Abstract
This paper considers the competitive maximization of information rates in the Gaussian frequency-selective interference channel, subject to global power and spectral mask constraints. We focus on the practical case in which the transmission by the different users contains time and frequency synchronization offsets. We propose a unified framework based on a distributed algorithm called asynchronous iterative waterfilling algorithm. In this algorithm, the users update their power spectral density in a completely distributed and asynchronous way: some users may update their power allocation more frequently than others and they may even use outdated measurements of the received interference. Moreover the users are not required to know time and frequency offsets. Our main contribution is to provide a unified set of convergence conditions for the whole class of algorithms obtained from the asynchronous iterative waterfilling algorithm.
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