Antenna selection method for large-scale MIMO system

Abstract

The invention discloses an antenna selection method of a large-scale MIMO system, belonging to the technical field of wireless communication. The method comprises the following steps: (1) initializingtwo empty antenna selection subsets S, T; (2) calculating the norm of each column in the large-scale MIMO channel matrix H, placing the column with the largest norm in the antenna selection subset Sas the reference antenna for the next antenna selection, and deleting the column and the column with the smallest norm from the matrix H to update the matrix; (3) traversing the remaining antennas ofthe matrix H, placing the column with the least correlation in the antenna selection subset S as a new reference antenna, and simultaneously deleting the column and the column with the greatest correlation from the matrix H to update the matrix; (4) selecting a specified number of antenna array sets; (5) computing the capacity and energy efficiency of large-scale MIMO system. The invention reducesthe deployment of the radio frequency link, reduces the hardware cost and the realization complexity, and improves the system capacity and the energy efficiency without increasing the computational complexity through the bidirectional cross iteration selection of the channel matrix of the large-scale MIMO system.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to an antenna selection method for a massive MIMO system. Background technique [0002] The MIMO (Multi-Input Multi-Output) system configures multiple antennas at the transmitting end and the receiving end to obtain diversity gain and multiplexing gain, so that the system can double the channel capacity and transmission reliability without increasing the bandwidth. Massive MIMO technology deploys tens, hundreds, or even thousands of transmitting antennas at the base station to fully exploit the degree of spatial freedom and serve more users on the same time-frequency resource, without increasing the system bandwidth and transmitting power. It is one of the core technologies of the fifth generation mobile communication system to significantly improve the system capacity and energy efficiency of the wireless communication system, and has been deeply studied ...

AI Technical Summary

Problems solved by technology

Among them, the exhaustive search algorithm is the optimal algorithm, which can achieve the optimal system capacity, but the number of calculations is extremely large and the complexity is high, which is not suitable for the massive MIMO system with large-scale antenna arrays; the incremental antenna selection algorithm starts from the empty set , the antenna that contributes the most to the system capacity is selected each time; the decreasing antenna selection algorithm starts from the complete set, and the antenna that contributes the least to the system capacity is deleted each time; the principle of the decreasing algorithm and the increasing algorithm are the same, and the complexity is greatly reduced compared with the exhaustive search algorithm , is a suboptimal algorithm for antenna selection; the maximum norm method is to select L columns from the channel matrix H with the largest Frobenius norm column to form a selected subset, and the complexity is low; the random selection method is to randomly select from the channel matrix H L antennas, simple to implement, but little contribution to the improvement of system capacity

The above classical algorithms cannot be fully applied to massive MIMO systems, so the antenna selection of massive MIMO systems has become a new research hotspot

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