Research On The Pilot Decontamination Techniques In Massive MIMO Systems

Massive multiple input multiple output(MIMO)technology can increase system capacity,reduce communication delay,suppress selective fading effects,improve anti-interference ability,and enhance system robustness by using a large amount of space degree of freedom.In the massive MIMO system,when the base station performs uplink(UL)reception detection and downlink(DL)transmission precoding,it needs to obtain the instantaneous channel state information(CSI).However,in the communication applications,the complex radio wave propagation environment results in a short channel coherence time,which cannot provide the number of orthogonal pilots required for pilot-based channel estimation.Accordingly,it's unavoidable to reuse pilots among the users.Pilot contamination(PC)formed by reusing pilot will cause channel estimation error,and its effect is larger than Gaussian white noise.Hence,this thesis focuses on the pilot decontamination techniques in the massive MIMO systems by adhering to the concept of "suppression" of pilot contamination aimed at effectively control the "contamination source".To analyze the causes of pilot contamination for the multi-cell and cell-free(CF)massive MIMO systems,the pilot decontamination schemes are proposed from the perspective of pilot allocation.The specific research contents are as follows:(1)For multi-cell massive MIMO systems,the pilot decontamination algorithm is researched from the perspective of partial pilot multiplexing.First of all,based on the idea of soft pilot reuse proposed by reference [1] and the available orthogonal pilot resources of systems,a user grouping based pilot allocation algorithm is proposed.The algorithm joints large-scale fading coefficients and the space distance between users and base stations,specifically,users are divided into cell-edge users with heavy pilot contamination and cell-center users with less pilot contamination.Accordingly,the cell-edge users are applied for the orthogonal pilots,whereas the cell-center users are sorted in ascending order of polar angles,and pilot sequences are sequentially allocated to reduce the performance loss of the cell-center group users.In addition,in view of the sufficient pilot resource scenario,a large-scale fading based pilot allocation algorithm is introduced: the user grouping can be completed based on the large-scale fading coefficient,whose pilot allocation is consistent with the user grouping based pilot allocation algorithm.The simulation results show that the proposed algorithms can dynamically resize the size of edge users based on the space location information,and save the pilot resources within the tolerable range of interference to significantly boost the uplink sum achievable rate.(2)Aiming at cell-free massive MIMO systems,a pilot allocation algorithm based on K-means clustering is proposed.Firstly,in order to avoid the communication between users and "invalid" access points(APs),a "user-centered" virtual cell division method is adopted to implement user selection of APs based on the large-scale fading coefficient,forming the specific AP clusters which serve the specific users.Then,exploits multiple features to determine the K value and selects the initial centroid,clustering users.Finally,based on the users' clustering results,users in the internal cluster are assigned to orthogonal pilots,whereas users in the external cluster are reused pilots.The proposed algorithm avoids the mutual interference caused by pilot reusing among users from a space perspective,optimizes the channel estimation performance,and enhances the uplink and downlink throughput of the system.