A framework for R.F. spectrum measurements and analysis

Weidling, F.; Datla, Dinesh; Petty, V.R.; Krishnan, P.; Minden, Gary J.

doi:10.1109/dyspan.2005.1542672

Cited by 33 publications

(31 citation statements)

References 2 publications

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“…A well chosen detection threshold can minimize spectrum sensing error, provide the primary user with enough protection, and fully enhance spectrum utilization. In [20], the detection threshold is optimized iteratively to satisfy the requirement on false alarm probability. Threshold optimization subject to spectrum sensing constraints is investigated in [21], where an optimal adaptive threshold level is developed by utilizing the spectrum sensing error function.…”

Section: ) Energy Detectormentioning

confidence: 99%

Advances in cognitive radio networks: A survey

Wang

Liu

2011

IEEE J. Sel. Top. Signal Process.

1,125

107

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Abstract-With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years on cognitive radios. This paper surveys recent advances in research related to cognitive radios. The fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications are first introduced. The existing works in spectrum sensing are reviewed, and important issues in dynamic spectrum allocation and sharing are investigated in detail.Index Terms-Cognitive radio (CR), platforms and standards, radio spectrum management, software radio, spectrum sensing, wireless communication.

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Section: ) Energy Detectormentioning

confidence: 99%

Advances in cognitive radio networks: A survey

Wang

Liu

2011

IEEE J. Sel. Top. Signal Process.

1,125

107

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“…1. During the sensing operation, the RF front end functions as a passive receiver that captures the spectrum measurements, with the signal presence detected using energy detection techniques [4]. The spectrum sensing control mechanism controls the parameters of the sensing operation.…”

Section: Proposed Parametric Adaptive Spectrum Sensing Architecturementioning

confidence: 99%

Parametric Adaptive Spectrum Sensing Framework for Dynamic Spectrum Access Networks

Datla

Rajbanshi

Wyglinski

et al. 2007

2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks

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The opportunistic usage of the spectrum must be done without causing any interference to the licensed spectrum users. Conventional non-adaptive wideband spectrum sensing approaches could potentially be inefficient since they generally employ the same scanning resolution, even though the spectrum might contain different types of signals, individually requiring scans with different resolutions. In this paper, we present a novel spectrum sensing framework that adapts its parameters across the spectrum of interest according to the characteristics of its occupancy. We also propose a dynamic scheduling algorithm for spectrum sensing which allocates different time resolutions to different portions of the spectrum. We demonstrate that the proposed algorithm improves the efficiency of spectrum sensing over a non-adaptive approach.

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“…Based on a comparison between the output of the energy detector and the given threshold for primary users, the challenges for energy detection are the selection of the appropriate detection threshold, the inability to differentiate interference from primary users and noise, and the poor performance under low signal-to-noise ratio (SNR) values [29]. There has been abundant research on these challenges, such as [30,31].…”

Section: Spectrum Sensingmentioning

confidence: 99%

Intelligent and efficient development of wireless networks: A review of cognitive radio networks

et al. 2012

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Facing the challenges on how to improve spectrum efficiency and how to realize heterogeneous network convergence in future wireless networks, a cognitive radio network (CRN) is proposed as one of the solutions. This has become a major research topic in recent years and it is timely to give an overview of the development of CRN and to summarize key issues and technologies. The fundamental concepts of CRN, including the cognitive cycle model, the network architecture, and the cognitive ability and intelligent decision functions, are introduced in detail based on recent advances. Key issues for each topic, followed with recent research on theory and method, are then classified and the industrialization developments of CRN testbeds based on TD-LTE cellular system and standards are briefly presented. Finally, conclusions are reached on the perspectives and directions of future development.cognitive radio networks, network architecture, cognitive ability, spectrum sensing, intelligent decision and dynamic spectrum allocation, end-to-end performance Driven by the requirements of ubiquitous wireless access and personalized wireless applications [1], worldwide, numerous wireless technologies are invading our lives, such as evolutionary telecommunication technologies, wideband wireless access and short distance wireless technologies. Furthermore, the concept of the internet of things (IoT) has become widespread based on the development of wireless sensor networks. With the explosive development of wireless technologies, several challenges must be addressed. The electromagnetic spectrum, whose use is licensed and managed by government, has been scarce for allocation to ubiquitous wireless applications. However, contrary to the physical scarcity of the available spectrum, the report published by the federal communication commission (FCC) shows that over 60 % of the licensed spectrum below 6 GHz remains underused [2,3]. The measurement results in Figure 1 taken in Beijing over a one month period, also indicate low spectrum use consistent with the results released by the FCC. Therefore, improvement of spectrum efficiency is the first challenge to be examined. On the other hand, the end-to-end performance of wireless networks is considered to be the performance indicator for ubiquitous and personalized wireless applications [4], such as end-to-end throughput, end-to-end delay and routing scheme, which take into account all network elements in a data transmission flow across different layers for the global optimization from the network aspect. Because the property of heterogeneity causes low radio resource use and mutual interference among heterogeneous networks, the other big challenge is that heterogeneous network convergence is needed to improve the end-to-end performance of wireless networks.Cognitive radio (CR), proposed by Mitola in 1999 [5,6], is considered a feasible solution for improving spectrum efficiency. Furthermore, a cognitive radio network (CRN), which is defined as a wireless network with the capabilities

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A framework for R.F. spectrum measurements and analysis

Cited by 33 publications

References 2 publications

Advances in cognitive radio networks: A survey

Advances in cognitive radio networks: A survey

Parametric Adaptive Spectrum Sensing Framework for Dynamic Spectrum Access Networks

Intelligent and efficient development of wireless networks: A review of cognitive radio networks

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