Literature Database Entry


Joana Angjo, "Coexistence Challenges in IRS-assisted Multi-Operator Networks," Proceedings of International Conference on Networked Systems (NetSys 2023), Poster Session, Potsdam, Germany, September 2023.


The deployment of intelligent reconfigurable surfaces (IRS) by wireless operators has gained significant attention as a means to optimize communication performance. IRS can manipulate the channel propagation characteristics not only for signals from the deploying operator but also for other operators in the same spatial location, even if they use different frequencies. However, the absence of bandpass filtering in IRS can lead to unwanted reflections and interference. We argue that IRS should be co-controlled by the operators to achieve efficient multi-operator coexistence. A solution might be to split a common IRS is split into multiple sub-blocks (subIRS) and dynamically assigning them to operators based on their spatial requirements. Through simulations, we demonstrate that properly assigning subIRS to operators can significantly enhance the performance of the overall multi-operator network compared to random assignments. Our results indicate substantial improvements in terms of the sum rate and fairness, as measured by the Jain's fairness index (JFI), with enhancements of up to a factor of 4.5 compared to the worst-case assignment. Furthermore, we explore the impact of factors such as the number of random assignments, operators, IRS elements, and spectrum on the system performance.

Quick access

BibTeX BibTeX


Joana Angjo

BibTeX reference

    author = {Angjo, Joana},
    title = {{Coexistence Challenges in IRS-assisted Multi-Operator Networks}},
    address = {Potsdam, Germany},
    booktitle = {International Conference on Networked Systems (NetSys 2023), Poster Session},
    month = {9},
    year = {2023},

Copyright notice

Links to final or draft versions of papers are presented here to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or distributed for commercial purposes without the explicit permission of the copyright holder.

The following applies to all papers listed above that have IEEE copyrights: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

The following applies to all papers listed above that are in submission to IEEE conference/workshop proceedings or journals: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

The following applies to all papers listed above that have ACM copyrights: ACM COPYRIGHT NOTICE. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or

The following applies to all SpringerLink papers listed above that have Springer Science+Business Media copyrights: The original publication is available at

This page was automatically generated using BibDB and bib2web.