An outer loop link adaptation for BICM-OFDM that learns

Sander Wahls, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Wireless BICM-OFDM systems usually perform some link adaptation procedure in order to adapt their transmission parameters to the changing channel. It is common practice to choose modulation and code rate based on thresholds on the signal-to-noise ratios (inner loop link adaptation), while these thresholds are shifted in an external control loop (outer loop link adaptation). This paper proposes a new approach for adjusting the threshold offset. Adaptive kernel regression is used in order to learn the relationship between offsets, the channel state, and packet error rates for each code rate in an online fashion. The proposed algorithm exploits this knowledge when selecting offsets. This is in contrast to current approaches, which do not anticipate the effect of changes to the offset but rely on probing only. Another advantage is that frequency-selective modulation can (but does not have to) be employed. Some less-known arguments in favor of frequency-selective modulation are pointed out.

Original languageEnglish (US)
Title of host publication2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2013
Pages719-723
Number of pages5
DOIs
StatePublished - 2013
Event2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2013 - Darmstadt, Germany
Duration: Jun 16 2013Jun 19 2013

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

Other

Other2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2013
Country/TerritoryGermany
CityDarmstadt
Period6/16/136/19/13

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Electrical and Electronic Engineering
  • Computer Science Applications

Keywords

  • Link adaptation
  • Machine learning algorithms
  • OFDM
  • Unsupervised learning

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