Experimental detection of mobile satellite transmissions with cyclostationary features

Abstract

SUMMARYOne of the important functions of cognitive radio (CR) technology is spectrum sensing. The implementation of an efficient spectrum sensing function can be quite challenging because of various factors such as multi-path fading, low signal-to-noise ratio of the radio communication services to be detected and the requirement to detect and analyze the signal in a short time. As a consequence, it is important to quantitatively assess the performance of spectrum sensing techniques in various scenarios. This paper investigates different digital signal processing techniques for spectrum sensing in the context of mobile satellite transmissions: power sensing, cyclostationary sensing, efficient cyclostationary sensing based on FFT accumulation method and strip spectral correlation algorithm. This paper presents experimental results on the cyclostationary properties of GSM Thuraya mobile satellite communications in various conditions both for the uplink and downlink channels. The receiver operating characteristics are computed, and the results are presented for different algorithms and different positions of the satellite terminals. The experimental results show that the cyclostationary-feature-based detection can be robust compared to energy-based technique for low signal-to-noise ratio levels.

Cyclostationarity: New trends and applications

“…Ad hoc receivers and processors have been derived for: blind detection of long-code code-division multiple access (CDMA) signals [216], quadrature amplitude modulated (QAM) signal identification [82], blind recognition and detection of orthogonal frequency division multiplexing (OFDM) signals [41,320,363], detection of binary offset carrier (BOC) signals adopted in global navigation satellite systems (GNSSs) [306] and of other mobile satellite transmissions [80], discrimination of worldwide interoperability for microwave access (WiMax) versus ultra wide-band (UWB) signals [341], blind recognition of single carrier linearly digitally modulated (SCLD) and OFDM signals [333], detection of interleaved single carrier frequency division multiple access (SC-FDMA) signals [244], classification of space-time block codes [240], digital television signal detection [373], and design of chaos-based communications systems [180]. Other ad hoc receivers are presented in [4,22,87,179,181,243,260,263,288,304,326,368,370,375] for communication signals and in [215] for radar signals.…”

Efficient Wideband Spectrum Sensing with Maximal Spectral Efficiency for LEO Mobile Satellite Systems

“…Considering the effects of dynamic and time-varying spectrum environment on CSS performance, most recent works [ 14 , 15 , 16 , 17 , 27 , 29 , 30 , 31 , 32 ] regard PU as either present or absent for the whole sensing frame length. This is a reasonable model when the PU has low traffic.…”

“…Based on the foregoing, it can be concluded that the application of CR techniques to satellite communication systems has obvious potential to improve spectral efficiency. Concretely, Dimc et al [ 14 ] performed spectrum sensing to find the signal of GSM Thuraya mobile satellite system for both uplink and downlink communication in the frequency ranges 1626.5–1660.5 MHz and 1525–1559 MHz, respectively. Clark et al [ 15 ] considered a real-world scenario involving spectrum sharing between terrestrial mobile wireless and meteorological satellite services in the band of 1695–1710 MHz with the total 15 MHz bandwidth.…”

Interference Mitigation for the GPS Receiver Utilizing the Cyclic Spectral Analysis and RR-MSWF Algorithm

“…For STFT, WT and related methods, their performance of interference mitigation often depends on the selection of transforming windows or wavelet basis functions, and this may bring some inconvenience in practical applications. On the other hand, for most man-made signals including the GPS signal and interference that we are to mitigate, they are spectral correlated in their corresponding cyclic spectral domains [15][16][17], and this feature can be used to mitigate the strong interference. Based on this, a new method utilizing CSA [18][19][20] of the received GPS signal and RR-MSWF algorithm [21], [22] to mitigate the strong interference for the GPS receiver is proposed.…”