5G NR CA-Polar Maximum Likelihood Decoding by GRAND
2020 54th Annual Conference on Information Sciences and Systems (CISS) CA-Polar codes have been selected for all control channel communications in 5G NR, but accurate, computationally feasible decoders are still subject to development. Here we report the performance of a recently proposed class of o...
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| creator | Duffy, Ken Solomon, Amit Konwar, Kishori M Medard, Muriel |
| description | 2020 54th Annual Conference on Information Sciences and Systems
(CISS) CA-Polar codes have been selected for all control channel communications in
5G NR, but accurate, computationally feasible decoders are still subject to
development. Here we report the performance of a recently proposed class of
optimally precise Maximum Likelihood (ML) decoders, GRAND, that can be used
with any block-code. As published theoretical results indicate that GRAND is
computationally efficient for short-length, high-rate codes and 5G CA-Polar
codes are in that class, here we consider GRAND's utility for decoding them.
Simulation results indicate that decoding of 5G CA-Polar codes by GRAND, and a
simple soft detection variant, is a practical possibility. |
| doi_str_mv | 10.48550/arxiv.1907.01077 |
| format | Article |
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(CISS) CA-Polar codes have been selected for all control channel communications in
5G NR, but accurate, computationally feasible decoders are still subject to
development. Here we report the performance of a recently proposed class of
optimally precise Maximum Likelihood (ML) decoders, GRAND, that can be used
with any block-code. As published theoretical results indicate that GRAND is
computationally efficient for short-length, high-rate codes and 5G CA-Polar
codes are in that class, here we consider GRAND's utility for decoding them.
Simulation results indicate that decoding of 5G CA-Polar codes by GRAND, and a
simple soft detection variant, is a practical possibility.</description><identifier>DOI: 10.48550/arxiv.1907.01077</identifier><language>eng</language><subject>Computer Science - Information Theory ; Mathematics - Information Theory</subject><creationdate>2019-07</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1907.01077$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1907.01077$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Duffy, Ken</creatorcontrib><creatorcontrib>Solomon, Amit</creatorcontrib><creatorcontrib>Konwar, Kishori M</creatorcontrib><creatorcontrib>Medard, Muriel</creatorcontrib><title>5G NR CA-Polar Maximum Likelihood Decoding by GRAND</title><description>2020 54th Annual Conference on Information Sciences and Systems
(CISS) CA-Polar codes have been selected for all control channel communications in
5G NR, but accurate, computationally feasible decoders are still subject to
development. Here we report the performance of a recently proposed class of
optimally precise Maximum Likelihood (ML) decoders, GRAND, that can be used
with any block-code. As published theoretical results indicate that GRAND is
computationally efficient for short-length, high-rate codes and 5G CA-Polar
codes are in that class, here we consider GRAND's utility for decoding them.
Simulation results indicate that decoding of 5G CA-Polar codes by GRAND, and a
simple soft detection variant, is a practical possibility.</description><subject>Computer Science - Information Theory</subject><subject>Mathematics - Information Theory</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotzrFOwzAUQFEvHVDhA5jqH0h4ju04HqMUAlIoqOoePdvPxWpCUBCo_fuqheluV4exewG5qrSGB5yP6TcXFkwOAoy5YVK3fLPlTZ29TwPO_BWPafwZeZcONKSPaQp8TX4K6XPP3Ym323qzvmWLiMM33f13yXZPj7vmOeve2pem7jIsjcm0KmQBIUTw1mnrqxgrIwV5siTJlioqT7qIrkQRUXuwpiTlKkAnvQ9aLtnqb3tV919zGnE-9Rd9f9XLM87GPaw</recordid><startdate>20190701</startdate><enddate>20190701</enddate><creator>Duffy, Ken</creator><creator>Solomon, Amit</creator><creator>Konwar, Kishori M</creator><creator>Medard, Muriel</creator><scope>AKY</scope><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20190701</creationdate><title>5G NR CA-Polar Maximum Likelihood Decoding by GRAND</title><author>Duffy, Ken ; Solomon, Amit ; Konwar, Kishori M ; Medard, Muriel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a677-542320ddf0c9b59c8ff8731ece9e3e964f4ce52fb6a1fa5c0976e4b80ab3ccd53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Computer Science - Information Theory</topic><topic>Mathematics - Information Theory</topic><toplevel>online_resources</toplevel><creatorcontrib>Duffy, Ken</creatorcontrib><creatorcontrib>Solomon, Amit</creatorcontrib><creatorcontrib>Konwar, Kishori M</creatorcontrib><creatorcontrib>Medard, Muriel</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv Mathematics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Duffy, Ken</au><au>Solomon, Amit</au><au>Konwar, Kishori M</au><au>Medard, Muriel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>5G NR CA-Polar Maximum Likelihood Decoding by GRAND</atitle><date>2019-07-01</date><risdate>2019</risdate><abstract>2020 54th Annual Conference on Information Sciences and Systems
(CISS) CA-Polar codes have been selected for all control channel communications in
5G NR, but accurate, computationally feasible decoders are still subject to
development. Here we report the performance of a recently proposed class of
optimally precise Maximum Likelihood (ML) decoders, GRAND, that can be used
with any block-code. As published theoretical results indicate that GRAND is
computationally efficient for short-length, high-rate codes and 5G CA-Polar
codes are in that class, here we consider GRAND's utility for decoding them.
Simulation results indicate that decoding of 5G CA-Polar codes by GRAND, and a
simple soft detection variant, is a practical possibility.</abstract><doi>10.48550/arxiv.1907.01077</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Information Theory Mathematics - Information Theory |
| title | 5G NR CA-Polar Maximum Likelihood Decoding by GRAND |
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