As a green and secure wireless transmission method, secure spatial modulation is becoming a hot research area. Its basic idea is to exploit both the index of activated transmit antenna and amplitude phase modulation signal to carry messages, improve security, and save energy. In this article, we review its crucial challenges: transmit antenna selection, artificial noise projection, power allocation (PA), and joint detection at the desired receiver. We proposed a low-complexity maximum likelihood (ML) detector, which efficiently reduces the complexity of detection. Meanwhile, for the sake of improving further secrecy rate (SR) performance, a PA strategy is designed on the basis of a deep neural-network (DNN). Simulation results show that the proposed low-complexity ML detector achieves lower complexity but the same bit error rate performance, compared to the traditional ML method, while the proposed DNN method strikes a good balance between complexity and SR performance.

中文翻译：

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空间调制：未来无线网络有吸引力的安全解决方案


安全空间调制作为一种绿色、安全的无线传输方式正在成为研究热点。其基本思想是利用激活的发射天线的指标和幅度相位调制信号来承载消息，提高安全性并节省能源。在本文中，我们回顾了其关键挑战：发射天线选择、人工噪声投射、功率分配 (PA) 以及所需接收器的联合检测。我们提出了一种低复杂度的最大似然（ML）检测器，它有效地降低了检测的复杂度。同时，为了进一步提高保密率（SR）性能，设计了基于深度神经网络（DNN）的PA策略。仿真结果表明，与传统的 ML 方法相比，所提出的低复杂度 ML 检测器实现了较低的复杂度，但具有相同的误码率性能，而所提出的 DNN 方法在复杂度和 SR 性能之间取得了良好的平衡。