On the Outage Capacity of a Practical Decoder Using Channel Estimation Accuracy

TL;DR

This paper develops a practical decoding metric that minimizes error probability under channel estimation errors, achieving near-optimal outage capacity in fading channels without added complexity.

Contribution

It introduces a new decoding metric within the nearest neighbor family that attains the outage capacity of a composite channel under imperfect estimation.

Findings

The proposed metric outperforms classical mismatched ML decoding in Rayleigh fading MIMO channels.

Numerical results show significant gains in achievable rates and BER with no extra decoding complexity.

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. This metric, for arbitrary memoryless channels, achieves the capacity of a composite (more noisy) channel. Next, according to the notion of estimation-induced outage capacity (EIO capacity) introduced in our previous work, we characterize maximal achievable information rates associated to the proposed decoder. The performance of the proposed decoding metric over uncorrelated Rayleigh fading MIMO channels is compared to both the classical mismatched maximum-likelihood (ML) decoder and the theoretical limits given by the EIO capacity (i.e. the best decoder in presence of channel estimation errors). Numerical results show that the derived metric provides significant gains, 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.