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

Cyber-physical systems (CPSs) are the next generation of engineered systems in which computing, communication, and control technologies are tightly integrated. Research on CPSs is fundamentally important for engineered systems in many important application domains such as transportation, energy, and medical systems. We overview CPS research from both a historical point of view in terms of technologies developed for early generations of control systems, as well as recent results on CPSs in many relevant research domains such as networked control, hybrid systems, real-time computing, real-time networking, wireless sensor networks, security, and model-driven development. We outline the potential for CPSs in many societally important application domains.

http://cesg.tamu.edu/wp-content/uploads/2012/03/ps_files/12-02-10-CPS-Centennial.pdf

Cyber–Physical Systems: A Perspective at the Centennial

Motivated by a problem of transmitting supplemental data over broadcast channels (Birk and Kol, INFOCOM 1998), we study the following coding problem: a sender communicates with n receivers R1,..., Rn. He holds an input x ∈ {0,01l}n and wishes to broadcast a single message so that each receiver Ri can recover the bit xi. Each Ri has prior side information about x, induced by a directed graph Grain nodes; Ri knows the bits of a; in the positions {j | (i,j) is an edge of G}.G is known to the sender and to the receivers. We call encoding schemes that achieve this goal INDEXcodes for {0,1}n with side information graph G. In this paper we identify a measure on graphs, the minrank, which exactly characterizes the minimum length of linear and certain types of nonlinear INDEX codes. We show that for natural classes of side information graphs, including directed acyclic graphs, perfect graphs, odd holes, and odd anti-holes, minrank is the optimal length of arbitrary INDEX codes. For arbitrary INDEX codes and arbitrary graphs, we obtain a lower bound in terms of the size of the maximum acyclic induced subgraph. This bound holds even for randomized codes, but has been shown not to be tight.

/pdf/index-coding-with-side-information-7dq4v2sk17.pdf

Index Coding With Side Information

A sender communicates with a receiver who wishes to reliably evaluate a function of their combined data. We show that if only the sender can transmit, the number of bits required is a conditional entropy of a naturally defined graph. We also determine the number of bits needed when the communicators exchange two messages. Reference is made to the results of rate distortion in evaluating the function of two random variables.

Coding for computing

We propose the use of punctured turbo codes for compression of correlated binary sources. Compression is achieved because of puncturing. The resulting performance is close to the theoretical limit provided by the Slepian-Wolf (1973) theorem. No information about the correlation between sources is required in the encoding process. The proposed source decoder utilizes iterative schemes, and performs well even when the correlation between the sources is not known in the decoder, since it can be estimated jointly with the iterative decoding process.

Compression of correlated binary sources using turbo codes

A discrete random variable X is to be transmitted by means of a discrete signal. The receiver has prior knowledge of a discrete random variable Y jointly distributed with X . The probability of error must be exactly zero, and the problem is to minimize the signal's alphabet size. In the case where the transmitter also has access to the value of Y , the problem is trivial and no advantage can be obtained by block coding over independent repetitions. If, however, Y is not known at the transmitter then the problem is equivalent to the chromatic number problem for graphs, and block coding may produce savings.

H. Witsenhausen

Papers

The zero-error side information problem and chromatic numbers (Corresp.)