University of Oulu

E. Moeen Taghavi, R. Hashemi, N. Rajatheva and M. Latva-Aho, "Environment-Aware Joint Active/Passive Beamforming for RIS-Aided Communications Leveraging Channel Knowledge Map," in IEEE Communications Letters, vol. 27, no. 7, pp. 1824-1828, July 2023, doi: 10.1109/LCOMM.2023.3270491

Environment-aware joint active/passive beamforming for RIS-aided communications leveraging channel knowledge map

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Author: Moeen Taghavi, Ehsan1; Hashemi, Ramin1; Rajatheva, Nandana1;
Organizations: 1Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 10.7 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2023
Publish Date: 2023-09-13


Reconfigurable intelligent surface (RIS)-aided communication is a promising technology for 6G systems to reconfigure the propagation environment proactively. However, it requires efficient real-time channel training, which suffers excessive overhead. To resolve this challenge, taking advantage of sensing with radio waves and localization, we propose a novel environment-aware joint active/passive beamforming for RIS-aided wireless communication based on the new concept of channel knowledge map (CKM). In the proposed scheme, the user equipments (UEs) location information is combined with the radio environment information provided by CKM to achieve efficient beamforming without real-time training. Simulation results show the proposed scheme’s superior performance over training-based beamforming, which is also quite robust to errors related to UE’s location in practice.

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Series: IEEE communications letters
ISSN: 1089-7798
ISSN-E: 2373-7891
ISSN-L: 1089-7798
Volume: 27
Issue: 7
Pages: 1824 - 1828
DOI: 10.1109/LCOMM.2023.3270491
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This research has been supported in part by the Academy of Finland, 6G Flagship program under Grant 346208 and in part by the European Commission through the H2020 Project Hexa-X under Grant 101015956.
EU Grant Number: (101015956) Hexa-X - A flagship for B5G/6G vision and intelligent fabric of technology enablers connecting human, physical, and digital worlds
Academy of Finland Grant Number: 346208
Detailed Information: 346208 (Academy of Finland Funding decision)
Copyright information: © The Author(s) 2023. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see