The 17–27 GHz Dual Horn Receiver on the NASA 70 m Canberra Antenna

A dual beam, dual polarization, low noise receiver has been installed at a Cassegrain focus of the NASA 70[Formula: see text]m antenna near Canberra, Australia. It operates in five pairs of 1[Formula: see text]GHz bands from 17 to 27[Formula: see text]GHz simultaneously. The receiver temperature measured at the feed is 21–22[Formula: see text]K at 22[Formula: see text]GHz and, during dry winter night-time conditions, zenith system temperatures as low as 35[Formula: see text]K have been observed in the 21–22[Formula: see text]GHz band. The native polarization is linear but can be converted to circular prior to down-conversion. The downconverters have complex mixers, followed by quadrature hybrids which can be bypassed or used to convert the quadrature phase channels into an upper and lower sideband, each 1000[Formula: see text]MHz wide. For spectroscopy, four ROACH1 signal processors each currently providing 32[Formula: see text]K channel spectra across four 1000[Formula: see text]MHz bands, for 0.4[Formula: see text]km/s velocity resolution at 22[Formula: see text]GHz. Using both beam- and position-switching, the receiver achieved a noise level of 5[Formula: see text]mK r.m.s. in an hour of integration and 31[Formula: see text]kHz resolution. The NASA 70[Formula: see text]m antennas have a 45 arcsec beamwidth at 22[Formula: see text]GHz and an aperture efficiency of 35.5% giving a sensitivity of 0.49[Formula: see text]K/Jy.

Statistical Properties of Energy Detection for Spectrum Sensing by Using Estimated Noise Variance

In energy detection for cognitive radio spectrum sensing, the noise variance is usually assumed given, by which a threshold is set to guarantee a desired constant false alarm rate (CFAR) or a constant detection rate (CDR). However, in practical situations, the exact information of noise variance is generally unavailable to a certain extent due to the fact that the total noise consists of time-varying thermal noise, receiver noise, and environmental noise, etc. Hence, setting the thresholds by using an estimated noise variance may result in different false alarm probabilities from the desired ones. In this paper, we analyze the basic statistical properties of the false alarm probability by using estimated noise variance, and propose a method to obtain more suitable CFAR thresholds for energy detection. Specifically, we first come up with explicit descriptions on the expectations of the resultant probability, and then analyze the upper bounds of their variance. Based on these theoretical preparations, a new method for precisely obtaining the CFAR thresholds is proposed in order to assure that the expected false alarm probability can be as close to the predetermined as possible. All analytical results derived in this paper are testified by corresponding numerical experiments.