Journal ArticleDOI
On the capacity of some channels with channel state information
Giuseppe Caire,Shlomo Shamai +1 more
- Vol. 45, Iss: 6, pp 2007-2019
TLDR
It is shown that variable-rate coding is not needed to achieve capacity and, even when the CSIT is not perfect, the capacity achieving power allocation is of the waferfilling type.Abstract:
We study the capacity of some channels whose conditional output probability distribution depends on a state process independent of the channel input and where channel state information (CSI) signals are available both at the transmitter (CSIT) and at the receiver (CSIR). When the channel state and the CSI signals are jointly independent and identically distributed (i.i.d.), the channel reduces to a case studied by Shannon (1958). In this case, we show that when the CSIT is a deterministic function of the CSIR, optimal coding is particularly simple. When the state process has memory, we provide a general capacity formula and we give some more restrictive conditions under which the capacity has still a simple single-letter characterization, allowing simple optimal coding. Finally, we turn to the additive white Gaussian noise (AWGN) channel with fading and we provide a generalization of some results about capacity with CSI for this channel. In particular, we show that variable-rate coding (or multiplexing of several codebooks) is not needed to achieve capacity and, even when the CSIT is not perfect, the capacity achieving power allocation is of the waferfilling type.read more
Citations
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Journal ArticleDOI
Capacity limits of MIMO channels
TL;DR: An overview of the extensive results on the Shannon capacity of single-user and multiuser multiple-input multiple-output (MIMO) channels is provided and it is shown that the capacity region of the MIMO multiple access and the largest known achievable rate region (called the dirty-paper region) for the M IMO broadcast channel are intimately related via a duality transformation.
Book
Network Information Theory
Abbas El Gamal,Young-Han Kim +1 more
TL;DR: In this article, a comprehensive treatment of network information theory and its applications is provided, which provides the first unified coverage of both classical and recent results, including successive cancellation and superposition coding, MIMO wireless communication, network coding and cooperative relaying.
Journal ArticleDOI
Fading channels: information-theoretic and communications aspects
TL;DR: This paper describes the statistical models of fading channels which are frequently used in the analysis and design of communication systems, and focuses on the information theory of fading channel, by emphasizing capacity as the most important performance measure.
References
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Book
Table of Integrals, Series, and Products
TL;DR: Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integral Integral Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequality 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform
Book
Information Theory and Reliable Communication
TL;DR: This chapter discusses Coding for Discrete Sources, Techniques for Coding and Decoding, and Source Coding with a Fidelity Criterion.
Journal ArticleDOI