Capacity Bounds for the $K$-User Gaussian Interference Channel
Abstract
The capacity region of the -user Gaussian interference channel (GIC) is a long-standing open problem and even capacity outer bounds are little known in general. A significant progress on degrees-of-freedom (DoF) analysis, a first-order capacity approximation, for the -user GIC has provided new important insights into the problem of interest in the high signal-to-noise ratio (SNR) limit. However, such capacity approximation has been observed to have some limitations in predicting the capacity at \emph{finite} SNR. In this work, we develop a new upper-bounding technique that utilizes a new type of genie signal and applies \emph{time sharing} to genie signals at receivers. Based on this technique, we derive new upper bounds on the sum capacity of the three-user GIC with constant, complex channel coefficients and then generalize to the -user case to better understand sum-rate behavior at finite SNR. We also provide closed-form expressions of our upper bounds on the capacity of the -user symmetric GIC easily computable for \emph{any} . From the perspectives of our results, some sum-rate behavior at finite SNR is in line with the insights given by the known DoF results, while some others are not. In particular, the well-known DoF achievable for almost all constant real channel coefficients turns out to be not embodied as a substantial performance gain over a certain range of the cross-channel coefficient in the -user symmetric real case especially for \emph{large} . We further investigate the impact of phase offset between the direct-channel coefficient and the cross-channel coefficients on the sum-rate upper bound for the three-user \emph{complex} GIC. As a consequence, we aim to provide new findings that could not be predicted by the prior works on DoF of GICs.
Cite
@article{arxiv.1506.03319,
title = {Capacity Bounds for the $K$-User Gaussian Interference Channel},
author = {Junyoung Nam},
journal= {arXiv preprint arXiv:1506.03319},
year = {2017}
}
Comments
Presented in part at ISIT 2015, submitted to IEEE Transactions on Information Theory on July 2015, and revised on January 2017