A Method for Channel Estimation in Multi-user MIMO-ofdm System

Abstract

The invention relates to a multi-user MIMO-OFDM system channel estimation method. The method comprises the following steps of S1, acquiring a residual error of each user and indexes of first Sk maximum correlation values of a measured matrix; S2, finding a common index value of all the users and determining the common index value as a common sparse support set omega c, calculating initial channel matrix estimation and renewing the residual error of each user; S3, calculating correlation of the residual error and the measured matrix by each user again, and through combining an improved LMMSE algorithm, calculating a channel estimation value of each user; S4, determining whether a residual error value of each user is less than a preset value or the step S3 is performed for (Sk-Sc) times, wherein the Sc is a number of common sparse support sets; and if a condition is not reached, returning to the S3 and repeating the above steps till that an iteration termination condition is satisfied and an estimation value of an channel state information matrix is finally acquired. In the invention, a sparse characteristic of a wireless multipath channel is considered and relevance among the plurality of user channel matrixes is also considered so that a characteristic of the common sparse support sets is possessed.

Description

technical field [0001] The invention relates to a multi-user MIMO-OFDM wireless communication method, in particular to a multi-user MIMO-OFDM system channel estimation method based on compressed sensing theory and linear channel estimation algorithm. Background technique [0002] MIMO technology uses multiple antennas to achieve multiple transmissions and multiple receptions, which can make full use of space resources, and use spatial multiplexing gain to double the channel capacity without increasing spectrum resources and antenna transmission power. However, for the current wireless communication broadband communication, due to the frequency-selective fading of the channel in the frequency domain, the resulting inter-symbol interference (ISI) greatly affects the performance of the MIMO system. In order to eliminate inter-symbol interference, space-time balanced MIMO system scheme and Orthogonal Frequency Division Multiplexing (OFDM) modulation MIMO system technology can be...

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Problems solved by technology

[0005] At present, although many multi-user MIMO-OFDM system models consider the sparse characteristics of wireless multipath transmission channels, they do not consider the characteristics of the common sparse support set of the channel matrix of different users and the channel impulse response (CIR) of each user within a certain period of time. ) The problem that the sparse support set of the vector changes very slowly, that is, the time correlation of the channel

In addition, traditional pilot-based channel estimation algorithms such as Least Square (LS) algorithm and Minimum Mean Square Error (Minimum Mean Square Error, MMSE) algorithm have low estimation accuracy, but their structure is simple and the algorithm complexity is low. , so a new reconstruction algorithm is needed to achieve high channel estimation performance while greatly reducing pilot overhead and complexity, and improving system transmission efficiency

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