Interference Alleviation For Massive MIMO Systems Under Imperfect Conditions

Massive MIMO is one of the key technologies in the next generation communication system.By deploying large scale antenna arrays at the base station side,so that the base station antenna number is much larger than the user number,Massive MIMO can alleviate inter-cell interference without the cooperation between base stations and significantly improve the spectrum/energy efficiency.In realistic deployments,the performance of Massive MIMO systems is greatly restricted by imperfect conditions.These imperfect conditions includes: 1)The imperfect Channel Station Information(CSI)in the time-division duplex systems;2)The channel correlation between users in realistic environments;3)The constraints of the hardware components.This paper analyzes the performances of the Massive MIMO systems under the above imperfect conditions and proposes solutions to alleviate their impacts.This paper composes four research thrust: Research thrust one proposes an Unified CSIT error for TDD systems,with the integration of effects of the estimation delay,the noise and the pilot interference;Research thrust two derives the achievable rates of Massive MIMO systems under the unified imperfect CSI model and proposes modular prcecoding based on zero forcing to reduce the base band computation time;Research thrust three combines Massive MIMO with high altitude platform communications and analyzes the system capacity;Research thrust four proposes user equipment beamforming to alleviate the inter-cell interference in Massive MIMO systems.The contributions of this paper are summarized as follows:1.CSI Error Analysis in mulit-cell MIMO systemsUnified CSI error models are proposed for TDD systems,with the integration of effects of the estimation delay,the noise and the pilot interference.For pilot interference,the modeling approach of stochastic geometry is adopted,which breaks the constraint of the fixed cross gain assumption in previous works.Both the pilot synchronized and un-synchronized cases are analyzed.The impact of shadowing is also studied.Based on the unified error model,the conditions when one imperfect factor dominates the overall CSI error are derived.Simulation results verify that higher accuracy can be achieved by the proposed modeling method.The proposed CSI error model is adopted by the research works in the rest part of the paper.2.Achievable rates analysis of Massive MIMO under the unified CSI error modelThis thesis utilizes the unified imperfect CSI error model during the achievable rate analysis of the Massive MIMO systems.The three imperfect CSI factors,which impact the system performance greatly in realistic networks with finite base station antennas,have not been considered simultaneously in the downlink analysis of the achievable rate of a specific precoding scheme in Massive MIMO.Considering the three imperfect factors,this thesis derives the closed form analytical achievable rates of three precoding schemes for both the single-cell scenario and the multi-cell scenario.The three precoding schemes are: Zero Forcing,Maximum Ratio Combining and Modular precoding based on Zero Forcing.Modular precoding based on Zero Forcing is proposed by this thesis to reduce the baseband processing time of Massive MIMO base stations.By using analytical results proposed in this paper,the network operator can determine the proper precoding scheme according to environmental and system parameters.3.Capacity analysis of Massive MIMO on High Altitude platformsWith Massive MIMO installed on High Altitude Platforms(HAPs),capacity analysis is conducted for both sparse users and hotspot users.Sparse users are assumed to follow the Poisson Point Process and their capacities are obtained via the random geometry theorem.For hotspot users,Massive MIMO combined with HAP-based communication is shown to be able to achieve the multiplexing gain thus increase the hotspot capacity.The channel correlation model of UPA under LOS propagations is obtained for users within the hotspot.An upper bound of the correlation function is further derived to show that the correlation between hotspot users can be sufficiently low,resulting in hotspot capacity improvement.The hotspot capacity is affected by location distributions of the scheduled users.Four user location distribution models are considered,which leads to the capacity upper bound,the practical schemes to implement and the capacity estimation method respectively.The impact of perturbations of the HAP to the system performance is also analyzed,the ratio of hotspot user SINR under perturbated HAP and static HAP is given,which shows the robustness of Massive MIMO on HAP with respect to perturbations of the HAP.4.User Equipment Beamforming Optimization for Multi-Cell Massive MIMO SystemsUser Equipment(UE)beamforming method is proposed for massive MIMO systems with multiple antenna UEs.the inter-cell interference is alleviated by the UE beamforming performed in both the uplink pilot transmission and the downlink data reception.For each UE,the beamforming vector is obtained by maximizing its Signal to Pilot contamination Ratio(SPR).The SPR maximization is fully decoupled among UEs,only the local statistical channel information is needed,which brings two benefits: one is that no additional channel information exchanges are required;the other is the low computational cost,since the beamforming vector does not need to be updated instantly.The SPR maximization is transferred into a Semi-Definite Programming problem first and then a convex problem by the method of Semi-Definite Relaxation.Simulations under both the terrestrial Massive MIMO system and the HAP Massive MIMO system demonstrate the performance improvement of the proposed method.