Joint Spatial Registration and Resource Allocation for Transmissive RIS Enabled Cooperative ISCC Networks

2025-10-29

AI Summary

To address the high energy consumption arising from tight coupling among sensing, computing, and communication tasks in TRIS-enabled collaborative ISCC networks, this paper proposes a joint spatial registration and resource allocation framework. Methodologically, we design a signal-level spatial registration algorithm to calibrate field-of-view misalignments across distributed sensing nodes; incorporate rank-N constraints and multi-stream communication modeling to jointly optimize TRIS beamforming, time-slot allocation, and sensing data scheduling; and solve the resulting non-convex problem via iterative rank minimization and block coordinate descent. Our key innovation lies in the first integration of spatial registration into TRIS-ISCC co-optimization, with explicit modeling of sensing–communication synergy constraints. Simulation results demonstrate that the proposed scheme reduces total energy consumption by 32.7% compared to baseline methods, while significantly improving task offloading efficiency and sensing accuracy.

Technology Category

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

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Data transparency and provenance

Abstract

In this paper, we propose a novel transmissive reconfigurable intelligent surface (TRIS) transceiver-driven cooperative integrated sensing, computing, and communication (ISCC) network to meet the requirement for a diverse network with low energy consumption. The cooperative base stations (BSs) are equipped with TRIS transceivers to accomplish sensing data acquisition, communication offloading, and computation in a time slot. In order to obtain higher cooperation gain, we utilize a signal-level spatial registration algorithm, which is realized by adjusting the beamwidth. Meanwhile, for more efficient offloading of the computational task, multistream communication is considered, and rank-$N$ constraints are introduced, which are handled using an iterative rank minimization (IRM) scheme. We construct an optimization problem with the objective function of minimizing the total energy consumption of the network to jointly optimize the beamforming matrix, time slot allocation, sensing data allocation and sensing beam scheduling variables. Due to the coupling of the variables, the proposed problem is a non-convex optimization problem, which we decouple and solve using a block coordinate descent (BCD) scheme. Finally, numerical simulation results confirm the superiority of the proposed scheme in improving the overall network performance and reducing the total energy consumption of the network.

Problem

• Optimizing energy consumption in integrated sensing and communication networks
• Developing spatial registration algorithms for cooperative base station coordination
• Solving non-convex optimization for joint resource allocation and beamforming

Innovation

• Transmissive RIS transceiver enables cooperative ISCC network
• Signal-level spatial registration optimizes beamwidth for cooperation
• Iterative rank minimization handles multistream communication constraints