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A low-latency zone-based cooperative spectrum sensing

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A low-latency zone-based cooperative spectrum sensing. / G C, Deepak; Navaie, Keivan.
In: IEEE Sensors Journal, Vol. 16, No. 15, 01.08.2016, p. 6028-6042.

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G C D, Navaie K. A low-latency zone-based cooperative spectrum sensing. IEEE Sensors Journal. 2016 Aug 1;16(15):6028-6042. Epub 2016 Jun 6. doi: 10.1109/JSEN.2016.2576438

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G C, Deepak ; Navaie, Keivan. / A low-latency zone-based cooperative spectrum sensing. In: IEEE Sensors Journal. 2016 ; Vol. 16, No. 15. pp. 6028-6042.

Bibtex

@article{e4504a16fabf40e68e9f6da03352466c,
title = "A low-latency zone-based cooperative spectrum sensing",
abstract = "In this paper we propose a spectrum sensing scheme for wireless systems with low latency requirement such as machine-to-machine communications. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. This however needs efficient incorporation of sensors{\textquoteright} location informationinto spectrum sensing. We propose a multi-channel cooperative spectrum sensing technique in which an independent network of sensors, namely monitoring network, detects the spectrum availability. The monitoring network divides the coverage area into overlapped but independent zones. This enables exploiting high spatial distribution without incorporating exact sensors{\textquoteright} location. Corresponding to each zone, a zone aggregator (ZA) is introduced which processes the sensors{\textquoteright} output. The aggregated decision in each zone associated with the ZA{\textquoteright}s locationis then passed to a decision fusion center (DFC). The secondary base station (SBS) accordingly allocates the available channels to maximize the spectral efficiency. We formulate the function of the DFC as an optimization problem with the objective of maximizing the spectral efficiency. For energy detector sensors, we further obtain optimal detection threshold for different cases with various spatial densities of ZAs and SBSs. This provides extra degrees of freedom in designing the spectrum monitoring network and provides quantitative insight on network design. We furtherdevise an efficient protocol for the proposed technique with very low signaling complexity and show that the proposed method reduces the spectrum sensing latency and results in a higherspectrum efficiency. Extensive simulations confirm our analytical results and indicate a significant improvement in sensing latency and accuracy.",
author = "{G C}, Deepak and Keivan Navaie",
year = "2016",
month = aug,
day = "1",
doi = "10.1109/JSEN.2016.2576438",
language = "English",
volume = "16",
pages = "6028--6042",
journal = "IEEE Sensors Journal",
issn = "1530-437X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "15",

}

RIS

TY - JOUR

T1 - A low-latency zone-based cooperative spectrum sensing

AU - G C, Deepak

AU - Navaie, Keivan

PY - 2016/8/1

Y1 - 2016/8/1

N2 - In this paper we propose a spectrum sensing scheme for wireless systems with low latency requirement such as machine-to-machine communications. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. This however needs efficient incorporation of sensors’ location informationinto spectrum sensing. We propose a multi-channel cooperative spectrum sensing technique in which an independent network of sensors, namely monitoring network, detects the spectrum availability. The monitoring network divides the coverage area into overlapped but independent zones. This enables exploiting high spatial distribution without incorporating exact sensors’ location. Corresponding to each zone, a zone aggregator (ZA) is introduced which processes the sensors’ output. The aggregated decision in each zone associated with the ZA’s locationis then passed to a decision fusion center (DFC). The secondary base station (SBS) accordingly allocates the available channels to maximize the spectral efficiency. We formulate the function of the DFC as an optimization problem with the objective of maximizing the spectral efficiency. For energy detector sensors, we further obtain optimal detection threshold for different cases with various spatial densities of ZAs and SBSs. This provides extra degrees of freedom in designing the spectrum monitoring network and provides quantitative insight on network design. We furtherdevise an efficient protocol for the proposed technique with very low signaling complexity and show that the proposed method reduces the spectrum sensing latency and results in a higherspectrum efficiency. Extensive simulations confirm our analytical results and indicate a significant improvement in sensing latency and accuracy.

AB - In this paper we propose a spectrum sensing scheme for wireless systems with low latency requirement such as machine-to-machine communications. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. This however needs efficient incorporation of sensors’ location informationinto spectrum sensing. We propose a multi-channel cooperative spectrum sensing technique in which an independent network of sensors, namely monitoring network, detects the spectrum availability. The monitoring network divides the coverage area into overlapped but independent zones. This enables exploiting high spatial distribution without incorporating exact sensors’ location. Corresponding to each zone, a zone aggregator (ZA) is introduced which processes the sensors’ output. The aggregated decision in each zone associated with the ZA’s locationis then passed to a decision fusion center (DFC). The secondary base station (SBS) accordingly allocates the available channels to maximize the spectral efficiency. We formulate the function of the DFC as an optimization problem with the objective of maximizing the spectral efficiency. For energy detector sensors, we further obtain optimal detection threshold for different cases with various spatial densities of ZAs and SBSs. This provides extra degrees of freedom in designing the spectrum monitoring network and provides quantitative insight on network design. We furtherdevise an efficient protocol for the proposed technique with very low signaling complexity and show that the proposed method reduces the spectrum sensing latency and results in a higherspectrum efficiency. Extensive simulations confirm our analytical results and indicate a significant improvement in sensing latency and accuracy.

U2 - 10.1109/JSEN.2016.2576438

DO - 10.1109/JSEN.2016.2576438

M3 - Journal article

VL - 16

SP - 6028

EP - 6042

JO - IEEE Sensors Journal

JF - IEEE Sensors Journal

SN - 1530-437X

IS - 15

ER -