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Approximately achieving Gaussian relay network capacity with lattice codes

TLDR
This paper shows that the same approximation result can be established by using lattices for transmission and quantization along with structured mappings at the relays.
Abstract
Recently, it has been shown that a quantize-map-and-forward scheme approximately achieves (within a constant number of bits) the Gaussian relay network capacity for arbitrary topologies [1]. This was established using Gaussian codebooks for transmission and random mappings at the relays. In this paper, we show that the same approximation result can be established by using lattices for transmission and quantization along with structured mappings at the relays.

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Citations
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Journal ArticleDOI

Wireless Network Information Flow: A Deterministic Approach

TL;DR: An exact characterization of the capacity of a network with nodes connected by deterministic channels is obtained, a natural generalization of the celebrated max-flow min-cut theorem for wired networks.
Journal ArticleDOI

Wireless Network Information Flow: A Deterministic Approach

TL;DR: In this paper, a deterministic channel model was proposed for Gaussian networks with a single source and a single destination and an arbitrary number of relay nodes, and a quantize-map-and-forward scheme was proposed.
Journal ArticleDOI

An Algebraic Approach to Physical-Layer Network Coding

TL;DR: A general framework is developed for studying nested-lattice-based PNC schemes-called lattice network coding (LNC) schemes for short-by making a direct connection between C&F and module theory and several generalized constructions of LNC schemes are given.
Journal ArticleDOI

Compute-and-Forward Strategies for Cooperative Distributed Antenna Systems

TL;DR: Low-complexity ATs and UTs selection schemes are presented and it is demonstrated through Monte Carlo simulation that the proposed schemes essentially eliminate the problem of rank deficiency of the system matrix and greatly mitigate the noninteger penalty affecting CoF/RCoF at high SNR.
Journal ArticleDOI

An Algebraic Approach to Physical-Layer Network Coding

TL;DR: In this article, a general framework is developed for studying nested-lattice-based PNC schemes, called lattice network coding (LNC) schemes for short, by making a direct connection between C&F and module theory.
References
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Journal ArticleDOI

Capacity theorems for the relay channel

TL;DR: In this article, the capacity of the Gaussian relay channel was investigated, and a lower bound of the capacity was established for the general relay channel, where the dependence of the received symbols upon the inputs is given by p(y,y) to both x and y. In particular, the authors proved that if y is a degraded form of y, then C \: = \: \max \!p(x,y,x,2})} \min \,{I(X,y), I(X,Y,Y,X,Y

Capacity theorems for the relay channel

TL;DR: An achievable lower bound to the capacity of the general relay channel is established and superposition block Markov encoding is used to show achievability of C, and converses are established.
Journal ArticleDOI

Wireless Network Information Flow: A Deterministic Approach

TL;DR: An exact characterization of the capacity of a network with nodes connected by deterministic channels is obtained, a natural generalization of the celebrated max-flow min-cut theorem for wired networks.
Journal ArticleDOI

Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding

TL;DR: In this article, a lattice code with lattice decoding was proposed to achieve the additive white Gaussian noise (AWGN) channel capacity, whose effective noise is reduced by a factor of /spl radic/(1+SNR/SNR) for any desired nesting ratio.
Journal ArticleDOI

Computation Over Multiple-Access Channels

TL;DR: It is shown that there is no source-channel separation theorem even when the individual sources are independent, and joint source- channel strategies are developed that are optimal when the structure of the channel probability transition matrix and the function are appropriately matched.
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