An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation

TL;DR

This paper introduces an iterative OFDM receiver that employs sparsity-based parametric channel estimation without grid restrictions, effectively avoiding leakage effects and achieving near-capacity performance at high SNRs.

Contribution

The proposed receiver uniquely avoids grid-based limitations, enabling accurate channel estimation in dense multipath environments and at high modulation orders.

Findings

Performs close to perfect CSI at all SNRs

Outperforms grid-based methods by avoiding leakage effects

Effective in dense multipath channels

Abstract

In this work we design a receiver that iteratively passes soft information between the channel estimation and data decoding stages. The receiver incorporates sparsity-based parametric channel estimation. State-of-the-art sparsity-based iterative receivers simplify the channel estimation problem by restricting the multipath delays to a grid. Our receiver does not impose such a restriction. As a result it does not suffer from the leakage effect, which destroys sparsity. Communication at near capacity rates in high SNR requires a large modulation order. Due to the close proximity of modulation symbols in such systems, the grid-based approximation is of insufficient accuracy. We show numerically that a state-of-the-art iterative receiver with grid-based sparse channel estimation exhibits a bit-error-rate floor in the high SNR regime. On the contrary, our receiver performs very close to the perfect channel state information bound for all SNR values. We also demonstrate both theoretically and numerically that parametric channel estimation works well in dense channels, i.e., when the number of multipath components is large and each individual component cannot be resolved.