A new mathematical analysis of the probability of detection in cognitive radio over fading channels

Altrad, Omar; Muhaidat, Sami

doi:10.1186/1687-1499-2013-159

Cited by 32 publications

(18 citation statements)

References 20 publications

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“…For a large N , using the central limit theorem, the distribution of the decision variable Y will be central chi‐square

χ_{N}^{2}

under H 0 and noncentral chi‐square

{\tilde{χ}}_{N}^{2}

with N degrees of freedom under H 1 ; the distribution can be expressed as

Y \sim ({,, \begin{array}{l} χ_{N}^{2} H_{0} \\ {\tilde{χ}}_{N}^{2} H_{1} \end{array}),

and its probability density function (PDF) is written as

f_{Y} ((),, y) = ({,, \begin{array}{l} \frac{1}{σ^{N} 2^{\frac{N}{2}} normalΓ ((),, \frac{N}{2})} y^{((),, \frac{N}{2}) - 1} exp ((),, \frac{- y}{2 σ^{2}}) H_{0} \\ \frac{1}{2 σ^{2}} {(\frac{y}{h^{2} δ})}^{((),, N - 2) true/ 4} exp ([],, \frac{- (y + h^{2} δ)}{2 σ^{2}}) \times I_{\frac{N}{2} - 1} ((),, \frac{\sqrt{h^{2} italicδy}}{σ^{2}}) H_{1} \end{array}),

where

δ = \sum_{n = 1}^{N} μ_{l ((),, n)}^{2} = \sum_{n = 1}^{N} {(E (l (n)))}^{2}

, μ l ( n ) is the mean of the n th samples of jamming signal under H 1 .

σ^{2} = \sum_{n = 1}^{N} E ((),, (|)

…”

Section: Spectrum Sensing Performance Under Awgn Channelmentioning

confidence: 99%

Transmit‐sense‐receive–based cognitive antijamming for airborne ad hoc networks

Qian

Liu

2017

Int J Communication

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In this paper, a transmit-sense-receive mode-based simultaneous transmit-andreceive cognitive antijamming (SCAJ) strategy is proposed to enhance spectrally efficient of airborne networks in congested electromagnetic spectrum environment.We explore the performance of spectrum sensing based on energy detection in SCAJ system. The tight close form expressions of jamming detection and false-alarm probability are derived under different channels, the throughput of individual SCAJ system is analyzed, and SCAJ transceiver-based airborne ad hoc network capacity is presented for air platform equipping with digital beamforming antennas. Simulation results show that proposed SCAJ technology can improve the antijamming capability and airborne ad hoc network capacity compared to the half-duplex cognitive antijamming scheme. It is an effective approach to solve the problem of designing airborne networks arise from the limited availability of spectrum and the desire to provide much higher data rates. without central coordination among the radios. However, it still has no opportunity to exploit the spectrum hole to transmit signal, so as to prevent EM interference from the internal and external RF equipment. Recently, cognitive radio (CR)-based antijamming (CAJ) communication technology was put forward. It can implement high efficient information transmission using available spectrum holes by spectrum sensing; therefore, the ATN performance can be greatly improved in a congested EM spectrum scenario.Cognitive radio has arisen commercially over the last decade, enabling dynamic spectrum access (DSA) scheme to share open spectrum. 1 The goal of DSA is to relieve the lack of EM spectrum, which is the scarcest resource to implement wireless communication. Most involved the study of CR has considered that secondary (unlicensed) users (SU) use the spectrum holes of primary (licensed) users (PU) without interfering primary communication and developed DSA mechanism to opportunistically access the licensed frequency channel. Consequently, spectrum sharing between PU and SU has been achieved, and spectral efficiency of wireless network is to be maximized.In this paper, the use of CR for antijamming wireless communication operating in ATN is conceived, where malicious jammers exist in addition to scarce EM spectrum. Because of the limitation of the congested EM spectrum resource among tactical radios, it is challenging to extend cognitive antijamming to airborne ad hoc networks operating in environments where electronic attacks and little infrastructure exist. Therefore, it is imperative that future tactical radios can dynamically to use the spectrum resources efficiently.Some researchers have carried on the beneficial exploration CAJ-based military communication technology. In literature, 2-4 Li analyze theoretically the jamming capacity of cognitive jammer and the antijamming performance of cognitive wireless network. A high frequency radio prototype system based on dynamic spectrum antijamming is reported in Zhu et al. 5 The competing ...

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“…For a large N , using the central limit theorem, the distribution of the decision variable Y will be central chi‐square

χ_{N}^{2}

under H 0 and noncentral chi‐square

{\tilde{χ}}_{N}^{2}

with N degrees of freedom under H 1 ; the distribution can be expressed as

Y \sim ({,, \begin{array}{l} χ_{N}^{2} H_{0} \\ {\tilde{χ}}_{N}^{2} H_{1} \end{array}),

and its probability density function (PDF) is written as

f_{Y} ((),, y) = ({,, \begin{array}{l} \frac{1}{σ^{N} 2^{\frac{N}{2}} normalΓ ((),, \frac{N}{2})} y^{((),, \frac{N}{2}) - 1} exp ((),, \frac{- y}{2 σ^{2}}) H_{0} \\ \frac{1}{2 σ^{2}} {(\frac{y}{h^{2} δ})}^{((),, N - 2) true/ 4} exp ([],, \frac{- (y + h^{2} δ)}{2 σ^{2}}) \times I_{\frac{N}{2} - 1} ((),, \frac{\sqrt{h^{2} italicδy}}{σ^{2}}) H_{1} \end{array}),

where

δ = \sum_{n = 1}^{N} μ_{l ((),, n)}^{2} = \sum_{n = 1}^{N} {(E (l (n)))}^{2}

, μ l ( n ) is the mean of the n th samples of jamming signal under H 1 .

σ^{2} = \sum_{n = 1}^{N} E ((),, (|)

…”

Section: Spectrum Sensing Performance Under Awgn Channelmentioning

confidence: 99%

Transmit‐sense‐receive–based cognitive antijamming for airborne ad hoc networks

Qian

Liu

2017

Int J Communication

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show abstract

“…The preamble-detection probability depends on the detection threshold setting. In LTE systems, the detection threshold is determined by the target false-alarm probability [15,16]. Here, the false-alarm probability is defined as the probability that the receiver detects a preamble transmission when the received signal is purely noise.…”

Section: Preamble Detectionmentioning

confidence: 99%

“…Here, the detection probability is defined as the probability that the receiver correctly detects the RAP transmitted from the MS. When the proposed RAP is received in mm-wave cellular systems with directional beams, the false-alarm probability in an AWGN channel is given by [15,16]…”

Section: Preamble Detectionmentioning

confidence: 99%

Random-Access Technique for Self-Organization of 5G Millimeter-Wave Cellular Communications

Arana

Han

Cho

2016

Mobile Information Systems

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The random-access (RA) technique is a key procedure in cellular networks and self-organizing networks (SONs), but the overall processing time of this technique in millimeter-wave (mm-wave) cellular systems with directional beams is very long because RA preambles (RAPs) should be transmitted in all directions of Tx and Rx beams. In this paper, two different types of preambles (RAP-1 and RAP-2) are proposed to reduce the processing time in the RA stage. After analyzing the correlation property, false-alarm probability, and detection probability of the proposed RAPs, we perform simulations to show that the RAP-2 is suitable for RA in mm-wave cellular systems with directional beams because of the smaller processing time and high detection probability in multiuser environments.

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“…The performance of energy detection (ED)-based spectrum sensing has been investigated for a variety of fading channels [6]. However, under "hyper-Rayleigh" fading conditions the performance of spectrum sensing is expected to be severely degraded.…”

Section: Introductionmentioning

confidence: 99%

Threshold Optimization for Energy Detection-Based Spectrum Sensing Over Hyper-Rayleigh Fading Channels

2015

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Spectrum sensing is a key function of cognitive radio systems. Sensing performance is determined by three main factors including the wireless channel between the primary system and the cognitive radio nodes, the detection threshold, and the sensing time. In this letter a closed-form expression for the average probability of detection for energy detection based spectrum sensing over two-wave with diffuse power fading channels is derived. This expression is then used to optimize the detection threshold for cognitive radio nodes, which operate in confined structures that exhibit worse than Rayleigh fading conditions. Such fading conditions can represent a behavioral model of cognitive machine-to-machine systems deployed in enclosed structures such as in-vehicular environments.

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A new mathematical analysis of the probability of detection in cognitive radio over fading channels

Cited by 32 publications

References 20 publications

Transmit‐sense‐receive–based cognitive antijamming for airborne ad hoc networks

Transmit‐sense‐receive–based cognitive antijamming for airborne ad hoc networks

Random-Access Technique for Self-Organization of 5G Millimeter-Wave Cellular Communications

Threshold Optimization for Energy Detection-Based Spectrum Sensing Over Hyper-Rayleigh Fading Channels

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