MIMO user detection and channel estimation device and method

Abstract

The invention provides an MIMO user detection and channel estimation device and method. The MIMO user detection and channel estimation device comprises a pilot frequency sequence generation module, achannel estimation module and a user detection module. The pilot frequency sequence generation module generates a pilot frequency sequence of a user by using a single-layer complex fully-connected neural network; the pilot frequency sequence is distributed and the pilot frequency sequence is sent to a user served by the base station; a neural network model based on an AMP algorithm form is built in the channel estimation module; the channel estimation module takes a base station receiving signal and a known pilot frequency sequence as inputs and takes a channel matrix as an output, the outputend of the channel estimation module is connected with the user detection module, and the user detection module takes the channel matrix as an input and takes a user activity vector as an output to obtain a user detection result. According to the method, the neural network based on the AMP form is adopted for channel estimation, the MIMO user detection and channel estimation device and method havefewer parameters compared with a common neural network, are easier to train, have higher accuracy and convergence compared with the AMP and have the lower computation complexity.

Description

technical field [0001] The invention belongs to the field of channel estimation and user detection of wireless communication, and in particular relates to a MIMO user detection and channel estimation device and method. Background technique [0002] MIMO wireless communication technology refers to a wireless communication system with multiple input and multiple output. Massive MIMO is a key technology in 5G, especially playing an important role in large-scale machine-type communication scenarios. Massive MIMO can obtain higher channel capacity, spectrum efficiency, and energy efficiency by further increasing base station antennas. In a large-scale machine type communication scenario, a multi-antenna base station needs to support tens of thousands to millions of user equipment (UE) access. The characteristic of this scenario is that its users are often machines and devices such as sensors, which do not maintain access for a long time, but only access when specific events occu...

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Problems solved by technology

[0003] In order to solve this engineering demand, some methods have been tried, including the use of some classic compressed sensing algorithms, such as AMP (approximate message passing) and its derivative algorithms, and some simple neural networks, such as simple full connection Auto-encoder and other schemes, but there are some problems in these schemes: it is difficult to meet the requirements of low complexity and high accuracy at the sam

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