H. Djelouat, M. Leinonen, L. Ribeiro and M. Juntti, "Joint User Identification and Channel Estimation via Exploiting Spatial Channel Covariance in mMTC," in IEEE Wireless Communications Letters, vol. 10, no. 4, pp. 887-891, April 2021, doi: 10.1109/LWC.2021.3049167
Joint user identification and channel estimation via exploiting spatial channel covariance in mMTC
|Author:||Djelouat, Hamza1; Leinonen, Markus1; Ribeiro, Lucas1;|
1Centre for Wireless Communications – Radio Technologies, FI-90014, University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202101202198
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2021-01-20
Grant-free random access is a key enabler in massive machine-type communications (mMTC) to reduce signalling overhead and latency thereby improving the energy efficiency. One of its main challenges lies in joint user activity identification and channel estimation (JUICE). Due to the sporadic mMTC traffic, JUICE can be solved as a compressive sensing (CS) problem. We address CS-based JUICE in uplink with single-antenna transmitters and a multiantenna base station under spatially correlated fading channels. We formulate a novel CS problem that utilizes prior information on the second order statistics of the channel of each user to improve the performance. We propose a method based on alternating direction method of multipliers to solve the JUICE efficiently. The simulation results show that the proposed method significantly improves the user identification accuracy and channel estimation performance with lower signalling overhead as compared to the baseline schemes.
IEEE wireless communications letters
|Pages:||887 - 891|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work has been financially supported in part by the Academy of Finland (grant 319485) and Academy of Finland 6Genesis Flagship (grant 318927). The work of M. Leinonen has also been financially supported in part by Infotech Oulu and the Academy of Finland (grant 323698).
|Academy of Finland Grant Number:||
319485 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
323698 (Academy of Finland Funding decision)
© 2021 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.