Interference Alignment and a Noisy Interference Regime for Many-to-One Interference Channels

TL;DR

This paper investigates the capacity of many-to-one interference channels, identifying a noisy interference regime where simple random coding and treating interference as noise achieve optimal sum-capacity, extending results to practical input constraints and various channel conditions.

Contribution

It introduces a noisy interference regime for many-to-one channels, extending capacity results to finite constellations and channels without full CSI, and identifies when random coding is optimal.

Findings

Noisy interference regime achieves sum-capacity with random coding.

Extension of noisy interference results to finite constellations like PSK and QAM.

Identification of a deterministic channel class where random coding is optimal without interference alignment.

Abstract

We study the capacity of discrete memoryless many-to-one interference channels, i.e., K user interference channels where only one receiver faces interference. For a class of many-to-one interference channels, we identify a noisy interference regime, i.e., a regime where random coding and treating interference as noise achieves sum-capacity. Specializing our results to the Gaussian MIMO many-to-one interference channel, which is a special case of the class of channels considered, we obtain new capacity results. Firstly, we extend the noisy interference regime, previously studied for (many-to-one) interference channels with average power constraints on the inputs, to a more general class of inputs. This more general class includes the practical scenario of inputs being restricted to fixed finite-size constellations such as PSK or QAM. Secondly, we extend noisy interference results previously studied in SISO interference channels with full channel state information (CSI) at all nodes, to MIMO and parallel Gaussian many-to-one interference channels, and to fading Gaussian many-to-one interference channels without CSI at the transmitters. While the many-to-one interference channel requires interference alignment, which in turn requires structured codes in general, we argue that in the noisy interference regime, interference is implicitly aligned by random coding irrespective of the input distribution. As a byproduct of our study, we identify a second class of many-to-one interference channels (albeit deterministic) where random coding is optimal (though interference is not treated as noise). The optimality of random coding in this second class of channels is due to an interference resolvability condition which precludes interference alignment and hence obviates the need of structured codes.