Symbiotic radio (SR) backscatter is a possible low-power wireless communication technique for future Internet of Things devices. In this letter, a multiple-input-multiple-output (MIMO) SR backscatter system is proposed, where the secondary multi-antenna transmission from the backscatter device (BD) to the receiver is riding on the primary multi-antenna transmission from the transmitter to the receiver. We investigate the beamforming design optimization problem which maximizes the sum capacity of primary and secondary transmissions under the capacity constraint of secondary transmission. In the MIMO SR backscatter system, each antenna of the SR BD reflects its received ambient radio frequency signals from all the transmitting antennas of the transmitter, which causes that the globally optimal solution is difficult to obtain. Here, we derive an algorithm to obtain the capacity upper bound. Furthermore, considering both primary and secondary transmissions, we propose an exact penalty method based locally optimal solution. Simulation results display that the proposed exact penalty method based locally optimal solution achieves the sum capacity which is close to the upper bound.

中文翻译：

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多输入多输出共生无线电反向散射系统中的波束成形设计

共生无线电 (SR) 反向散射是未来物联网设备的一种可能的低功耗无线通信技术。在这封信中，提出了一种多输入多输出 (MIMO) SR 反向散射系统，其中从反向散射设备 (BD) 到接收器的次要多天线传输依赖于来自发射器的主要多天线传输到接收器。我们研究了波束成形设计优化问题，该问题在二次传输的容量约束下最大化主次传输的总容量。在MIMO SR背向散射系统中，SR BD的每个天线都会反射其接收到的来自发射机所有发射天线的环境射频信号，导致难以获得全局最优解。这里，我们推导出一种算法来获得容量上限。此外，考虑到初级和次级传输，我们提出了一种基于局部最优解的精确惩罚方法。仿真结果表明，所提出的基于局部最优解的精确惩罚方法实现了接近上限的总容量。