A semi blind joint CFO estimation, equalization and data detection in presence of non-linearity for mm-Wave communications

Preety Priya, Shashank Verma, Sucharita Chakraborty, Debarati Sen

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

Abstract

Millimeter wave (mm-Wave) is an emerging paradigm towards 5G technology that can support high data rate. The foreseen potential of mm-Wave is limited by huge path loss incurred due to the high frequency operation which can be alleviated by high emission power at the transmitter. This in concurrence with the enormous bandwidth of mmWave and high frequency design limitations of the integrated circuits enforce the power amplifier (PA) into non-linear region. Further, the non-linear distortion in collusion with frequency selective channel and carrier frequency offset (CFO) degrade the signal detection performance. To solve this problem, we propose a semi-blind joint estimation of CFO and frequency selective channel gains followed by data detection in the presence of PA non-linearity. The presence of non-linearity results in the posterior probability distribution of complex data symbol to be non-Gaussian and hence, analytically intractable. Therefore, sequential importance resampling based particle filter (PF) is suggested for approximating the intractable posterior distribution of interest by the weighted random probability samples (particles) to detect the data symbols. The detected symbols are then used to jointly update the channel gains and CFO using a novel sequential maximum likelihood (ML) estimation. Extensive simulation results validate the proposed algorithm. This novel scheme enhances the non-linear signal detection performance in presence of CFO and frequency selective channel at the receiver.

Original languageEnglish
Title of host publication2018 IEEE 88th Vehicular Technology Conference (VTC-Fall) - Proceedings
EditorsJames Irvine
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1764-1768
Number of pages5
ISBN (Electronic)9781538663585, 9781538663578
ISBN (Print)9781538663592
DOIs
Publication statusPublished - 2018
Externally publishedYes
EventIEEE Vehicular Technology Conference 2018 (Fall) - Chicago, United States of America
Duration: 27 Aug 201830 Aug 2018
Conference number: 88th
https://ieeexplore.ieee.org/xpl/conhome/8672788/proceeding (Proceedings)

Publication series

NameIEEE Vehicular Technology Conference
PublisherIEEE, Institute of Electrical and Electronics Engineers
Volume2018-August
ISSN (Print)1550-2252
ISSN (Electronic)2577-2465

Conference

ConferenceIEEE Vehicular Technology Conference 2018 (Fall)
Abbreviated titleVTC Fall 2018
Country/TerritoryUnited States of America
CityChicago
Period27/08/1830/08/18
Internet address

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