Maximum mutual information vector quantization of log-likelihood ratios for memory efficient HARQ implementations

Matteo Danieli; Søren Forchhammer; Jakob Dahl Andersen; Lars P.B. Christensen; Søren Skovgaard Christensen

doi:10.1109/DCC.2010.98

Maximum mutual information vector quantization of log-likelihood ratios for memory efficient HARQ implementations

Matteo Danieli, Søren Forchhammer, Jakob Dahl Andersen, Lars P.B. Christensen, Søren Skovgaard Christensen

Nokia Danmark A/S

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Modern mobile telecommunication systems, such as 3GPP LTE, make use of Hybrid Automatic Repeat reQuest (HARQ) for efficient and reliable communication between base stations and mobile terminals. To this purpose, marginal posterior probabilities of the received bits are stored in the form of log-likelihood ratios (LLR) in order to combine information sent across different transmissions due to requests. To mitigate the effects of ever-increasing data rates that call for larger HARQ memory, vector quantization (VQ) is investigated as a technique for temporary compression of LLRs on the terminal. A capacity analysis leads to using maximum mutual information (MMI) as optimality criterion and in turn Kullback-Leibler (KL) divergence as distortion measure. Simulations run based on an LTE-like system have proven that VQ can be implemented in a computationally simple way at low rates of 2-3 bits per LLR value without compromising the system throughput.

Original language	English
Title of host publication	Data Compression Conference (DCC), 2010
Publisher	IEEE
Publication date	2010
Pages	30-39
ISBN (Print)	978-1-4244-6425-8
DOIs	https://doi.org/10.1109/DCC.2010.98
Publication status	Published - 2010
Event	Data Compression Conference 2010 - Snowbird, UT, United States Duration: 24 Mar 2010 → 26 Mar 2010 http://www.informatik.uni-trier.de/~ley/db/conf/dcc/dcc2010.html

Conference

Conference	Data Compression Conference 2010
Country/Territory	United States
City	Snowbird, UT
Period	24/03/2010 → 26/03/2010
Internet address	http://www.informatik.uni-trier.de/~ley/db/conf/dcc/dcc2010.html

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Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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http://www.cs.brandeis.edu/~dcc/Programs/Program2010.pdf

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title = "Maximum mutual information vector quantization of log-likelihood ratios for memory efficient HARQ implementations",

abstract = "Modern mobile telecommunication systems, such as 3GPP LTE, make use of Hybrid Automatic Repeat reQuest (HARQ) for efficient and reliable communication between base stations and mobile terminals. To this purpose, marginal posterior probabilities of the received bits are stored in the form of log-likelihood ratios (LLR) in order to combine information sent across different transmissions due to requests. To mitigate the effects of ever-increasing data rates that call for larger HARQ memory, vector quantization (VQ) is investigated as a technique for temporary compression of LLRs on the terminal. A capacity analysis leads to using maximum mutual information (MMI) as optimality criterion and in turn Kullback-Leibler (KL) divergence as distortion measure. Simulations run based on an LTE-like system have proven that VQ can be implemented in a computationally simple way at low rates of 2-3 bits per LLR value without compromising the system throughput.",

author = "Matteo Danieli and S{\o}ren Forchhammer and Andersen, {Jakob Dahl} and Christensen, {Lars P.B.} and {Skovgaard Christensen}, S{\o}ren",

note = "Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.; Data Compression Conference 2010, DCC 2010 ; Conference date: 24-03-2010 Through 26-03-2010",

year = "2010",

doi = "10.1109/DCC.2010.98",

language = "English",

isbn = "978-1-4244-6425-8",

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booktitle = "Data Compression Conference (DCC), 2010",

publisher = "IEEE",

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url = "http://www.informatik.uni-trier.de/~ley/db/conf/dcc/dcc2010.html",

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Danieli, M, Forchhammer, S , Andersen, JD, Christensen, LPB & Skovgaard Christensen, S 2010, Maximum mutual information vector quantization of log-likelihood ratios for memory efficient HARQ implementations. in Data Compression Conference (DCC), 2010. IEEE, pp. 30-39, Data Compression Conference 2010, Snowbird, UT, United States, 24/03/2010. https://doi.org/10.1109/DCC.2010.98

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AU - Forchhammer, Søren

AU - Andersen, Jakob Dahl

AU - Christensen, Lars P.B.

AU - Skovgaard Christensen, Søren

N1 - Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2010

Y1 - 2010

N2 - Modern mobile telecommunication systems, such as 3GPP LTE, make use of Hybrid Automatic Repeat reQuest (HARQ) for efficient and reliable communication between base stations and mobile terminals. To this purpose, marginal posterior probabilities of the received bits are stored in the form of log-likelihood ratios (LLR) in order to combine information sent across different transmissions due to requests. To mitigate the effects of ever-increasing data rates that call for larger HARQ memory, vector quantization (VQ) is investigated as a technique for temporary compression of LLRs on the terminal. A capacity analysis leads to using maximum mutual information (MMI) as optimality criterion and in turn Kullback-Leibler (KL) divergence as distortion measure. Simulations run based on an LTE-like system have proven that VQ can be implemented in a computationally simple way at low rates of 2-3 bits per LLR value without compromising the system throughput.

AB - Modern mobile telecommunication systems, such as 3GPP LTE, make use of Hybrid Automatic Repeat reQuest (HARQ) for efficient and reliable communication between base stations and mobile terminals. To this purpose, marginal posterior probabilities of the received bits are stored in the form of log-likelihood ratios (LLR) in order to combine information sent across different transmissions due to requests. To mitigate the effects of ever-increasing data rates that call for larger HARQ memory, vector quantization (VQ) is investigated as a technique for temporary compression of LLRs on the terminal. A capacity analysis leads to using maximum mutual information (MMI) as optimality criterion and in turn Kullback-Leibler (KL) divergence as distortion measure. Simulations run based on an LTE-like system have proven that VQ can be implemented in a computationally simple way at low rates of 2-3 bits per LLR value without compromising the system throughput.

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DO - 10.1109/DCC.2010.98

M3 - Article in proceedings

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EP - 39

BT - Data Compression Conference (DCC), 2010

PB - IEEE

T2 - Data Compression Conference 2010

Y2 - 24 March 2010 through 26 March 2010

ER -

Maximum mutual information vector quantization of log-likelihood ratios for memory efficient HARQ implementations

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