Noisy-interference sum-rate capacity of parallel Gaussian interference channels

Authors:
Xiaohu Shang;Biao Chen;Gerhard Kramer;H. Vincent Poor
Affiliations:
Department of EE, Princeton University;Department of EECS, Syracuse University;Department of EE, University of Southern California;Department of EE, Princeton University
Venue:
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
Year:
2009

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Abstract

The sum-rate capacity of the parallel Gaussian interference channel is studied. Sufficient conditions are derived in terms of channel coefficients and power constraints such that the sum-rate capacity can be achieved by: 1) independent transmission across sub-channels, and 2) treating interference as noise in each sub-channel. The optimal power allocation is characterized for such parallel channels.