Research On Sparsity Based Time-Varying Channel Modeling And Estimation

Orthogonal Frequency Division Multiplexing(OFDM)has been widely used in many merging communication standards due to its robustness against frequency selective fading channels and high spectral efficiency.Accurate channel state information is crucial for the coherent detection in OFDM systems.Pilot-aided channel estimation methods have been studied to acquire channel parameters.The insertion of pilots inevitably leads to reduction of the spectral efficiency,and as the channel deteriorates,the pilot overhead required increases significantly.This paper focuses on the sparse feature of wireless time-varying channels.By fully exploiting the intrinsic characteristics of channel,sparsity channel model and corresponding estimation method aiming to obtain high estimation precision with high spectral efficiency have been studied.This paper studies two scenarios of slowly time varying channel and fast time varying channel.The main content of this paper can be summarized as follows:1.Aiming to the problem of high pilot overhead and poor performance of slowly time varying channel estimation,we propose a novel channel estimation scheme based on joint sparse auto-regressive model by taking advantage of the dynamic characteristic,sparsity and joint sparsity of channel.The proposed method performs the following two steps.Firstly,the channel delay structure is estimated by using the proposed sparsity adaptive simultaneous orthogonal matching pursuit(SASOMP)algorithm.Secondly,with the channel delay estimation,a Kalman filter is performed to obtain the channel amplitude.Simulation results indicate that the proposed method is capable of recovering the time-varying channel with much lower pilot overhead than conventional channel estimators and conventional compressed sensing based channel estimators with a superior estimation performance.2.A joint sparse basis expansion model is proposed to estimate the fast time varying channel.In the proposed channel model,joint sparsity is considered and the estimation of the channel impulse response is converted to the estimation of the basis expansion coefficient.The proposed method firstly uses the SOMP algorithm to acquire a rough estimation of channel and a subsequent piece-wise linear smoothing method is adopted to reduce the model error.Combined with the proposed channel estimation method,the OTFS transform and corresponding inverse transform are introduced into OFDM system as an anti-interference module,which leads to high reliability and provides an idea for the implementation of OTFS communication system.