eprintid: 10086611
rev_number: 16
eprint_status: archive
userid: 608
dir: disk0/10/08/66/11
datestamp: 2019-11-29 11:57:25
lastmod: 2021-09-29 22:33:01
status_changed: 2019-11-29 11:57:25
type: proceedings_section
metadata_visibility: show
creators_name: Wu, T
creators_name: Grammenos, R
title: Reduced Complexity Maximum Likelihood Detector for DFT-s-SEFDM Systems
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F46
keywords: SEFDM, DFT-s-SEFDM, BER, maximum-likelihood (ML), reduced complexity detector, NB-IoT
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: In this paper, we report on the design of a Complexity-Reduced Maximum Likelihood (CRML) detector for DFT-spread Spectrally Efficient Frequency Division Multiplexing (DFT-s-SEFDM) systems. DFT-s-SEFDM systems are similar to DFT-spread Orthogonal Frequency Division Multiplexing (DFT-s-OFDM) systems, yet offer improved spectral efficiency. Simulation results demonstrate that the CRML detector can achieve the same bit error rate (BER) performance as the ML detector in DFT-s-SEFDM systems at reduced computational complexity. Specifically, compared to a conventional ML detector, it is shown that CRML can decrease the search region by up to 2^{M} times where M denotes the constellation cardinality. Depending on parameter configuration, CRML can offer up to two orders of magnitude improvement in execution runtime performance. CRML is best-suited to applications with small system sizes, for example, in narrowband Internet of Things (NB-IoT) networks.
date: 2019-11-18
date_type: published
publisher: IEEE
official_url: https://doi.org/10.23919/EUSIPCO.2019.8902942
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1722906
doi: 10.23919/eusipco.2019.8902942
isbn_13: 978-9-0827-9703-9
lyricists_name: Grammenos, Ryan
lyricists_id: RGRAM49
actors_name: Grammenos, Ryan
actors_id: RGRAM49
actors_role: owner
full_text_status: public
publication: 2019 27th European Signal Processing Conference (EUSIPCO)
event_title: 27th European Signal Processing Conference (EUSIPCO)
event_dates: 02 September 2019 - 06 September 2019
institution: 2019 27th European Signal Processing Conference (EUSIPCO)
book_title: Proceedings of the 27th European Signal Processing Conference (EUSIPCO)
citation:        Wu, T;    Grammenos, R;      (2019)    Reduced Complexity Maximum Likelihood Detector for DFT-s-SEFDM Systems.                     In:  Proceedings of the 27th European Signal Processing Conference (EUSIPCO).    IEEE       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10086611/1/EUSIPCO2019_FinalVersion.pdf