Being spectrally efficient, easily implemented, and highly immune to selective channel imperfections multipath fading, the Orthogonal Frequency Division Multiplexing (OFDM) can provide a sufficiently robust high data rate modulation technique for emerging wired wireless telecommunication applications. However, major drawback of OFDM that is represented by its Peak-to-Average Power Ratio (PAPR) ...

Spectrum mapping has emerged as an important problem in wireless communications, which generates a spectrum map for the resource analysis and management. Given constrained transceiver volume limited energy consumption, how to effectively reconstruct situation by sampling data is pressing challenge mapping. In this paper, exploiting sparse nature of situation, we firstly attempt solve three-dime...

Compressive sampling (CS) based energy detectors are developed for ultra-wideband (UWB) pulse position modulation (PPM), in multipath fading environments so as to reduce the sampling complexity at the receiver side. Due to sub-Nyquist rate sampling, the CS process outputs a compressed version of the received signal such that the original signal can be recovered from this low dimensional represe...

Signal processing methods have been changed substantially over the last several decades. Traditional sampling theorem of Shannon-Nyquist states that the sampling rate must be at least twice the maximum frequency presented in the signal; however, sampling at the Nyquist rate is inefficient because the signals of interest contain only a small number of significant frequencies relative to the band...

The Shannon sampling principle requires substantial amounts of data to ensure the accuracy of on-line monitoring of roller bearing fault signals. Challenges are often encountered as a result of the cumbersome data monitoring, thus a novel method focused on compressed vibration signals for detecting roller bearing faults is developed in this study. Considering that harmonics often represent the ...

Compressed sensing is a theory which guarantees the exact recovery of sparse signals from a small number of linear projections. The sampling schemes suggested by current compressed sensing theories are often of little practical relevance since they cannot be implemented on real acquisition systems. In this paper, we study a new random sampling approach that consists in projecting the signal ove...