Asymmetric Millimeter-wave Massive MIMO Research On Channel Estimation And Precoding Method

Due to the diversification of future applications,intelligent connectivity,and deep information processing,a large amount of data and high-speed information transmission will be generated.The optimal choice for such systems is a millimeter-wave all-digital multi-beam system.However,the complexity,cost,and power consumption of such a system are high,making it difficult to implement in future systems.Therefore,an asymmetric millimeter-wave massive Multiple Input Multiple Output(MIMO)system is proposed,which can not only retain the advantages of digital multi-beam systems,but also keep its complexity,cost,and power consumption within an acceptable range.Due to the asymmetric design of the base station’s transmit and receive antenna arrays,the reciprocity of the uplink and downlink channels no longer holds completely during the coherent time,and the channel only satisfies partial reciprocity.This paper mainly studies channel estimation and precoding for asymmetric millimeter-wave massive MIMO systems.Firstly,the partial reciprocity of the uplink and downlink channels in the asymmetric millimeter-wave system was studied.The angle information of the channel was found to satisfy partial reciprocity under different antenna array sizes through channel measurement.However,due to different array sizes,the spatial degrees of freedom were different,and the uplink channel could not identify all propagation paths of the downlink channel.Since the scattering objects around the base station are limited,the paths contributed by each scattering object have a certain angle extension,making the channel appear clustered in the 2D beam domain.Therefore,a clustered separable compressed sensing matching pursuit algorithm is proposed.Simulation results show that the performance of the proposed algorithm is better than that of the separable compressed sensing matching pursuit algorithm and its iteration times are less than half.In downlink channel estimation,based on the angle information already estimated from the uplink channel,a threshold-based layered search algorithm is proposed.Since the number of effective propagation paths is not known in advance during channel estimation,the threshold is used to stop the iteration.In each search process,the threshold is used to judge whether there are paths in the angle range,thereby reducing the search complexity.Simulation results show that the complexity of the proposed algorithm is lower than that of the traditional layered search algorithm,and the more angle information obtained from the uplink channel estimation,the less overhead is needed for the downlink channel estimation and the better the performance.In traditional millimeter-wave massive MIMO systems,hybrid beamforming is adopted from the perspective of complexity,power consumption,cost,and performance.The base station and users use hybrid precoding algorithms.However,in the asymmetric millimeter-wave system,the base station uses an all-digital multi-beam structure,requiring new precoding algorithms.This paper proposes a hybrid precoding algorithm based on maximum frequency efficiency,which decouples the analog and digital precoding.In the design of analog precoding,frequency efficiency is maximized in each iteration to construct the analog precoding,and then singular value decomposition is used to construct digital precoding to reduce complexity.Simulation results show that the proposed algorithm is better than the hybrid precoding algorithm based on the array response vector,and when the number of effective propagation paths is greater than a certain threshold,the complexity of the proposed algorithm is also lower than that of the hybrid precoding algorithm based on the array response vector.