Semi-blind channel estimation method and system

Abstract

The present invention belongs to the wireless communication system technology field, and especially relates to a semi-blind channel estimation method and system. The method comprises: the step a: in a first time block, employing the sparse signal reconstruction algorithm to establish a sparse channel reconstruction model based on training pilot signals, and estimating the channel information of the first time block through the sparse channel reconstruction model; the step b: in the tth time block, employing a maximum likelihood detector to detect the transmission signals of the tth time block based on the channel information of the tth time block, wherein 2<=t<=T, and T is the total number of the time blocks; and the step c: based on the transmission signals of the tth time block, employing the semi-blind channel estimation to establish a semi-blind sparse channel reconstruction model, and establishing the channel information of the tth time block through the semi-blind sparse channel reconstruction model. The semi-blind channel estimation method and system can highly and tightly approach to the parameter sparsity in a continuous domain angle space domain so as to greatly improve the system frequency spectrum efficiency.

Description

technical field [0001] The invention belongs to the technical field of wireless communication systems, and in particular relates to a semi-blind channel estimation method and system. Background technique [0002] The millimeter-wave large-scale multi-antenna system is expected to achieve a data transmission rate of gigabits per second compared with the traditional multi-antenna system. In order to obtain higher communication system throughput, it is a very critical step for the transceiver to acquire channel information. In fact, the channel part is the medium through which information must be effectively transmitted. Accurate and real-time channel information is the key to realizing beamforming, multi-user scheduling, rate allocation, self-adaptation, channel equalization, signal detection and decoding in millimeter wave communication systems. basic basis for operation. However, in a large-scale multi-antenna system, due to the increase in the number of transceiver antenn...

AI Technical Summary

Problems solved by technology

However, due to the difference in matrix representation between the transmit and receive antenna array response in the mmWave channel model and the single-antenna array response matrix in the existing methods, the existing channel estimation method based on the minimization of one-dimensional atomic norm cannot be directly extended to a dual-antenna array with both transmit and receive antennas. Response mmWave channel information estimation

[0006] At the same time, the channel estimation methods mentioned above are all limited to the pilot-based channel estimation mechanism, which generates a large amount of pilot training load and seriously reduces the spectral efficiency of the system.

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