Joint Channel Estimation and MUD for Scalable Grant-Free Random Access

Ameha Tsegaye Abebe; Chung G. Kang

doi:10.1109/LCOMM.2019.2945577

Joint Channel Estimation and MUD for Scalable Grant-Free Random Access

Ameha Tsegaye Abebe, Chung G. Kang

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

A scalable grant-free access, which simultaneously reduces access collision rate and signaling overhead, can be enabled by allowing contending users to randomly select a preamble from a very large set of non-orthogonal preamble sequences. By casting the joint channel estimation and multi-user detection (CE-MUD) problem into a multiple measurement vector (MMV)-based compressive sensing problem and employing a two-stage active preambles search over a narrowed subspace, a scheme proposed in this letter shows significant performance improvement over conventional schemes. Particularly, the two-stage search allows the proposed scheme to support multiple order of more active users while reducing receiver's complexity.

Original language	English
Article number	8861377
Pages (from-to)	2229-2233
Number of pages	5
Journal	IEEE Communications Letters
Volume	23
Issue number	12
DOIs	https://doi.org/10.1109/LCOMM.2019.2945577
Publication status	Published - 2019 Dec

Bibliographical note

Funding Information:
Manuscript received June 25, 2019; revised August 27, 2019; accepted September 17, 2019. Date of publication October 7, 2019; date of current version December 10, 2019. This work was supported in part by Samsung Research in Samsung Electronics and in part by Korea University. The associate editor coordinating the review of this letter and approving it for publication was K. E. Psannis. (Corresponding author: Chung G. Kang.) A. T. Abebe is with the School of Electrical and Computer Engineering, Korea University, Seoul 136-713, South Korea (e-mail: [email protected]).

Publisher Copyright:
© 1997-2012 IEEE.

Keywords

MUD
Non-orthogonal preamble sequences
channel estimation
compressive sensing
grant-free random access

ASJC Scopus subject areas

Modelling and Simulation
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/LCOMM.2019.2945577

Cite this

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abstract = "A scalable grant-free access, which simultaneously reduces access collision rate and signaling overhead, can be enabled by allowing contending users to randomly select a preamble from a very large set of non-orthogonal preamble sequences. By casting the joint channel estimation and multi-user detection (CE-MUD) problem into a multiple measurement vector (MMV)-based compressive sensing problem and employing a two-stage active preambles search over a narrowed subspace, a scheme proposed in this letter shows significant performance improvement over conventional schemes. Particularly, the two-stage search allows the proposed scheme to support multiple order of more active users while reducing receiver's complexity.",

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Joint Channel Estimation and MUD for Scalable Grant-Free Random Access

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Bibliographical note

Keywords

ASJC Scopus subject areas

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