Soft-Decision-Driven Channel Estimation for Pipelined Turbo Receivers

TL;DR

This paper introduces a Kalman-based, soft-decision-driven channel estimation algorithm tailored for pipelined turbo equalizers in MIMO-OFDM systems, effectively handling varying decision reliabilities and improving estimation accuracy.

Contribution

It presents a novel sequential channel estimation method that manages multiple soft-decisions with different reliabilities using puncturing, enhancing turbo receiver performance.

Findings

Outperforms existing channel estimation techniques in simulations.

Effectively handles correlated observations from pipeline stages.

Adapts to varying decision qualities in real-time.

Abstract

We consider channel estimation specific to turbo equalization for multiple-input multiple-output (MIMO) wireless communication. We develop a soft-decision-driven sequential algorithm geared to the pipelined turbo equalizer architecture operating on orthogonal frequency division multiplexing (OFDM) symbols. One interesting feature of the pipelined turbo equalizer is that multiple soft-decisions become available at various processing stages. A tricky issue is that these multiple decisions from different pipeline stages have varying levels of reliability. This paper establishes an effective strategy for the channel estimator to track the target channel, while dealing with observation sets with different qualities. The resulting algorithm is basically a linear sequential estimation algorithm and, as such, is Kalman-based in nature. The main difference here, however, is that the proposed algorithm employs puncturing on observation samples to effectively deal with the inherent correlation among the multiple demapper/decoder module outputs that cannot easily be removed by the traditional innovations approach. The proposed algorithm continuously monitors the quality of the feedback decisions and incorporates it in the channel estimation process. The proposed channel estimation scheme shows clear performance advantages relative to existing channel estimation techniques.