Power-constrained low-complexity coding of compressed sensing measurements

We study a low delay and low complexity sensor-communication system based on compressed sensing (CS) and scalar coding for transmission. The proposed scheme uses a 1 : r channel dimension expansion on the CS measurements for protection against channel noise. Simulation results show that optimizing the choice of r and the power allocation between the r transmissions significantly improve the system performance when compared to existing CS-communication schemes. Moreover, we consider the asymptotic behaviour of our CS system as the channel signal-to-noise ratio grows without bound and show that the proposed scheme achieves the optimal scaling exponent.