RSCNet: Dynamic CSI Compression for Cloud-based WiFi Sensing

WiFi-enabled Internet-of-Things (IoT) devices are evolving from mere communication devices to sensing instruments, leveraging Channel State Information (CSI) extraction capabilities. Nevertheless, resource-constrained IoT devices and the intricacies of deep neural networks necessitate transmitting CSI to cloud servers for sensing. Although feasible, this leads to considerable communication overhead. In this context, this paper develops a novel Real-time Sensing and Compression Network (RSCNet) which enables sensing with compressed CSI; thereby reducing the communication overheads. RSCNet facilitates optimization across CSI windows composed of …

capabilities cloud cloud-based communication compression context cs.ai cs.hc cs.it cs.lg devices dynamic eess.sp extraction information internet iot leads math.it networks neural networks paper sensing servers state wifi