Improved Sparse Channel Estimation for Cooperative Communication Systems
نویسندگان
چکیده
Accurate channel state information (CSI) is necessary at receiver for coherent detection in amplify-and-forward (AF) cooperative communication systems. To estimate the channel, traditional methods, that is, least squares (LS) and least absolute shrinkage and selection operator (LASSO), are based on assumptions of either dense channel or global sparse channel. However, LS-based linear method neglects the inherent sparse structure information while LASSO-based sparse channel method cannot take full advantage of the prior information. Based on the partial sparse assumption of the cooperative channel model, we propose an improved channel estimation method with partial sparse constraint. At first, by using sparse decomposition theory, channel estimation is formulated as a compressive sensing problem. Secondly, the cooperative channel is reconstructed by LASSO with partial sparse constraint. Finally, numerical simulations are carried out to confirm the superiority of proposed methods over global sparse channel estimation methods.
منابع مشابه
Improved Channel Estimation for DVB-T2 Systems by Utilizing Side Information on OFDM Sparse Channel Estimation
The second generation of digital video broadcasting (DVB-T2) standard utilizes orthogonal frequency division multiplexing (OFDM) system to reduce and to compensate the channel effects by utilizing its estimation. Since wireless channels are inherently sparse, it is possible to utilize sparse representation (SR) methods to estimate the channel. In addition to sparsity feature of the channel, the...
متن کاملSparse Channel Estimation for Dual-Hop Amplify-and-Forward Cooperative Communiacion Systems
Cooperative transmission is one of key techniques which can improve system capacity and transmit range with limit power in the next-generation communication systems. However, accurate Channel State Information (CSI) is necessary at the destination for coherent detection. Consider a Dual-Hop Amplify-and-Forward (DHAF) Cooperative Communication System (CCS), traditional linear channel estimation ...
متن کاملAdaptive Sparse Channel Estimation Methods for Time-Variant MIMO Communication Systems
Channel estimation problem is one of key technical issues in time-variant multiple-input multiple-output (MIMO) communication systems. To estimate the MIMO channel, least mean square (LMS) algorithm was applied to adaptive channel estimation (ACE). Since the MIMO channel is often described by sparse channel model, such sparsity could be exploited and then estimation performance could be improve...
متن کاملCompressive Estimation of Cluster-sparse Channels
Cluster-sparse multipath channels, i.e., non-zero taps occurring in clusters, exist frequently in many communication systems, e.g., underwater acoustic (UWA), ultra-wide band (UWB), and multiple-antenna communication systems. Conventional sparse channel estimation methods often ignore the additional structure in the problem formulation. In this paper, we propose an improved compressive channel ...
متن کاملPreamble Design for Channel Estimation in OFDM/OQAM Cooperative Systems
Preamble design for LS channel estimation in OFDM/OQAM cooperative systems is investigated in this paper. A simple but important setup is considered, consisting of a pair of single-antenna terminals (source and destination) assisted in their communication by an AF relay and following a well-established two-phase transmission protocol. The so-called sparse preamble case (i.e., pilot tones surrou...
متن کامل