OFDM pilot allocation for sparse channel estimation

TL;DR

This paper proposes a deterministic pilot allocation method for OFDM systems using compressed sensing, optimizing pilot placement to improve sparse channel estimation with minimal overhead.

Contribution

It introduces a novel pilot allocation strategy based on minimizing DFT matrix coherence, including non-uniform patterns and a greedy search for non-difference set cases.

Findings

Non-uniform pilot patterns based on cyclic difference sets are optimal.

Greedy search can find effective suboptimal pilot patterns.

Performance of OMP and IMAT recovery methods is evaluated.

Abstract

In communication systems, efficient use of the spectrum is an indispensable concern. Recently the use of compressed sensing for the purpose of estimating Orthogonal Frequency Division Multiplexing (OFDM) sparse multipath channels has been proposed to decrease the transmitted overhead in form of the pilot subcarriers which are essential for channel estimation. In this paper, we investigate the problem of deterministic pilot allocation in OFDM systems. The method is based on minimizing the coherence of the submatrix of the unitary Discrete Fourier Transform (DFT) matrix associated with the pilot subcarriers. Unlike the usual case of equidistant pilot subcarriers, we show that non-uniform patterns based on cyclic difference sets are optimal. In cases where there are no difference sets, we perform a greedy search method for finding a suboptimal solution. We also investigate the performance of the recovery methods such as Orthogonal Matching Pursuit (OMP) and Iterative Method with Adaptive Thresholding (IMAT) for estimation of the channel taps.