A real time measurement based spectrum occupancy investigation in north-western india for Cognitive Radio applications

GSM-RF Channel Characterization Using a Wideband Subspace Sensing Mechanism for Cognitive Radio Networks

“…The commonly used within GSM-based primary networks is the ED, mainly because of its low computational load and minimum dependency to a priori information [19]. It was implemented in a primitive way, in [13] using a spectrum analyzer to retrieve spectrum occupancy statistics of GSM band at Jaipur city, India. However, ED is vulnerable to noise uncertainty and needs to have an accurate knowledge of the noise floor, which interrogates the accuracy of signal detection in the presence of injurious shadowing and multipath fading effects.…”

“…In addition, they do not need a priori information of the PUs signal characteristics as in [21,22] since they are not restricted to specific modulations. Furthermore, subspace techniques are significantly robust against noise as shown in [29], unlike the methods used in [13,14,19], because they rely on the eigen-decomposition of the autocorrelation matrix which allows to remove the uncertain background noise in advance. This was the main motivation behind the recent study held in [30] that used subspace filtering to sense multiple PU signals corrupted with AWGN (Additive White Guassian Noise) and Rayleigh fading.…”

“…(1) Different from the works in [11,13,14], we are proposing realistic testbed using SUs devices enabled with SDR, configured to act independently and collect periodically the signal samples emitted by GSM PUs to lower the sensing cost that usually accompanies subspace techniques in multiple antennas system design as in [15].…”

“…Authors have adopted many assumptions to meet spectrum sensing constraints in GSM bands, which question the validity of the model for real case scenarios. Other works in the literature [13,14] have addressed spectrum sensing using Energy Detection (ED) based techniques in GSM, though they are significantly vulnerable in noisy environments. Furthermore, such techniques are limited to narrow band sensing problems, which make them unable to detect more than one frequency channel per time.…”

RF-spectrum opportunities for cognitive radio networks operating over GSM channels

“…Compared with other algorithms in the literature, the proposed algorithm improves the identification performance with short observation intervals at low SNRs. Instead of adopting a specific spectrum sensing module, the spectrum availability in [7] and [12] were determined by the power level measured by a spectrum analyzer, which may penalize the analysis, namely in terms of timegranularity of the spectrum availability. Contrarily, [13] analyzed the spectrum opportunities available in the GSM bands adopting an energy detector to sense the spectrum in realtime.…”