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This paper studies normalized least mean square‐based adaptive sparse filtering algorithms for estimating multiple‐input multiple‐output (MIMO) channels. Although the MIMO channel is often modeled as sparse, traditional normalized least mean square‐based filtering algorithm never takes the advantage of the inherent sparse structure information and thus causes some performance loss. Unlike the traditional...
In this work, we investigate channel estimation problem in Multi-Input Multi-Output (MIMO) cooperative networks that employ the amplify-and-forward (AF) transmission scheme. Least square (LS) and expectation conditional maximization (ECM) have been proposed in the system. However, both of them never take advantage of channel sparsity and then they cause the estimation performance loss. Unlike the...
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