Transfer Performance Analysis And Power Allocation Design For Massive MIMO

During the past decades, multiple input multiple output (MIMO) has been intensively investigated from theory to practice. Recently, a landmark extension of MIMO, namely massive MIMO or large-scale MIMO, was proposed to meet the ever growing demand on wireless data services. By exploiting an extraordinarily large number of antennas, massive MIMO shows great potential on achieving radiated energy and spectrum efficiency, jamming robustness, latency reduction and enhancing wireless energy transfer. It is well acknowl-edged as a core evolutionary technology for next generation cellular communications. This thesis focuses on the performance analysis and power allocation of massive MIMO.Firstly, the thesis introduces the research background and the research progress of massive MIMO. A comprehensive survey on massive MIMO is conducted, summarizing the state of art in the fields of channel state estimation, downlink precoding and uplink detection of massive MIMO. Moreover, the thesis also points out that various technologies can be integrated into massive MIMO, such as dual-polarized antennas and wireless energy transfer. Furthermore, the basic theoretical framework of massive MIMO is presented as the foundation of this thesis, including the pros and cons, the channel issues and a basic system model of massive MIMO.Additionally, the downlink system performance is analyzed under pilot contamination. Pilot contami-nation has become a main constraint for massive MIMO. This thesis considers a multi-cell massive MIMO scenario where the number of users per cell is proportional to that of base station antennas. Both performance with and without pilot contamination are analyzed in a quantitative way with closed-form expressions. Unlike some existing works, this thesis derive the result by coping with the fast fading explicitly, which makes the re-sults far more accurate in comparison with the classic paper, especially for moderate to large antenna number. From the derived results, it is found that the interference still exists when both base station antenna number and user number per cell tend to infinity with a fixed non-zero ratio, and pilot contamination leads to a direc-tional interference in the downlink, which will not vanish no matter how the user number changes. Moreover, pilot contamination has larger impact on the performance in a system where base station is equipped with a larger antenna number.Furthermore, the thesis investigates dual-polarized massive MIMO in aspects of performance analy-sis and user scheduling scheme. Generally, a dual-polarized system benefits from easy deployment with much less antenna space. It enjoys the reduction in pilot contamination and multiuser interference due to cross-polarization fading, while the signal power is also reduced compared to the monopole antenna system, and the overall effect to the system performance is still unrevealed. This thesis considers downlink perfor-mance of a multi-cell network with base stations equipped with large dual-polarized antenna arrays under pilot contamination. This thesis derives closed-form expressions of network performance in terms of user signal-to-interference-and-noise ratio both under the case of perfect channel state information and in the p-resence of pilot contamination. The derived results, however, reveal that the performance of a dual-polarized system can be optimized by properly setting receive antenna polarizations, and fortunately the optimal per-formance behaves identically to that of a monopole massive MIMO. The receive antenna polarizations should be optimized by randomly selected polarization directions with equal probabilities.Finally, this thesis also studies the power allocation in wireless powered communication network massive MIMO. This thesis considers the downlink wireless energy transfer as the sole source of power to support uplink data transmission in a multiuser massive MIMO. This thesis derives the user achievable rate, and finds that the classic water-filling power allocation no longer applies to this non-orthogonal multiple access and effective power allocation is still unrevealed. The asymptotically optimal closed-form downlink power allocation strategy is derived to maximize the uplink sum rate using matched filter based beamforming, which is significantly different with classic water-filling scheme. Moreover, it is interesting to find that the obtained power allocation for uplink sum rate maximization simultaneously maximizes the minimum user rate under the asymptotic massive MIMO scenario, which maintains fairness while chasing for optimal system performance. The simulation results confirm that the proposed scheme outperforms water-filling and equal gain power allocation.