Versatile Spectrum Sensing on Mobile Devices?

Dejonghe, Antoine; Pollin, Sofie; Hollevoet, Lieven; Naessens, Frederik; Lopez, Eduardo; Raghavan, Praveen; Bourdoux, André; Wesemael, Peter Van; Ryckaert, Julien; Craninckx, Jan; Perre, Liesbet Van der

doi:10.1109/dyspan.2010.5457836

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…Since is a sequence of disjoint events, we can write A similar argument yields . Thus, we have the inequalities (5) As for classical SPRT, we assume that these inequalities hold with equality to obtain the thresholds and in terms of the desired conditional error probabilities. Thus, we set (6) We now proceed to prove the optimality of SPRT in the presence of sensor usage constraints.…”

Section: Theorem 1 (Optimality Of Sprt Without Sensor Usage Constrainmentioning

confidence: 99%

A Stochastic Sensor Selection Scheme for Sequential Hypothesis Testing With Multiple Sensors

Bai

Katewa

Gupta

et al. 2015

IEEE Trans. Signal Process.

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We study the problem of binary sequential hypothesis testing using multiple sensors with associated observation costs. An off-line randomized sensor selection strategy, in which a sensor is chosen at every time step with a given probability, is considered. The objective of this work is to find a sequential detection rule and a sensor selection probability vector such that the expected total observation cost is minimized subject to constraints on reliability and sensor usage. First, the sequential probability ratio test is shown to be the optimal sequential detection rule in this framework as well. Efficient algorithms for obtaining the optimal sensor selection probability vector are then derived. In particular, a special class of problems in which the algorithm has complexity that is linear in the number of sensors is identified. An upper bound for the average sensor usage to estimate the error incurred due to Wald's approximations is also presented. This bound can be used to set a safety margin for guaranteed satisfaction of the constraints on the sensor usage.

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Section: Theorem 1 (Optimality Of Sprt Without Sensor Usage Constrainmentioning

confidence: 99%

A Stochastic Sensor Selection Scheme for Sequential Hypothesis Testing With Multiple Sensors

Bai

Katewa

Gupta

et al. 2015

IEEE Trans. Signal Process.

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“…The sensing digital front-end is implemented with the DIFFS architecture [3]. DIFFS has now been fully implemented as a chip in 65nm CMOS technology.…”

Section: B Digital Front-end For Sensingmentioning

confidence: 99%

An integrated reconfigurable engine for multi-purpose sensing up to 6 GHz

Pollin

Hollevoet

Wesemael

et al. 2011

2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)

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We demonstrate a reconfigurable engine for multipurpose spectrum sensing within the cost and power constraints of mobile devices. The analog part builds up on the Scaldio reconfigurable analog front-end [1]. The digital part is an innovative Digital Front-end for Sensing capable of performing a range of sensing algorithms [3], which has now been fully implemented as a chip. The goal of this demo is the first demonstration of the digital chip, integrated with an analog front-end, enabling real-time validation of the sensing engine. The setup is validated for DVB-T and LTE, two important candidates for future DySPAN networks, as well as for very fast spectrum sweeping. This is the first integrated low power solution that can achieve such a very fast spectrum sweeping, thanks to the integration of two innovative components.

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“…The common component for both systems is the digital part of the system, named SPIDER, which contains the DIgital Front-end For Sensing (DIFFS) [2]. The differentiator between the two systems is the RF section, namely the SCALDIO 2B RFIC [1] and its successor, the SCALDIO 2C RFIC [3] [4].…”

Section: Hardware Componentsmentioning

confidence: 99%

Interference robust SDR FE receiver

Wesemael

Pollin

Desmet

et al. 2012

2012 IEEE International Symposium on Dynamic Spectrum Access Networks

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Research on Dynamic Spectrum Access (DSA) has focused to a large extent on the reliable detection of signals at very low power levels, possibly even under the noise floor. However, many of those channels that are detected to be free are adjacent to used channels, with possibly very large power levels. As a result, the true DSA problem is not only reliable detection of free bands, but also robust operation next to used bands. In this demo we demonstrate an SDR RFIC which is robust against outof-band interference. This robustness is achieved by improving the linearity of the SDR receiver significantly. The need for robustness is demonstrated in real time by showing the received constellation diagram of an 802.11af-like OFDM signal in the presence of a large out-of-band interferer. The wanted and interfering signal are received simultaneously by two generations of SDR RFIC's, showing both the performance degradation caused by interference from adjacent bands and the improvement enabled by the robust receiver.I.

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Versatile Spectrum Sensing on Mobile Devices?

Cited by 7 publications

References 7 publications

A Stochastic Sensor Selection Scheme for Sequential Hypothesis Testing With Multiple Sensors

A Stochastic Sensor Selection Scheme for Sequential Hypothesis Testing With Multiple Sensors

An integrated reconfigurable engine for multi-purpose sensing up to 6 GHz

Interference robust SDR FE receiver

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