Proceedings ArticleDOI
Design of network coding functions in multihop relay networks
Georg Zeitler,Ralf Koetter,Gerhard Bauch,Joerg Widmer +3 more
- pp 249-254
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TLDR
A wireless relay network with two sources, one relay, and one destination is considered, and reliability information about the coded bits in terms of log-likelihood ratios (LLRs) is transmitted from the relay to the destination.Abstract:
A wireless relay network with two sources, one relay, and one destination is considered. In case of erroneous source-relay links, reliability information about the coded bits in terms of log-likelihood ratios (LLRs) is transmitted from the relay to the destination. We introduce a transmission strategy for the reliability information at the relay. In contrast to other popular transmission methods (analog transmission, transmission via soft bit), our approach is motivated by a rate distortion problem for the LLRs obtained at the relay.read more
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Journal ArticleDOI
Nonlinear Information Bottleneck
TL;DR: In this paper, a non-parametric upper bound for mutual information is proposed to find the optimal bottleneck variable for arbitrary-distributed discrete and/or continuous random variables X and Y with a Gaussian joint distribution.
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Nonlinear Information Bottleneck.
TL;DR: This work proposes a method for performing IB on arbitrarily-distributed discrete and/or continuous X and Y, while allowing for nonlinear encoding and decoding maps, that achieves better performance than the recently-proposed “variational IB” method on several real-world datasets.
Proceedings ArticleDOI
On Quantizer Design for Soft Values in the Multiple-Access Relay Channel
TL;DR: The quantizer design is based on the information bottleneck method using the notion of relevant information as an optimization criterion and jointly compresses the soft information available for both sources at the relay.
Journal ArticleDOI
Analysis and optimization of a rateless coded joint relay system
TL;DR: The code design for a half-duplex 4-node joint relay system with two sources, one relay, and one destination and two coding schemes for information combining at the relay, namely, the superposition coding (SC) and the Raptor coding (RC).
Journal ArticleDOI
Analog Network Coding Mappings in Gaussian Multiple-Access Relay Channels
Sha Yao,Mikael Skoglund +1 more
TL;DR: This work proposes and investigates mappings based on the Archimedean spiral for analog non-linear combining for relaying in the multiple-access relay channel, and investigates the resulting achievable rate regions and sum rates.
References
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Journal ArticleDOI
Network information flow
TL;DR: This work reveals that it is in general not optimal to regard the information to be multicast as a "fluid" which can simply be routed or replicated, and by employing coding at the nodes, which the work refers to as network coding, bandwidth can in general be saved.
Journal ArticleDOI
Capacity theorems for the relay channel
Thomas M. Cover,Abbas El Gamal +1 more
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
Thomas M. Cover,A. El Gamal +1 more
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
Cooperative strategies and capacity theorems for relay networks
TL;DR: The capacity results generalize broadly, including to multiantenna transmission with Rayleigh fading, single-bounce fading, certain quasi-static fading problems, cases where partial channel knowledge is available at the transmitters, and cases where local user cooperation is permitted.
Journal ArticleDOI
Iterative decoding of binary block and convolutional codes
TL;DR: Using log-likelihood algebra, it is shown that any decoder can be used which accepts soft inputs-including a priori values-and delivers soft outputs that can be split into three terms: the soft channel and aPriori inputs, and the extrinsic value.