Neuromorphic computing is an emerging technology that support event-driven data processing for applications requiring efficient online inference and/or control. Recent work has introduced the concept of neuromorphic communications, whereby neuromorphic computing is integrated with impulse radio (IR) transmission to implement low-energy and low-latency remote inference in wireless IoT networks. In this paper, we introduce neuromorphic integrated sensing and communications (N-ISAC), a novel solution that enables efficient online data decoding and radar sensing. N-ISAC leverages a common IR waveform for the dual purpose of conveying digital information and of detecting the presence or absence of a radar target. A spiking neural network (SNN) is deployed at the receiver to decode digital data and detect the radar target using directly the received signal. The SNN operation is optimized by balancing performance metric for data communications and radar sensing, highlighting synergies and trade-offs between the two applications.
翻译:神经地貌计算是一种新兴技术,支持对需要高效率在线推断和/或控制的应用进行事件驱动的数据处理。最近的工作引入了神经地貌通信的概念,根据这一概念,神经地貌计算与脉冲无线电(IR)传输相结合,在无线IoT网络中实施低能和低长远程推断。在本文中,我们引入神经地貌综合遥感和通信(N-ISAC),这是一个新颖的解决办法,能够有效地进行在线数据解码和雷达遥感。N-ISAC利用一种通用的IR波形,以双重目的传递数字信息并探测雷达目标的存在或不存在。在接收器中安装了一个闪烁式神经网络(SNN),以直接利用接收的信号解码数字数据并探测雷达目标。SNNE行动通过平衡数据通信和雷达遥感的性能衡量标准,突出两个应用之间的协同作用和取舍来优化。