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https://doi.org/10.1109/comst....
Article . 2019 . Peer-reviewed
License: IEEE Open Access
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A Tutorial on Lossy Forwarding Cooperative Relaying

Authors: Jiguang He; Valtteri Tervo; Xiaobo Zhou 0003; Xin He 0017; Shen Qian; Meng Cheng; Markku J. Juntti; +1 Authors

A Tutorial on Lossy Forwarding Cooperative Relaying

Abstract

Lossy decode-and-forward (DF) relaying, also referred to as lossy forwarding (LF), can significantly enhance the transmission reliability and expand the communication coverage at the cost of a small increase in computational effort compared to its DF counterpart. Furthermore, it can further simplify the operations at the relay nodes by removing the error-detecting operation, e.g., cyclic redundancy check, which is used in the conventional DF systems. Due to these advantages, LF has been intensively investigated with the aim of its applications to various cooperative communication networks with different topologies. This paper offers a comprehensive literature review on the LF relaying strategy and makes comparisons between LF and DF. Five basic exemplifying scenarios are taken into consideration. These are the three-node network, the single-source multi-relay network with direct source-to-destination link, the multiple access relay channel, the two-way relay network, and the general multi-source multi-relay network. The paper includes not only theoretical performance limit analyses, but also performance evaluation by employing low-complexity accumulator aided turbo codes at the sources and relays as well as joint decoding at the destination. As expected, the performance enhancement in terms of outage probability, frame error rate, and $ {\epsilon }$ -outage achievable rate by LF over DF is significant, which is demonstrated in all the exemplifying scenarios in the literatures. Hence LF has a great potential to be applied to future 5G wireless communication networks, e.g., device-to-device, vehicle-to-vehicle, and machine-type communications, which are composed of the aforementioned exemplifying scenarios.

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Finland
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Keywords

lossy source-channel separation theorem, distributed turbo code, lossy forwarding, Slepian-Wolf, multiple access relay channel, source coding with a helper, Decode-and-forward, joint decoding

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
38
Top 10%
Top 10%
Top 10%
Green
bronze