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Open AccessArticle

An Information-Spectrum Approach to the Capacity Region of the Interference Channel

1
School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China
2
School of Data and Computer Science, Sun Yat-sen University, Guangzhou 510006, China
3
Department of Electronic Engineering, City University of Hong Kong, Hong Kong 999077, China
4
Department of Computer Science, Jinan University, Guangzhou 510632, China
5
State Laboratory of ISN, Xidian University, Xi’an 710071, China
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in the 2012 IEEE International Symposium on Information Theory, Cambridge, MA, USA, 1–6 July 2012.
Academic Editor: Raúl Alcaraz Martínez
Entropy 2017, 19(6), 270; https://doi.org/10.3390/e19060270
Received: 8 April 2017 / Revised: 2 June 2017 / Accepted: 10 June 2017 / Published: 13 June 2017
(This article belongs to the Special Issue Multiuser Information Theory)
In this paper, a general formula for the capacity region of a general interference channel with two pairs of users is derived, which reveals that the capacity region is the union of a family of rectangles. In the region, each rectangle is determined by a pair of spectral inf-mutual information rates. The presented formula provides us with useful insights into the interference channels in spite of the difficulty of computing it. Specially, when the inputs are discrete, ergodic Markov processes and the channel is stationary memoryless, the formula can be evaluated by the BCJR (Bahl-Cocke-Jelinek-Raviv) algorithm. Also the formula suggests that considering the structure of the interference processes contributes to obtaining tighter inner bounds than the simplest one (obtained by treating the interference as noise). This is verified numerically by calculating the mutual information rates for Gaussian interference channels with embedded convolutional codes. Moreover, we present a coding scheme to approach the theoretical achievable rate pairs. Numerical results show that the decoding gains can be achieved by considering the structure of the interference. View Full-Text
Keywords: capacity region; interference channel; information spectrum; limit superior/inferior in probability; spectral inf-mutual information rate capacity region; interference channel; information spectrum; limit superior/inferior in probability; spectral inf-mutual information rate
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MDPI and ACS Style

Lin, L.; Ma, X.; Liang, C.; Huang, X.; Bai, B. An Information-Spectrum Approach to the Capacity Region of the Interference Channel. Entropy 2017, 19, 270.

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