Path division multiple access method based on large-scale MIMO-OTFS

Abstract

The invention belongs to the technical field of wireless communication, and discloses a path division multiple access method based on a large-scale MIMO-OTFS. The path division multiple access methodcomprises the steps of: acquiring a large-scale MIMO-OTFS angle-delay-Doppler domain received signal model and angle-delay-Doppler domain uplink primary and secondary 3D channel models through OTFS modulation; designing a user angle domain grouping and path scheduling algorithm by utilizing the dispersion characteristic of a large-scale MIMO-OTFS channel in an-angle-delay-Doppler domain, and reasonably allocating angle domain resources at a user side; receiving pilot frequencies and effective data of different users at scheduled receiving grid point positions, using a least square estimator for estimating channels thereof, and carrying out data recovery through adopting a maximum ratio combination method; and guiding a downlink access process by using a user grouping and path scheduling algorithm in uplink transmission. By adopting the path division multiple access method , interference among multiple users can be reduced, large-scale access of the users is realized, and the spectrum utilization rate is effectively improved.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a large-scale MIMO-OTFS-based path division multiple access method. Background technique [0002] Present: Massive MIMO is a promising technology for next-generation communication networks. Significant gains in energy and capacity efficiency can be achieved by using a large number of antennas on the base station. With accurate channel state information, the achievable rate of the system can be analyzed, network interference can be quantified, resource allocation can be optimized, and the energy efficiency of the system can be derived. Furthermore, the signal processing elements of massive MIMO, such as beamforming, precoding, user scheduling, and data detection, can be optimized. However, as the user moves at higher speeds, the channel changes over time. Acquiring time-varying channels with limited channel coherence time will be more challenging. ...

AI Technical Summary

Problems solved by technology

Although BEM-based schemes can characterize the massive MIMO channel dynamics within a given block, the parameters of BEM are sensitive to user mobility conditions

In addition, both models have model approximation errors, especially at high speeds, where the errors become non-negligible

[0007] (2) When accessing a large number of users in a massive MIMO-OTFS system, since the channels of different users have different dispersion characteristics, the problem of inter-user interference management is more complicated; if the allocation delay-Doppler The resource blocks in the domain will cause a serious waste of spectrum resources

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