Basis Expansion Channel Model Research Articles

Reduced rank MIMO-OFDM channel estimation for high speed railway communication using 4D GDPS sequences

Abstract This paper presents a reduced rank channel estimator for multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) high speed railway (HSR) systems. Conventional interpolation based channel estimators require high pilot load for robust estimation of the rapidly time varying frequency-selective MIMO-OFDM HSR channel. To relax the high pilot overhead requirement, we take advantage of the channel’s restriction to low dimensional subspaces due to the time, frequency and spatial correlation and propose a low complexity linear minimum mean square error (LMMSE) channel estimator. The channel estimator utilizes a four-dimensional (4D) basis expansion channel model obtained from band-limited generalized discrete prolate spheroidal (GDPS) sequences. Simulation results validate that the mean square estimation error of the proposed estimator is smaller than that of the conventional interpolation based least square (LS) estimator and the performance is robust to different delay, Doppler and angular spreads.

Compressed sensing based channel estimation for fast fading OFDM systems

A compressed sensing (CS) based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel. A compressive basis expansion channel model with sparsity in both time and frequency domains is given. The pilots in accordance with a novel random pilot matrix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel. The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate significantly below the Nyquist rate. The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm. The proposed algorithm can effectively improve the channel estimation performance when the number of pilot symbols is reduced with improvement of throughput efficiency.

Doubly selective fading channel estimation in MIMO OFDM systems

High data transmission rates and high mobility give rise to time- and frequency-selectivity in wireless communication channels. This paper investigated time and frequency doubly selective channel estimation using pilot tones among Multi-Input Multi-Output (MIMO) orthogonal frequency division multiplexing (OFDM). Firstly, a complex exponential basis expansion channel model (BECM) was introduced to represent doubly selective channel during an OFDM symbol period; then, based on BECM, an effective MIMO-OFDM doubly selective channel estimation method was presented; finally, the optimality in designing pilot tones parameters was done according to the minimization of channel estimation MSE, mainly including the number, the placement and the structure of pilot tones. Simulation results show that the proposed estimation method has good performance in doubly selective channel scenarios and confirms the theoretical analysis findings.

Optimal training for block transmissions over doubly selective wireless fading channels

High data rates give rise to frequency-selective propagation, whereas carrier frequency-offsets and mobility-induced Doppler shifts introduce time-selectivity in wireless links. To mitigate the resulting time- and frequency-selective (or doubly selective) channels, optimal training sequences have been designed only for special cases: pilot symbol assisted modulation (PSAM) for time-selective channels and pilot tone-assisted orthogonal frequency division multiplexing (OFDM) for frequency-selective channels. Relying on a basis expansion channel model, we design low-complexity optimal PSAM for block transmissions over doubly selective channels. The optimality in designing our PSAM parameters consists of maximizing a tight lower bound on the average channel capacity that is shown to be equivalent to the minimization of the minimum mean-square channel estimation error. Numerical results corroborate our theoretical designs.