Decentralized Cooperative Beamforming for BDRIS-Assisted Cell-Free MIMO OFDM Systems

2026-01-19

AI Summary

This work addresses the high computational overhead, imperfect channel state information, and complex base station (BS) coordination inherent in centralized approaches for BDRIS-aided cell-free MIMO-OFDM systems. To overcome these challenges, a decentralized active and passive beamforming framework is proposed, leveraging a dynamic group-connected (DGC) BDRIS architecture. The design integrates robust optimization with a consensus-based decentralized collaboration mechanism to jointly optimize the tunable BDRIS capacitances, permutation matrices, and BS precoders while minimizing inter-BS communication. An efficient solution is developed using successive concave approximation and alternating projection strategies. Simulation results demonstrate that the proposed method significantly outperforms non-cooperative benchmarks, and the DGC architecture achieves sum-rate performance close to that of fully connected BDRIS with substantially reduced overhead.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Distributed Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

In this paper, a wideband cell-free multi-stream multi-user Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system is considered operating within a smart wireless environment enabled by multiple Beyond Diagonal Reconfigurable Intelligent Surfaces (BDRISs). A novel decentralized active and passive beamforming framework, robust to imperfect channel state availability and with minimal cooperation among the system's multiple Base Stations (BSs) for deciding the final configurations of the shared BDRISs, is proposed, which aims to substantially reduce the overhead inherent in centralized solutions necessitating a central processing unit of high computational power. By considering a Dynamic Group-Connected (DGC) BDRIS architecture with frequency-selective responses per unit element, we formulate the system's sum-rate maximization problem with respect to the tunable capacitances and permutation matrices of the BDRISs as well as the precoding matrices of the BSs, which is solved via successive concave approximation and alternating projections as well as consensus-based updates for the BDRISs'design. Through extensive simulation results, it is showcased that the proposed robust decentralized cooperative approach with diverse BDRIS architectures outperforms non-cooperation benchmarks. It is also demonstrated that the considered DGC BDRIS architecture is able to provide sum-rate performance gains sufficiently close to the more complex fully-connected BDRIS structure.

Problem

• Decentralized beamforming
• BDRIS
• Cell-Free MIMO
• OFDM
• Sum-rate maximization

Innovation

• Decentralized Beamforming
• BDRIS
• Cell-Free MIMO
• Dynamic Group-Connected Architecture
• Robust Optimization