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.

翻译：本文提出了一种新型透射式可重构智能表面（TRIS）收发器驱动的协同集成感知、计算与通信（ISCC）网络，以满足多样化网络需求并降低能耗。协同基站（BSs）配备TRIS收发器，可在单个时隙内完成感知数据采集、通信卸载与计算任务。为获得更高的协同增益，我们采用信号级空间配准算法，该算法通过调整波束宽度实现。同时，为更高效地卸载计算任务，本文考虑多流通信并引入秩-$N$约束，采用迭代秩最小化（IRM）方案进行处理。我们构建了一个以最小化网络总能耗为目标的优化问题，联合优化波束成形矩阵、时隙分配、感知数据分配及感知波束调度变量。由于变量间存在耦合，该问题为非凸优化问题，我们采用块坐标下降（BCD）方案进行解耦求解。最终，数值仿真结果验证了所提方案在提升网络整体性能与降低网络总能耗方面的优越性。