678 research outputs found

    Capacity Analysis for Gaussian and Discrete Memoryless Interference Networks

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    Interference is an important issue for wireless communication systems where multiple uncoordinated users try to access to a common medium. The problem is even more crucial for next-generation cellular networks where frequency reuse becomes ever more intense, leading to more closely placed co-channel cells. This thesis describes our attempt to understand the impact of interference on communication performance as well as optimal ways to handle interference. From the theoretical point of view, we examine how interference affects the fundamental performance limits, and provide insights on how interference should be treated for various channel models under different operating conditions. From the practical design point of view, we provide solutions to improve the system performance under unknown interference using multiple independent receptions of the same information. For the simple two-user Gaussian interference channel, we establish that the simple Frequency Division Multiplexing (FDM) technique suffices to provide the optimal sum- rate within the largest computable subregion of the general achievable rate region for a certain interference range. For the two-user discrete memoryless interference channels, we characterize different interference regimes as well as the corresponding capacity results. They include one- sided weak interference and mixed interference conditions. The sum-rate capacities are derived in both cases. The conditions, capacity expressions, as well as the capacity achieving schemes are analogous to those of the Gaussian channel model. The study also leads to new outer bounds that can be used to resolve the capacities of several new discrete memoryless interference channels. A three-user interference up-link transmission model is introduced. By examining how interference affects the behavior of the performance limits, we capture the differences and similarities between the traditional two-user channel model and the channel model with more than two users. If the interference is very strong, the capacity region is just a simple extension of the two-user case. For the strong interference case, a line segment on the boundary of the capacity region is attained. When there are links with weak interference, the performance limits behave very differently from that of the two-user case: there is no single case that is found of which treating interference as noise is optimal. In particular, for a subclass of Gaussian channels with mixed interference, a boundary point of the capacity region is determined. For the Gaussian channel with weak interference, sum capacities are obtained under various channel coefficients and power constraint conditions. The optimalities in all the cases are obtained by decoding part of the interference. Finally, we investigate a topic that has practical ramifications in real communication systems. We consider in particular a diversity reception system where independently copies of low density parity check (LDPC) coded signals are received. Relying only on non-coherent reception in a highly dynamic environment with unknown interference, soft-decision combining is achieved whose performance is shown to improve significantly over existing approaches that rely on hard decision combining

    Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities

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    This monograph presents a unified treatment of single- and multi-user problems in Shannon's information theory where we depart from the requirement that the error probability decays asymptotically in the blocklength. Instead, the error probabilities for various problems are bounded above by a non-vanishing constant and the spotlight is shone on achievable coding rates as functions of the growing blocklengths. This represents the study of asymptotic estimates with non-vanishing error probabilities. In Part I, after reviewing the fundamentals of information theory, we discuss Strassen's seminal result for binary hypothesis testing where the type-I error probability is non-vanishing and the rate of decay of the type-II error probability with growing number of independent observations is characterized. In Part II, we use this basic hypothesis testing result to develop second- and sometimes, even third-order asymptotic expansions for point-to-point communication. Finally in Part III, we consider network information theory problems for which the second-order asymptotics are known. These problems include some classes of channels with random state, the multiple-encoder distributed lossless source coding (Slepian-Wolf) problem and special cases of the Gaussian interference and multiple-access channels. Finally, we discuss avenues for further research.Comment: Further comments welcom

    Sum-Capacity of Ergodic Fading Interference and Compound Multiaccess Channels

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    The problem of resource allocation is studied for two-sender two-receiver fading Gaussian interference channels (IFCs) and compound multiaccess channels (C-MACs). The senders in an IFC communicate with their own receiver (unicast) while those in a C-MAC communicate with both receivers (multicast). The instantaneous fading state between every transmit-receive pair in this network is assumed to be known at all transmitters and receivers. Under an average power constraint at each source, the sum-capacity of the C-MAC and the power policy that achieves this capacity is developed. The conditions defining the classes of strong and very strong ergodic IFCs are presented and the multicast sum-capacity is shown to be tight for both classes.Comment: Proceedings of the 2008 IEEE International Symposium on Information Theory, Toronto, ON, Canada, July 6 - 11, 200

    Negligible Cooperation: Contrasting the Maximal- and Average-Error Cases

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    In communication networks, cooperative strategies are coding schemes where network nodes work together to improve network performance metrics such as the total rate delivered across the network. This work studies encoder cooperation in the setting of a discrete multiple access channel (MAC) with two encoders and a single decoder. A network node, here called the cooperation facilitator (CF), that is connected to both encoders via rate-limited links, enables the cooperation strategy. Previous work by the authors presents two classes of MACs: (i) one class where the average-error sum-capacity has an infinite derivative in the limit where CF output link capacities approach zero, and (ii) a second class of MACs where the maximal-error sum-capacity is not continuous at the point where the output link capacities of the CF equal zero. This work contrasts the power of the CF in the maximal- and average-error cases, showing that a constant number of bits communicated over the CF output link can yield a positive gain in the maximal-error sum-capacity, while a far greater number of bits, even numbers that grow sublinearly in the blocklength, can never yield a non-negligible gain in the average-error sum-capacity

    Lecture Notes on Network Information Theory

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    These lecture notes have been converted to a book titled Network Information Theory published recently by Cambridge University Press. This book provides a significantly expanded exposition of the material in the lecture notes as well as problems and bibliographic notes at the end of each chapter. The authors are currently preparing a set of slides based on the book that will be posted in the second half of 2012. More information about the book can be found at http://www.cambridge.org/9781107008731/. The previous (and obsolete) version of the lecture notes can be found at http://arxiv.org/abs/1001.3404v4/
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