Random Access Compressed Sensing over Fading and Noisy Communication Channels

Random Access Compressed Sensing (RACS) is an efficient method for data gathering from a network of distributed sensors with limited resources. RACS relies on integrating random sensing with the communication architecture, and achieves overall efficiency in terms of the energy per bit of information successfully delivered. To address realistic deployment conditions, we consider data gathering over a fading and noisy communication channel. We provide a framework for system design under various fading conditions, and quantify the bandwidth and energy requirements of RACS in fading. We show that for most practical values of the signal to noise ratio, energy utilization is higher in a fading channel than it is in a non-fading channel, while the minimum required bandwidth is lower. Finally, we demonstrate the savings in the overall energy and the bandwidth requirements of RACS compared to a conventional TDMA scheme. We show that considerable gains in energy -on the order of 10 dB- are achievable, as well as a reduction in the required bandwidth, e.g., 2.5-fold decrease in the bandwidth for a network of 4000 nodes.