Sensitive White Space Detection with Spectral Covariance Sensing

This paper proposes a novel, highly effective spectrum sensing algorithm for cognitive radio and whitespace applications. The proposed spectral covariance sensing (SCS) algorithm exploits the different statistical correlations of the received signal and noise in the frequency domain. Test statistics are computed from the covariance matrix of a partial spectrogram and compared with a decision threshold to determine whether a primary signal or arbitrary type is present or not. This detector is analyzed theoretically and verified through realistic open-source simulations using actual digital television signals captured in the US. Compared to the state of the art in the literature, SCS improves sensitivity by 3 dB for the same dwell time, which is a very significant improvement for this application. Further, it is shown that SCS is highly robust to noise uncertainty, whereas many other spectrum sensors are not

Spectrum Sensing of DVB-T2 Signals in Multipath Channels for Cognitive Radio Networks

© 2018 VDE VERLAG GMBHIn this paper, spectrum sensing of digital video broadcasting-second generation terrestrial (DVB-T2) signals in different fading environments with energy detection (ED) is considered. ED is known to achieve an increased performance among low computational complexity detectors, but it is susceptible to noise uncertainty. By taking into consideration the edge pilot and scattered pilot periodicity in DVB-T2 signals, a low computational complex noise power estimator is proposed. It is shown analytically that the choice of detector depends on the environment, the detector requirements, the available prior knowledge and with the noise power estimator. Simulation confirm that with the noise power estimator, ED significantly outperforms the pilot correlation-based detectors. Simulation also show that the proposed scheme enables ED to obtain increased detection performance in fading channels

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Development of UHF radiometer

A wideband multifrequency UHF radiometer was initially developed to operate in the 500 to 710 MHz frequency range for the remote measurement of ocean water salinity. However, radio-frequency interference required a reconfiguration to operate in the single-frequency radio astronomy band of 608 to 614 MHz. Details of the radiometer development and testing are described. Flight testing over variable terrain provided a performance comparison of the UHF radiometer with an L-band radiometer for remote sensing of geophysical parameters. Although theoretically more sensitive, the UHF radiometer was found to be less desirable in practice than the L-band radiometer

A Practical Distributed Spectrum Sensing System

As the demand for wireless communication systems grows, the need for spectrum grows accordingly. However, a large portion of the usable spectrum has already been exclusively licensed to various entities. This exclusive allocation method encourages spectrum to be left unused if the licensee has no need for that spectrum. In order to better utilize spectrum and formulate new approaches for greater spectrum use efficiency, it is imperative to possess a thorough understanding about how wireless spectrum behaves over time, frequency, and space. In this thesis, a practical, scalable, and low-cost wideband distributed spectrum sensing system is designed, implemented, and tested. The proposed system is made up of a collection of nodes that use general purpose, off-the-shelf computer hardware as well as a collection of inexpensive software-defined radio (SDR) equipment in order to collect and analyze spectrum data that varies across time, frequency, and space. The spectrum data the proposed system collects is the power present at a given frequency. The tools needed to analyze the gathered data are also created, including a periodogram and spectrogram function, which visualize average spectrum use over a period of time and as spectrum use varies with time, respectively. The proposed system also facilitates the testing of a spatio-spectrum characterization method using real data. This method has only been simulated up to this point. The characterization technique allows for spatially varying spectrum measurements to be visualized using heat maps