Network optimization in RIS-assisted communications

Thesis event information

Date and time of the thesis defence

Place of the thesis defence


Topic of the dissertation

Network optimization in RIS-assisted communications

Doctoral candidate

Master of Science (Tech.) Ehsan Moeen Taghavi

Faculty and unit

University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Centre for Wireless Communications

Subject of study

Communications engineering


Professor Jyri Hämäläinen, School of Electrical Engineering, Aalto University


Professor Nandana Rajatheva, University of Oulu

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Network optimization in RIS-assisted communications

This thesis presents new user association (UA) schemes that take cell interference into account for a multi-cell network aided with multiple reconfigurable intelligent surfaces (RISs). We formulate a network spectral efficiency maximization problem by jointly optimizing active beamforming at the base stations (BSs), passive beamforming at the RISs, and user-BS association with consideration to the impact of RISs. We then propose a computationally efficient iterative algorithm based on alternating optimization 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 RISs, and a penalization method combined with successive convex programming is applied for UA optimization, which is shown to achieve an optimal solution. Additionally, we balance BS loads and maximize the network utility by optimizing the user association with a matching game in another scheme.

Finally, a crucial aspect of 6G is that localization and sensing will not be a by-product of communications development but will instead be integrated into the system from the start, and thus is a main design target of 6G. Toward this, a vision for how location and sensing information can be used to support, enable, and enrich novel applications will be sketched. In addition, the potential benefits of location and sensing information for improving communications are investigated as use cases. Therefore, taking advantage of sensing with radio waves and localization, we propose a novel environment-aware joint active/passive beamforming approach for RIS-aided wireless communication based on the new concept of channel knowledge map (CKM). In the proposed scheme, the user equipment 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 the UE’s location in practice.
Last updated: 25.9.2023