems

With the in-depth development of China's social information and the wide applica-tion of smart terminals,the demand for high performance of mobile communications is increasing.The next generation mobile communication system,5G,has emerged to cope with the problems caused by the high traffic from wireless and mobile devices,massive device connectivity and low-latency services.As one of the core technologies of 5G,massive MIMO technology has attracted extensive attention from academia and industry.Compared with the traditional MIMO,massive MIMO technology can greatly improve spectral efficiency without increasing bandwidth and the transmit power of antennas by simply deploying hundreds of antennas at the base station.With the number of anten-nas increasing,thermal noise and interference between different users in the same cell can be further eliminated.However,massive MIMO technology also faces many chal-lenges.The most prominent of the challenges are the complexity,economic costs and power consumption of hardware.That is because in the practical massive MIMO sys-tems,each antenna of the base station needs to be equipped with a corresponding radio frequency link,and each radio frequency link has a quantizer with high sampling rate and high resolution.This will greatly increase the complexity,cost and power consumption of the hardware,which will also constrain the deployment and final commercialization of massive MIMO systems.Therefore,it is very important and necessary to study on low-complexity and low-cost large-scale MIMO systems.In the above background,this thesis focuses on the key technologies of low-complexity massive MIMO,aiming to provide correct theoretical basis and technical support for the later 5G network.The main contributions of this paper are summarized as follows:1)Research on the channel capacity of massive MIMO systems.Firstly,according to the configuration of large but finite number of antennas at the base station in practical communication environments,the closed-form expressions of the ergodic channel capac-ity for different Taylor expansion orders are derived by using mathematical tools such as matrix Taylor expansion and high-order statistics.Then comparing with the channel ca-pacity which is obtained in the case of infinite antennas at base station,we can conclude that with the orders of Taylor expansion increases,the derived channel capacity becomes closer to the one in practical environment.Finally,the correctness and accuracy of the derived closed-form expression can be verified by the numerical results.Moreover,we can use the derived channel capacity expression to analyze the performance in practical environment,thereby reducing the complexity of the performance analysis.2)Research on the low-resolution massive MIMO systems.Firstly,for narrowband massive MIMO systems,the closed-form expressions for the uplink achievable rate for MMSE receiver with perfect and imperfect channel state information are derived,respec-tively.Moreover,based on the derived expressions,we can conclude that the one-bit and two-bit massive MIMO systems can achieve the same spectral efficiency as the conven-tional massive MIMO systems by deploying 1.5 times and 1.1 times more antennas at the base station respectively.Furthermore,it can be seen that the complexity and power consumption of hardware can be reduced by employing low-resolution ADCs in massive MIMO systems.3)Research on mixed-ADC massive MIMO systems.Firstly,for narrowband mas-sive MIMO systems and massive MIMO-OFDM systems,the closed-form expressions for uplink achievable rate with MRC and ZF receiver are derived in case of the sys-tem with perfect and imperfect channel state information.Then by comparing with low resolution large-scale MIMO systems and conventional large-scale MIMO system,the energy efficiency and spectrum efficiency of the systems are analyzed based on the de-rived closed-form expressions.Finally,numerical results verify the correctness of the derived results and show the advantages of mixed-resolution massive MIMO systems in the trade-off between energy efficiency and spectrum efficiency.Moreover,we can con-clude that the best trade-off can be obtained when the quantization resolution of ADC is 3 or 4 bits.4)Research on antenna selection technology in low-resolution massive MIMO sys-tems.Firstly,for the downlink massive MIMO systems,by employing the greedy al-gorithm and QR decomposition,an antenna selection algorithm base on the criterion of maximum SNR is proposed.Then by analyzing the difference of antenna selection technology between the low-resolution massive MIMO systems and traditional massive MIMO systems,we propose two antenna selection algorithms under the consideration of quantization error and the channel gains.After modifying the steps of algorithms,two improved ones are proposed according to different selected antenna numbers.Finally,numerical results and complexity comparison verify that the effectiveness of proposed algorithms.Moreover,it shows that the antenna selection technology can effectively re-duce the number of radio frequency links in large-scale MIMO systems,and it can also be combined with low-resolution technology to further reduce system complexity,economic costs and power consumption.