AN ADAPTIVE MEASUREMENT SCHEME BASED ON COMPRESSED SENSING FOR WIDEBAND SPECTRUM DETECTION IN COGNITIVE WSN

An Adaptive Measurement Scheme (AMS) is investigated with Compressed Sensing (CS) theory in Cognitive Wireless Sensor Network (C-WSN). Local sensing information is collected via energy detection with Analog-to-Information Converter (AIC) at massive cognitive sensors, and sparse representation is considered with the exploration of spatial temporal correlation structure of detected signals. Adaptive measurement matrix is designed in AMS, which is based on maximum energy subset selection. Energy subset is calculated with sparse transformation of sensing information, and maximum energy subset is selected as the row vector of adaptive measurement matrix. In addition, the measurement matrix is constructed by orthogonalization of those selected row vectors, which also satisfies the Restricted Isometry Property (RIP) in CS theory. Orthogonal Matching Pursuit (OMP) reconstruction algorithm is implemented at sink node to recover original information. Simulation results are performed with the comparison of Random Measurement Scheme (RMS). It is revealed that, signal reconstruction effect based on AMS is superior to conventional RMS Gaussian measurement. Moreover, AMS has better detection performance than RMS at lower compression rate region, and it is suitable for large-scale C-WSN wideband spectrum sensing.

Wideband signal detection based on high-speed photonic analog-to-digital converter

This Letter demonstrates the effectiveness of a high-speed high-resolution photonic analog-to-digital converter （PADC） for wideband signal detection. The PADC system is seeded by a high-speed actively mode locked laser, and the sampling rate is multiplied via a time-wavelength interleaving scheme. According to the laboratory test, an X-band linear frequency modulation signal is detected and digitized by the PADC system. The channel mismatch effect in wideband signal detection is compensated via an algorithm based on a short-time Fourier transform. Consequently, the signal-to-distortion ratio （SDR） of the wideband signal detection is enhanced to the comparable SDR of the single-tone signal detection.

CO and CO_2 dual-gas detection based on mid-infrared wideband absorption spectroscopy

A dual-gas sensor system is developed for CO and CO_2 detection using a single broadband light source, pyroelectric detectors and time-division multiplexing(TDM) technique. A stepper motor based rotating system and a single-reflection spherical optical mirror are designed and adopted for realizing and enhancing dual-gas detection. Detailed measurements under static detection mode(without rotation) and dynamic mode(with rotation) are performed to study the performance of the sensor system for the two gas samples. The detection period is 7.9 s in one round of detection by scanning the two detectors. Based on an Allan deviation analysis, the 1σ detection limits under static operation are 3.0 parts per million(ppm) in volume and 2.6 ppm for CO and CO_2, respectively, and those under dynamic operation are 9.4 ppm and 10.8 ppm for CO and CO_2, respectively. The reported sensor has potential applications in various fields requiring CO and CO_2 detection such as in the coal mine.