Reliable wideband multichannel spectrum sensing using randomized sampling schemes

Ahmad, Bashar I.; Tarczyński, Andrzej

doi:10.1016/j.sigpro.2010.02.006

Cited by 15 publications

(14 citation statements)

References 28 publications

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“…Alternatively, relaxing the amount of information needed to assess the existence of spectral opportunities was addressed in [6][7][8]. Compressed sensing [6] techniques and randomized sensing [7,26] and sampling [8] were proposed. However, all of the aforementioned sensing techniques lead to inaccurate decisions in hidden or exposed primary sender scenarios.…”

Section: Opportunistic Spectrum Sensingmentioning

confidence: 99%

Probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks

Khattab

Perkins

Bayoumi

2011

J Wireless Com Network

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Existing distributed opportunistic spectrum management schemes do not consider the inability of today's cognitive transceivers to measure interference at the primary receivers. Consequently, optimizing the constrained cognitive radio network performance based only on the local interference measurements at the cognitive senders does not lead to truly optimal performance due to the existence of hidden (or exposed) primary senders. In this paper, we present a probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks that optimizes the constrained cognitive user goodput while taking the unavoidable inaccuracy of spectrum sensing into account. The proposed framework (i) randomly explores individual spectrum bands as local interference measurements lead to inaccurate spectrum access decisions and (ii) adopts a non-greedy probabilistic spectrum access policy that prevents a single cognitive transmission from monopolizing an available spectral opportunity. In contrast to existing techniques, our approach allows multiple cognitive flows to fairly share the available opportunities without explicit inter-flow coordination. We analytically formulate the cognitive user performance optimization problem as a mixed-integer non-linear programming to derive the optimal parameter values. We use packet-level simulations to show that our approach achieves up to 138% higher goodput with significantly better fairness characteristics compared to greedy approaches.

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Section: Opportunistic Spectrum Sensingmentioning

confidence: 99%

Probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks

Khattab

Perkins

Bayoumi

2011

J Wireless Com Network

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“…In [24], we investigated spectrum sensing of WSS signals using SARS where transmissions over the system subbands are presumed to be of equal power levels. Here, digital communication signals, which are modeled as cyclostationary processes, are analyzed and the scenario where the conveyed transmissions are of different power levels, e.g., due to the propagation channel gain, is considered.…”

Section: A Related Workmentioning

confidence: 99%

“…Here, digital communication signals, which are modeled as cyclostationary processes, are analyzed and the scenario where the conveyed transmissions are of different power levels, e.g., due to the propagation channel gain, is considered. The reliability of detection is expressed in terms of the widely embraced receiver operating characteristics (ROC) in lieu of a general metric, i.e., Chebychev's inequality parameter as in [24]. Circumventing the nonstationary nature of the communication signals either via phase randomization, e.g., [25] and [26], or assuming pseudostationarity within a short signal time window, as in [4] and [12], is the common approach adopted in the literature.…”

Section: A Related Workmentioning

confidence: 99%

“…Therefore, the adopted estimator is an admissible tool to unveil the presence of an active transmission where the examined frequency points in (2) are placed at/near the center of the system subbands, i.e., within the identified guarded regions. It is noted that for WSS signals, the used estimator is a suitable tool for detection where is independent of for all [24].…”

Section: A Evaluation Of the Estimator's Adequacymentioning

confidence: 99%

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A SARS Method for Reliable Spectrum Sensing in Multiband Communication Systems

Ahmad

Tarczyński

2011

IEEE Trans. Signal Process.

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This paper introduces a novel method of spectrum sensing in communication systems that utilizes nonuniform sampling in conjunction with a suitable spectral analysis tool. It is referred to here as spectral analysis for randomized sampling (SARS). Owing to the deployment of nonuniform sampling, the proposed technique can accomplish the sensing task by using sampling rates well below the ones demanded by uniform-sampling-based digital signal processing (DSP). The effect of the cyclostationary nature of the incoming digital communication signal on the adequacy of the adopted periodogram-type estimator for the spectrum sensing operation is addressed. The statistical characteristics of the estimator are presented. General reliability conditions on the length of the required signal observation window, i.e., sensing time, for a chosen sampling rate or vice versa are provided amid a sought system performance. The impact of the presence of noise and processing transmissions with various power levels on the derived dependability recommendations is given. The analytical results are illustrated by numerical examples. This paper establishes a new framework for efficient spectrum sensing where considerable savings on the sampling rate and number of processed samples can be attained.

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“…Another important goal of the paper is to design new sensing schemes for wideband spectrum sensing that do not require the full wideband Nyquist rate. Unlike most existing work that focuses on some sophisticated, non-uniform sub-Nyquist sampling schemes such as multi-coset sampling [21], co-prime sampling [22], and random sampling on a grid [23], this paper focuses on uniform sampling. Extensions of this work to such non-uniform, sub-Nyquist sampling schemes can be found in [24], [25].…”

Section: Introductionmentioning

confidence: 99%

Performance Metrics, Sampling Schemes, and Detection Algorithms for Wideband Spectrum Sensing

Sun

Laneman

2014

IEEE Trans. Signal Process.

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In this paper, we study the problem of wideband spectrum sensing for cognitive radio networks by partitioning it into four fundamental elements: system modeling, performance metrics, sampling schemes, and detection algorithms. Each element can potentially couple the individual channels so that designs for wideband spectrum sensing should consider the four elements jointly. We propose the -sparse model for the primary occupancies and study three uniform sampling schemes for wideband spectrum sensing, specifically, partial-band Nyquist sampling, sequential narrowband Nyquist sampling, and integer undersampling. We suggest new performance metrics more appropriate for wideband spectrum sensing, specifically, the probability of insufficient spectrum opportunity and the probability of excessive interference opportunity. We also develop detection algorithms that effectively tradeoff these metrics. Our results indicate that for performance metrics that couple the individual channels, multichannel detection algorithms have a significant advantage over channel-by-channel detection algorithms even for wideband Nyquist sampling. Furthermore, integer undersampling, which corresponds to the simplest sub-Nyquist sampling scheme, along with suitable detection algorithms exhibits appealing detection performance in the regime that better protects the primary system.

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Reliable wideband multichannel spectrum sensing using randomized sampling schemes

Cited by 15 publications

References 28 publications

Probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks

Probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks

A SARS Method for Reliable Spectrum Sensing in Multiband Communication Systems

Performance Metrics, Sampling Schemes, and Detection Algorithms for Wideband Spectrum Sensing

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