Abstract
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.
Highlights
In wireless communications, since the electromagnetic spectrum is limited, frequency bands are often simultaneously used by several radio links that are not completely isolated [1]
By adopting the information spectrum approach [20,21], we present a general formula for the capacity region of the two-user general interference channel (IC)
From the formula, it can be seen that the capacity region is the union of a family of rectangles, in which each rectangle is determined by a spectral inf-mutual information rate pair
Summary
Since the electromagnetic spectrum is limited, frequency bands are often simultaneously used by several radio links that are not completely isolated [1]. From the formula, it can be seen that the capacity region is the union of a family of rectangles, in which each rectangle is determined by a spectral inf-mutual information rate pair. The information spectrum approach, which is based on the limit superior/inferior in probability of a sequence of random variables, has been proved to be powerful in characterizing the limit behavior of a general source/channel. The information spectrum approach can be used to derive the capacity region of a general multiple access channel [23]. We use PX ( x ) to denote the probability mass function (pmf) of X if it is discrete or the probability density function (pdf) of X if it is continuous
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