Integration of a Precolouring Matrix in the Random Demodulator model for improved Compressive Ppectrum Estimation

The random demodulator (RD) is a compressive sensing (CS) architecture for acquiring frequency sparse, bandlimited signals. Such signals occur in cognitive radio networks for instance, where efficient sampling is a critical design requirement. A recent RD-based CS system has been shown to effectively acquire and recover frequency sparse, high-order modulated multiband signals which have been precoloured by an autoregressive (AR) filter. A shortcoming of this AR-RD architecture is that precolouring imposes additional computational cost on the signal transmission system. This paper introduces a novel CS architecture which seamlessly embeds a precolouring matrix (PM) into the signal recovery stage of the RD model (iPM-RD) with the PM depending only upon the AR filter coefficients, which are readily available. Experimental results using sparse wideband quadrature phased shift keying (QPSK) and 64 quadrature amplitude modulation 64QAM) signals confirm the iPM-RD model provides improved CS performance compared with the RD, while incurring no performance degradation compared with the original AR-RD architecture

A novel precolouring-random demodulator architecture for compressive spectrum estimation

One of the main challenges of conventional spectrum estimation methods in cognitive radio applications is the very high sampling rates involved, which imposes significant operating demands upon the analog-to-digital converter (ADC). This has given impetus to employing compressive sensing (CS) techniques, such as the random demodulator (RD) structure to relax the input ADC specification. It has been recently shown the RD spectrum estimation performance for quadrature phased shift keying (PSK) modulated signals can be significantly improved in terms of spectral concentration and signal-to-noise ratio, when signals are precoloured by an autoregressive (AR) filter. This paper presents an extended AR-RD architecture, which provides enhanced CS capability for higher-order digital modulation schemes, including 16 quadrature amplitude modulation (16QAM), 64QAM and binary PSK (BPSK). Quantitative results corroborate the improved CS performance of the AR-RD structure for higher-order modulations schemes, which provides a propitious design trade-off between AR-RD complexity, latency and CS performance