| With the increasing popularity of portable terminals and the wide application of the Internet,the number of communication users and service traffic are increasing explosively.How to improve the spectrum efficiency and energy efficiency of the communication system to meet the needs of various services has become a serious challenge for wireless communication.Because the spatial degree of freedom can be used to improve the multiplexing gain and diversity gain of spectrum resources,the spectrum efficiency and system capacity will be significantly improved,and large-scale MIMO(Multiple-Input Multiple-Output)structure for signal transmission and reception has become an effective way to meet this challenge.In the communication system based on large-scale MIMO structure,due to the random characteristics of wireless channels,there are correlations among many antennas.At the same time,the use of these antennas for signal transceiver can not increase the system capacity.Therefore,under the premise of not affecting the capacity of large-scale MIMO communication system,how to reasonably select the transceiver antenna of the system can effectively reduce the hardware cost and power consumption of the system,which plays a very important role in the realization of green broadband wireless communication.So,this paper will start from the problem of antenna selection in largescale MIMO systems.The main tasks are as follows:(1)Through the singular value decomposition of the channel matrix of largescale MIMO communication system,the main path of signal transmission is obtained,and a low complexity antenna selection algorithm is proposed.The simulation results show that the antenna selection algorithm is better than the decreasing method and the norm method in different scale antenna systems,and slightly worse than the greedy algorithm.With the increase of the number of selected antennas,the complexity is stable and much lower than that of the decreasing method and greedy algorithm.(2)Accurate channel state information is needed for antenna selection.Kalman filter is used to estimate and predict the channel when only part of the channel state information is available.And an antenna selection algorithm based on Kalman filter will be proposed.The simulation results show that when the channel changes,the channel estimated by Kalman filter is closer to the actual channel;when the channel changes quickly,using the predicted channel instead of the original channel has better real-time performance.(3)Combining with the high performance of hybrid precoding and the low cost of antenna selection,a joint antenna selection precoding algorithm is proposed under the condition of maximizing spectral efficiency.In this algorithm,the antenna selection matrix is obtained by low complexity antenna selection algorithm,and then the subchannel corresponding to the selected antenna is used as a new channel to get hybrid precoding.Simulation results show that the performance of the proposed antenna selection joint hybrid precoding algorithm is better than that of the same antenna selection algorithm combined with SOMP hybrid precoding in the same antenna system.And the spectral efficiency of 85% of the corresponding hybrid precoding can be obtained by using 1/4 antennas in the same signal-to-noise ratio.(4)Building a simulation platform to verify the proposed algorithm,comparing the algorithm proposed in this paper with the related algorithms,then,analyzing the results,and discussing and explaining the special situation. |
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