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Published September 2017 | Submitted
Journal Article Open

The Dirty MIMO Multiple-Access Channel

Abstract

In the scalar dirty multiple-access channel, in addition to Gaussian noise, two additive interference signals are present, each known non-causally to a single transmitter. It was shown by Philosof et al.. that for strong interferences, an i.i.d. ensemble of codes does not achieve the capacity region. Rather, a structured-codes approach was presented, that was shown to be optimal in the limit of high signal-to-noise ratios, where the sum-capacity is dictated by the minimal ("bottleneck") channel gain. In the present work, we consider the multipleinput multiple-output (MIMO) variant of this setting. In order to incorporate structured codes in this case, one can utilize matrix decompositions, which transform the channel into effective parallel scalar dirty multiple-access channels. This approach however suffers from a "bottleneck" effect for each effective scalar channel and therefore the achievable rates strongly depend on the chosen decomposition. It is shown that a recently proposed decomposition, where the diagonals of the effective channel matrices are equal up to a scaling factor, is optimal at high signal-to-noise ratios, under an equal rank assumption. This approach is then extended to any number of transmitters. Finally, an application to physical-layer network coding for the MIMO two-way relay channel is presented.

Additional Information

© 2017 IEEE. March 10, 2017. Date of publication April 27, 2017; date of current version August 16, 2017. Manuscript received October 25, 2015; revised January 9, 2017; accepted March 10, 2017. Date of publication April 27, 2017; date of current version August 16, 2017. A. Khina was supported in part by the Feder Family Award, in part by the Trotsky Foundation at Tel Aviv University, in part by the Yitzhak and Chaya Weinstein Research Institute for Signal Processing, and in part by the Clore Israel Foundation. Y. Kochman was supported in part by the Israeli Science Foundation under Grant #956/12, in part by the German–Israeli Foundation for Scientific Research and Development, and in part by the HUJI Cyber Security Research Center in conjunction with the Israel National Cyber Bureau in the Prime Minister's Office. U. Erez was supported by the ISF under Grant 1956/15. This paper was presented in part at the 2011 IEEE International Symposium of Information Theory and at the 2016 IEEE International Symposium of Information Theory.

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