Paper Info
Title
Reduced Complexity Maximum Likelihood Detector for DFT-s-SEFDM Systems
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 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</sup> 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.
Year
DOI
Venue
2019
10.23919/EUSIPCO.2019.8902942
2019 27th European Signal Processing Conference (EUSIPCO)
Keywords
Field
DocType
SEFDM,DFT-s-SEFDM,BER,maximum-likelihood (ML),reduced complexity detector,NB-IoT
Narrowband,Computer science,Frequency-division multiplexing,Cardinality,Algorithm,Spectral efficiency,Detector,Orthogonal frequency-division multiplexing,Bit error rate,Computational complexity theory
Conference
ISSN
ISBN
Citations 
2219-5491
978-1-5386-7300-3
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Tong Wu100.34
Ryan C. Grammenos2726.07