Research On Massive MIMO Technology For 5G Wireless Communications

As the fast growing demand for high-rate and high-quality wireless communications, it is predicted that the network capacity needed in 2020 will be 1000 times than that of the current system. Therefore, the fifth generation mobile communications technology(5G), which can significantly imporve the system capacity and the spectral and energy efficiency, attracts considerable attentions, and the massive multi-input multi-output(MIMO) is one of the most important technologies in it. Based on the realistic scenario, this dissertation focuses on the more general channel model---Ricean fading channel. Compared with the traditional MIMO, the capacity improvements of massive MIMO systems are analyzed. Meanwhile, the Ricean power-scaling law and method to eliminate the pilot contamination are also presented, which are novel and useful for both theory and practice. Moreover, a low-complexity power allocation mechanism used in multicell scenario is proposed, and the effect of power allocation schemes in massive MIMO systems is analyzed under different conditions. The main contributions of this dissertation lie in:Firstly, the power-scaling law of massive MIMO systems under Ricean fading is investigated. In contrast to previous relevant work, the dissertation focuses on the more general Ricean fading channel with line-of-sight(LOS) component. In the single-cell multi-user MIMO(MU-MIMO) scenario, achievable uplink rates are analyzed, using maximal-ratio combining(MRC) and zero-forcing(ZF) receivers, assuming perfect and imperfect channel state information(CSI), respectively. The Ricean power-scaling law that the users' transmit power should satisfy is obtained, while maintaining a desirable quality of service. It is found that, in the case of perfect CSI, as the number of base station antennas( M) grows large, the transmit power of each user can be scaled down proportionally to 1 / M. If CSI is estimated with uncertainty, the same result holds true but only when the LOS component is included. Otherwise, if the channel experiences pure Rayleigh fading, the transmit power of each user can be only proportionally cut down to 1 /(?).Secondly, the system performance of multicell massive MIMO systems with Ricean fading is investigated, and the method to eliminate the pilot contamination is given. In the multicell MU-MIMO scenario, the effect of the LOS component on the uplink system performance is analyzed, assuming perfect and imperfect CSI, respectively. It is found that increasing the proportion of the LOS component can improve the uplink performance. Particularly, for the case of imperfect CSI, which suffers from the effect of pilot contamination, the uplink rate will approach a finite constant as M increases, whilst if the proportion of the LOS component is increased at the same time, the uplink rate can grow without bound. That is, all interference and noise vanish with both very large base station antennas and the proportion of the LOS component, and the pilot contamination effect is eliminated. The multi-cell Ricean power-scaling law is also obtained, which is proved to be consistent with the conclusion in single-cell scenario.Finally, the power allocation mechanism in multicell massive MIMO systems is investigated. A low-complexity scheduling mechanism for power allocation is proposed, where in a single time slot, only cells that do not interfere with each other adjust their transmit powers. Then, the joint optimization over the whole network is simplified to a single-cell optimization problem. Based on this, corresponding transmit power allocation schemes applied for both uplink and downlink are given. These schemes are shown to bring considerable gains over equal power allocation for practical antenna configurations(e.g., up to a few hundred). However, as the ratio of base station antennas( M) to the number of users( N) increases, these gains diminish, and as M/ N ??, equal power allocation becomes optimal. Moreover, applicable values of M/ N under an acceptable power allocation gain threshold are presented, which can be used as to determine when the proposed power allocation schemes yield appreciable gains, and when they do not. From the network point of view, the proposed scheduling approach can achieve almost the same performance as the joint power allocation after one scheduling round, with much reduced complexity.