We propose a smooth approximation l(0)-norm constrained affine projection algorithm (SL0-APA) to improve the convergence speed and the steady-state error of affine projection algorithm (APA) for sparse channel estimation. The proposed algorithm ensures improved performance in terms of the convergence speed and the steady-state error via the combination of a smooth approximation l(0)-norm (SL0) ...

In this letter, the sparse recovery algorithm orthogonal matching pursuit (OMP) and subspace pursuit (SP) are applied for MIMO OFDM channel estimation. A new algorithm named SOMP is proposed, which combines the advantage of OMP and SP. Simulation results based on 3GPP spatial channel model (SCM) demonstrate that SOMP performs better than OMP and SP in terms of normalized mean square error (NMSE...

The channel estimation algorithm based on sparse Bayesian learning proposed in recent years shows better performance than the traditional by effectively reducing convergence error process. However, expectation maximization (EM-SBL) is difficult to meet practical applications with low complexity and power consumption. In order guarantee long-term stable communication of underwater devices, this ...

In this paper, we study channel estimation at a uniform linear array (ULA) with N antennas, where the ULA is composed of xmlns:xlink="http://www.w3.org/1999/xlink">L paths different angles arrival (AoAs). It assumed that Discrete-Time Fourier Transform (DTFT) beams (also known as xmlns:xlin...

in this paper, a novel time-varying channel estimation approach based on Kalman filter compressive sensing is proposed for the high sampling problem of ultra wideband (UWB) system considering the sparse of the channel impulse response. The direct sequence UWB signal is formulated to the mathematical model of compressed sensing after down sampling. The receiver recovery the channel impulse respo...

The problem of wideband massive MIMO channel estimation is considered. Targeting for low complexity algorithms as well as small training overhead, a compressive sensing (CS) approach is pursued. Unfortunately, due to the Kroneckertype sensing (measurement) matrix corresponding to this setup, application of standard CS algorithms and analysis methodology does not apply. By recognizing that the c...

The problem of estimating a sparse channel, i.e. a channel with a few non-zero taps, appears in various areas of communications. Recently, we have developed an algorithm based on iterative alternating minimization which iteratively detects the location and the value of the taps. This algorithms involves an approximate Maximum A Posteriori (MAP) probability scheme for detection of the location o...