University of Oulu

E. M. Taghavi, R. Hashemi, A. Alizadeh, N. Rajatheva, M. Vu and M. Latva-aho, "Joint Active-Passive Beamforming and User Association in IRS-Assisted mmWave Cellular Networks," in IEEE Transactions on Vehicular Technology, vol. 72, no. 8, pp. 10448-10461, Aug. 2023, doi: 10.1109/TVT.2023.3260922

Joint active-passive beamforming and user association in IRS-assisted mmWave cellular networks

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Author: Moeen Taghavi, Ehsan1; Hashemi, Ramin1; Alizadeh, Alireza2;
Organizations: 16G Flagship, Centre for Wireless Communications, University of Oulu, Oulu, Finland
2Department of Electrical and Computer Engineering, Tufts University, Medford, MA, USA
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2023
Publish Date: 2023-10-04


Intelligent reflecting surfaces (IRSs) are a promising technology for future-generation wireless networks by extending coverage region to blind spots and increasing mmWave propagation paths in non-line of sight environments. User association (UA) in dense millimeter wave (mmWave) networks is vital to characterizing connections among base stations (BSs) and mobile users for load balancing, interference management, and maximizing network utility. However, it has yet to be examined thoroughly in a multi-IRS-aided network. This paper presents a new UA scheme that takes cell interference into account for a multi-cell mmWave cellular network aided with multiple IRSs. We formulate a network spectral efficiency maximization problem by jointly optimizing active beamforming (AB) at the BSs, passive beamforming (PB) at the IRSs, and user-BS association with consideration of the impact of IRSs. We then propose a computationally efficient iterative algorithm based on alternating optimization (AO) to resolve this intractable mixed-integer non-convex problem. A fractional programming technique is used to optimize active beamforming at the BSs and passive beamforming at the IRSs, and a penalization method combined with successive convex programming is applied for UA optimization, which is shown to reach the optimal solution. Simulation results show significant performance improvements obtained by the proposed algorithm, providing higher spectral efficiency compared to several benchmark algorithms, while having a low computational complexity.

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Series: IEEE transactions on vehicular technology
ISSN: 0018-9545
ISSN-E: 1939-9359
ISSN-L: 0018-9545
Volume: 72
Issue: 8
Pages: 10448 - 10461
DOI: 10.1109/TVT.2023.3260922
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work is supported in part by the Academy of Finland, 6G Flagship program under Grant 346208 and in part by the National Science Foundation under Grant 190855.
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