On the calculation of the minimax-converse of the channel coding problem

A minimax-converse has been suggested for the general channel coding problem by Polyanskiy etal. This converse comes in two flavors. The first flavor is generally used for the analysis of the coding problem with non-vanishing error probability and provides an upper bound on the rate given the error probability. The second flavor fixes the rate and provides a lower bound on the error probability. Both converses are given as a min-max optimization problem of an appropriate binary hypothesis testing problem. The properties of the first converse were studies by Polyanskiy and a saddle point was proved. In this paper we study the properties of the second form and prove that it also admits a saddle point. Moreover, an algorithm for the computation of the saddle point, and hence the bound, is developed. In the DMC case, the algorithm runs in a polynomial time.Comment: Extended version of a submission to ISIT 201

On the Diversity-Multiplexing Tradeoff of Unconstrained Multiple-Access Channels

In this work the optimal diversity-multiplexing tradeoff (DMT) is investigated for the multiple-input multiple-output fading multiple-access channels with no power constraints (infinite constellations). For K users (K>1), M transmit antennas for each user, and N receive antennas, infinite constellations in general and lattices in particular are shown to attain the optimal DMT of finite constellations for the case N equals or greater than (K+1)M-1, i.e., user limited regime. On the other hand for N<(K+1)M-1 it is shown that infinite constellations can not attain the optimal DMT. This is in contrast to the point-to-point case in which infinite constellations are DMT optimal for any M and N. In general, this work shows that when the network is heavily loaded, i.e. K>max(1,(N-M+1)/M), taking into account the shaping region in the decoding process plays a crucial role in pursuing the optimal DMT. By investigating the cases where infinite constellations are optimal and suboptimal, this work also gives a geometrical interpretation to the DMT of infinite constellations in multiple-access channels

A Universal Decoder Relative to a Given Family of Metrics

Consider the following framework of universal decoding suggested in [MerhavUniversal]. Given a family of decoding metrics and random coding distribution (prior), a single, universal, decoder is optimal if for any possible channel the average error probability when using this decoder is better than the error probability attained by the best decoder in the family up to a subexponential multiplicative factor. We describe a general universal decoder in this framework. The penalty for using this universal decoder is computed. The universal metric is constructed as follows. For each metric, a canonical metric is defined and conditions for the given prior to be normal are given. A sub-exponential set of canonical metrics of normal prior can be merged to a single universal optimal metric. We provide an example where this decoder is optimal while the decoder of [MerhavUniversal] is not.Comment: Accepted to ISIT 201

Optimal Feedback Communication via Posterior Matching

In this paper we introduce a fundamental principle for optimal communication over general memoryless channels in the presence of noiseless feedback, termed posterior matching. Using this principle, we devise a (simple, sequential) generic feedback transmission scheme suitable for a large class of memoryless channels and input distributions, achieving any rate below the corresponding mutual information. This provides a unified framework for optimal feedback communication in which the Horstein scheme (BSC) and the Schalkwijk-Kailath scheme (AWGN channel) are special cases. Thus, as a corollary, we prove that the Horstein scheme indeed attains the BSC capacity, settling a longstanding conjecture. We further provide closed form expressions for the error probability of the scheme over a range of rates, and derive the achievable rates in a mismatch setting where the scheme is designed according to the wrong channel model. Several illustrative examples of the posterior matching scheme for specific channels are given, and the corresponding error probability expressions are evaluated. The proof techniques employed utilize novel relations between information rates and contraction properties of iterated function systems.Comment: IEEE Transactions on Information Theor