Active user detection and channel estimation method with adaptive overhead

Abstract

The invention discloses an active user detection and channel estimation method with adaptive overhead. Using the estimated active user set and the channel thereof, the estimation quality is evaluatedby calculating the received signal error, and the time slot overhead of the pilot frequency in the frame structure can be adaptively adjusted according to the number of active users and the channel environment in the real system, so that the service quality is ensured with the access time delay as low as possible, and super-reliable active user detection and channel estimation are realized. The method also aims at an enhanced mobile broadband scene, large-scale machine type communication and other huge-address communication scenes in a cellular network in the future. According to the method, the pilot signal for broadband uplink unlicensed multiple access is reasonably designed by utilizing the sporadic characteristic of the uplink transmission flow of the user and the sparsity of a large-scale MIMO virtual angle domain channel, and an advanced compressed sensing technology is introduced, so that the access delay of the user can be greatly reduced.

Description

technical field [0001] The present invention relates to the field of active users and channel estimation in wireless communication, and in particular to active user detection and channel estimation under the scene of uplink multiple access of massive users in giant address communication supporting enhanced mobile broadband. Background technique [0002] With the rapid development of video streaming, social networking, and emerging Internet of Things technologies, the number of user equipment and service traffic will increase explosively in future cellular networks. Huge connections with huge business traffic. The current design of the cellular network is mainly aimed at mobile phone users, and the number of users that can be supported is limited. Reliable support for giant-dimensional uplink multiple access is very challenging for the current network. [0003] Traditional authorization-based random multiple access protocols require additional control signaling and resource ...

AI Technical Summary

Problems solved by technology

Professor W. Yu from the University of Toronto in Canada proposed an active user detection and channel estimation algorithm based on the AMP algorithm to further reduce the computational complexity in large-scale random multiple access, and analyzed the multi-antenna system in the giant However, this scheme needs to use the specific channel distribution and noise power as prior information, which still has obstacles in the application of actual communication systems.

[0006] In addition, all the above-mentioned large-scale random multiple access schemes consider the narrow-band giant-site communication of single-carrier transmission, and it is still a very challenging problem to reliably support large-scale random multiple access in the eMBB (Enhanced Mobile Broadband, Enhanced Mobile Broadband) scenario. question

Moreover, for the actual system, the number of active users and the channel environment are constantly changing, resulting in a time-varying sparsity of the uplink channel matrix. If the sparsity is relatively small, reliable active users can be obtained with a relatively small pilot slot overhead. collection and its channels; on the contrary, when the sparsity is relatively large, a large overhead is required

All the above-mentioned schemes use a fixed-length pilot overhead, which will undoubtedly lead to waste or shortage of pilots, so a more flexible way is needed to reasonably control the pilot overhead

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