Distributed Joint Multi-cell Optimization of IRS Parameters with Linear Precoders

We present distributed methods for jointly optimizing Intelligent Reflecting Surface (IRS) phase-shifts and beamformers in a cellular network. The proposed schemes require knowledge of only the intra-cell training sequences and corresponding received signals without explicit channel estimation. Inst...

Full description

Saved in:
Bibliographic Details
Published in:IEEE International Conference on Communications (2003) pp. 1468 - 1474
Main Authors: Wiesmayr, R., Honig, M., Joham, M., Utschick, W.
Format: Conference Proceeding
Language:English
Published: IEEE 16.05.2022
Subjects:
Channel estimation
Degradation
Intelligent reflecting surfaces
Intercell interference
MIMO
Power control
precoder optimization
Simulation
Synchronization
Training
ISSN:1938-1883
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We present distributed methods for jointly optimizing Intelligent Reflecting Surface (IRS) phase-shifts and beamformers in a cellular network. The proposed schemes require knowledge of only the intra-cell training sequences and corresponding received signals without explicit channel estimation. Instead, an achievable sum-rate objective is estimated via sample means and maximized directly. This automatically includes and mitigates both intra- and inter-cell interference provided that the uplink training is synchronized across cells. Different schemes are considered that limit the set of known training sequences from interferers. With MIMO links an iterative synchronous bi-directional training scheme jointly optimizes the IRS parameters with the beamformers and combiners. Simulation results show that the proposed distributed methods show a modest performance degradation compared to centralized channel estimation schemes, which estimate all channels including all cross-channels, and perform significantly better than decentralized channel estimation schemes which ignore the inter-cell interference.
ISSN:1938-1883
DOI:10.1109/ICC45855.2022.9839115