MUSIC-based multiple CFOs estimation methods for CA-OFDM systems

Chin Yi Chang, Yu Ting Sun, Meng Lin Ku

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Orthogonal frequency division multiplexing (OFDM) is a very promising technique for high data rate transmission in multipath channels. In general, the achievable data rate of an OFDM system is confined by the available bandwidth, which strongly depends on the spectrum policy. Carrier aggregation is an attractive and flexible bandwidth extension technique which allows for upgrading data rates by aggregating several contiguous or non-contiguous carriers. Different from the conventional OFDM systems, multiple carrier frequency offsets (CFOs) have to be taken into account in carrier-aggregated OFDM (CA-OFDM) systems. In this paper, a set of preambles is constructed as pilots for component carriers. Based on the received preambles, we investigate novel multiple CFOs estimation methods using MUSIC or root-MUSIC algorithms to find multiple CFOs. Two CFOs mapping methods are then proposed to map the estimated CFOs to the corresponding component carriers. Simulation results show the proposed method can get good performance, in terms of the detection error rate and mean square error (MSE) in multipath time-varying channels.

Original languageEnglish
Title of host publication2011 11th International Conference on ITS Telecommunications, ITST 2011
Pages702-707
Number of pages6
DOIs
StatePublished - 2011
Event2011 11th International Conference on ITS Telecommunications, ITST 2011 - St. Petersburg, Russian Federation
Duration: 23 Aug 201125 Aug 2011

Publication series

Name2011 11th International Conference on ITS Telecommunications, ITST 2011

Conference

Conference2011 11th International Conference on ITS Telecommunications, ITST 2011
Country/TerritoryRussian Federation
CitySt. Petersburg
Period23/08/1125/08/11

Keywords

  • Carrier aggregation
  • CFO estimation
  • MUSIC algorithms
  • OFDM
  • root-MUSIC algorithms

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