Wireless Communications

Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified by the definition of a cognitive radio as an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. This side information typically comprises knowledge about the activity, channels, codebooks, and/or messages of other nodes with which the cognitive node shares the spectrum. Based on the nature of the available side information as well as a priori rules about spectrum usage, cognitive radio systems seek to underlay, overlay, or interweave the cognitive radios' signals with the transmissions of noncognitive nodes. We provide a comprehensive summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information-theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today's crowded spectrum.

Breaking Spectrum Gridlock With Cognitive Radios: An Information Theoretic Perspective

This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multihop networks, and extensions to distributed computing, secrecy, wireless communication, and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding, and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. This book is ideal for use in the classroom, for self-study, and as a reference for researchers and engineers in industry and academia.

Network Information Theory

Information Theory and Reliable Communication

Wyner's results for discrete memoryless wire-tap channels are extended to the Gaussian wire-tap channel. It is shown that the secrecy capacity Cs is the difference between the capacities of the main and wire.tap channels. It is further shown that Rd= Cs is the upper boundary of the achievable rate-equivocation region.

The Gaussian wire-tap channel

This paper generalizes Cover's results on broadcast channels with two binary symmetric channels (BSC) to the class of degraded channels with N components. A random code, and its associated decoding scheme, is shown to have expected probability of error going to zero for all components simultaneously as the codeword length goes to infinity, if the point representing the rates to the various receivers falls in the set of achievable rates described by this paper. A procedure to expurgate a good random broadcast code is given, leading to a bound on the maximum probability of error. Binary symmetric broadcast channels always fall in the class of degraded broadcast channels. The results of the paper are applied to this class of channels of potential practical importance.

Random coding theorem for broadcast channels with degraded components

Sets of achievable rates for the additive white Gaussian noise broadcast channel have been found by Cover [1] for channels with two outputs and generalized by Bergmans [2] to channels with any number of outputs. In this correspondence, we establish a simple converse showing the optimality of these sets of achievable rates. The proof is made simple by use of special properties of the Gaussian channel.

P. Bergmans

Papers

Random coding theorem for broadcast channels with degraded components

A simple converse for broadcast channels with additive white Gaussian noise (Corresp.)