Abstract
This paper aims to develop an efficient compressed sensing (CS) based channel estimation method for non-sample spaced sparse channels in orthogonal frequency division multiplexing (OFDM) systems, which can effectively balance the channel estimation performance, spectral efficiency and computational complexity. To realize this goal, a novel delay tracking and residual norm minimization (DTRNM) method is proposed. In this method, the idea of reference delay grids (RDG) inspired by the delay tracking (DT) method proposed in [1] is formulated, which is proven to be much more efficient than current algorithms in estimating non-sample spaced sparse channels. Both theoretical derivation and simulation results show the effectiveness of the proposed method.
Highlights
As a multicarrier modulation technique, orthogonal frequency division multiplexing (OFDM) technique has the ability to provide reliable high data rate transmission in different communication scenarios [1], [2]
Reference [1] proposes a novel adaptive delay tracking (DT) method, which achieves comparatively good channel estimation performance significantly reduces the computational complexity by decreasing the number of coherence matching computations between the bases of the measurement matrix and the residual vector
The reference delay grid (RDG) guided residual norm minimization (RNM) method is proposed in this paper to effectively fight against the nonuniform pilot arrangement and realize the near optimal delay searching of the lth channel tap, which will be discussed after the DT method
Summary
As a multicarrier modulation technique, orthogonal frequency division multiplexing (OFDM) technique has the ability to provide reliable high data rate transmission in different communication scenarios [1], [2]. H. Xie et al.: Efficient CS-Based Non-Sample Spaced Sparse Channel Estimation in OFDM System estimation performance, spectral efficiency and computational complexity efficiently. 2. The reference delay grid (RDG) guided residual norm minimization (RNM) method proposed in this paper is the main contribution of this work, which is new and clearly different from the current non-sample spaced sparse channel estimation methods [1], [10]. The newly proposed reference delay grid (RDG) guided residual norm minimization (RNM) method can effectively fight against the non-uniform pilot arrangement and promote the channel delay estimation precision, the proposed method has significantly better channel estimation performance than the methods proposed in [1] and [10] throughout the whole considered Eb/N0.
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