On the Performance of Joint Channel Estimation and MUD for CS-Based Random Access in Multi-Cell Environment

Ameha T. Abebe, Chung Gu Kang

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

1 Citation (Scopus)

Abstract

Synchronization, channel estimation, and multi-user detection (MUD) can be performed in a single shot for a comprehensive grant-free access [1]. The scheme employs compressive sensing by exploiting two sparse phenomena: sparsity in users' activity and sparsity in channel delay spread. The performance of compressive sensing based schemes should be thoroughly studied in a multi-cell environment as the other-cell interference (OCI) may affect the underlying sparsity. In this paper, we provide a performance analysis of the comprehensive grant-free access scheme in a multi-cell environment and showed that OCI would not affect the sparsity of the received signal, and rather can be considered as a dispersed noise, if signature allocation among cells is properly handled. Furthermore, we show the performance & complexity of the receiver in contrast with other multiple measurement vector-based receivers modified for joint & blind channel estimation and (MUD).

Original languageEnglish
Title of host publication2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509059089
DOIs
Publication statusPublished - 2017 May 3
Event2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017 - San Francisco, United States
Duration: 2017 Mar 192017 Mar 22

Other

Other2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017
CountryUnited States
CitySan Francisco
Period17/3/1917/3/22

Fingerprint

Multiuser detection
Channel estimation
Synchronization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Renewable Energy, Sustainability and the Environment
  • Media Technology
  • Software

Cite this

Abebe, A. T., & Kang, C. G. (2017). On the Performance of Joint Channel Estimation and MUD for CS-Based Random Access in Multi-Cell Environment. In 2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017 [7919090] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WCNCW.2017.7919090

On the Performance of Joint Channel Estimation and MUD for CS-Based Random Access in Multi-Cell Environment. / Abebe, Ameha T.; Kang, Chung Gu.

2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7919090.

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

Abebe, AT & Kang, CG 2017, On the Performance of Joint Channel Estimation and MUD for CS-Based Random Access in Multi-Cell Environment. in 2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017., 7919090, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017, San Francisco, United States, 17/3/19. https://doi.org/10.1109/WCNCW.2017.7919090
Abebe AT, Kang CG. On the Performance of Joint Channel Estimation and MUD for CS-Based Random Access in Multi-Cell Environment. In 2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 7919090 https://doi.org/10.1109/WCNCW.2017.7919090
Abebe, Ameha T. ; Kang, Chung Gu. / On the Performance of Joint Channel Estimation and MUD for CS-Based Random Access in Multi-Cell Environment. 2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017. Institute of Electrical and Electronics Engineers Inc., 2017.
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