On the Outage Capacity of a Practical Decoder Accounting for Channel Estimation Inaccuracies

TL;DR

This paper investigates the outage capacity of practical decoders under channel estimation errors, deriving a new decoding metric that improves achievable rates and BER performance in fading MIMO channels without added complexity.

Contribution

It introduces a new decoding metric for nearest neighbor decoders that accounts for channel estimation inaccuracies, enhancing performance in practical coded modulation systems.

Findings

Significant gains in achievable rates and BER with the new metric.

The proposed decoder outperforms classical mismatched ML decoders.

No additional decoding complexity is introduced.

Abstract

The optimal decoder achieving the outage capacity under imperfect channel estimation is investigated. First, by searching into the family of nearest neighbor decoders, which can be easily implemented on most practical coded modulation systems, we derive a decoding metric that minimizes the average of the transmission error probability over all channel estimation errors. Next, we specialize our general expression to obtain the corresponding decoding metric for fading MIMO channels. According to the notion of estimation-induced outage (EIO) capacity introduced in our previous work and assuming no channel state information (CSI) at the transmitter, we characterize maximal achievable information rates, using Gaussian codebooks, associated to the proposed decoder. In the case of uncorrelated Rayleigh fading, these achievable rates are compared to the rates achieved by the classical mismatched maximum-likelihood (ML) decoder and the ultimate limits given by the EIO capacity. Numerical results show that the derived metric provides significant gains for the considered scenario, in terms of achievable information rates and bit error rate (BER), in a bit interleaved coded modulation (BICM) framework, without introducing any additional decoding complexity.