Efficient GLRT/DOA spectrum sensing algorithm for single primary user detection in cognitive radio systems

Fouda, Hager Shawky; Hussein, Amr H.; Attia, Mahmoud A.

doi:10.1016/j.aeue.2018.03.012

Cited by 17 publications

(10 citation statements)

References 26 publications

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“…In this section, the proposed array beamforming is applied to GD SS algorithm introduced in [10]. The block diagram of the proposed BF/GD algorithm is shown in Fig.…”

Section: Proposed Beamforming Based Gd Algorithm (Bf/gd)mentioning

confidence: 99%

“…3. Using the same narrow band signal model introduced in [10], s (n) = A m e j2πnf 0 +ϕ where A m and ϕ are the signal amplitude and phase, respectively. f 0 ≤ 0.5 is the normalized frequency.…”

Section: Proposed Beamforming Based Gd Algorithm (Bf/gd)mentioning

confidence: 99%

“…In this case, the temporary unused spectrum holes will be used efficiently by the SU until the PU returns to use his licensed frequency band [3]. Effective research efforts have been exerted in this area and many SS techniques have been introduced for efficient utilization of the limited frequency resources [4]- [10]. One of the most popular SS technologies is the energy detector (ED), which is characterized by its low complexity and the lack of prior knowledge of the PU signal parameters and channel characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…In [9], two high-performance volumebased detection algorithms denoted as VD1 and VD2 are introduced where their test statistics are also based on the eigenvalue decomposition of the covariance matrix. In [10], a Generalized Likelihood Ratio Test/ Direction of Arrival estimation (GD) based SS algorithm was introduced. In this algorithm, in order to take the advantage of the receiving ULA gain, delay and sum beamforming was performed to combine the received PU signal versions constructively considering the random nature of the noise signals at each antenna element.…”

Section: Introductionmentioning

confidence: 99%

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A Highly Efficient Spectrum Sensing Approach Based on Antenna Arrays Beamforming

et al. 2020

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In cognitive radio (CR), the sensitivity of the spectrum sensing (SS) algorithms depends mainly on several factors such as the receiver sensitivity, the antenna gain, the antenna efficiency and the SS algorithm itself. Researchers depend mainly on a single antenna element and sometimes on a uniform linear antenna (ULA) arrays to increase the system sensitivity. But actually the ULA suffers from the large side lobe level which in turn reduces the antenna gain. Furthermore, the separation between elements in the ULA is almost chosen to be half wavelength at the operating frequency which results in a dense array of close elements. If this separation increases slightly in order to reduce the mutual coupling between elements, the side lobes will increase and thus the realized gain is reduced more and more and as a consequence, the SNR will be reduced also which has a direct effect on the sensitivity of the system. In this paper, a low complexity and highly efficient SS technique based on antenna arrays beamforming and the generalized likelihood ratio test (GLRT) denoted as BF/GD is introduced. The proposed beamforming approach allows the utilization of the limited number of ULA elements and their corresponding RF chains to synthesize the desired radiation patterns of larger size antenna arrays for maximum gain realization. The desired pattern is realized by optimizing the excitation coefficients and inter-element spacing of the array. Consequently, the enhancement in the realized array gain will lead to a direct increase in the received signal-to-noise ratio (SNR) which significantly improves the sensitivity and the SS capability of the CR receiver without the need for extra hardware. INDEX TERMS Beamforming (BF), cognitive radio (CR), spectrum sensing (SS), multiple antenna elements (MAE), uniform linear array (ULA), generalized likelihood ratio test (GLRT).

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“…In this section, the proposed array beamforming is applied to GD SS algorithm introduced in [10]. The block diagram of the proposed BF/GD algorithm is shown in Fig.…”

Section: Proposed Beamforming Based Gd Algorithm (Bf/gd)mentioning

confidence: 99%

Section: Proposed Beamforming Based Gd Algorithm (Bf/gd)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Highly Efficient Spectrum Sensing Approach Based on Antenna Arrays Beamforming

et al. 2020

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“…In CR networks, the secondary user (SU) (unlicensed user) should identify the white space of the considered spectrum, periodically monitor the activity of the primary user (PU) (licensed user), and share the spectrum in an intelligent way. The magnificent success of this unlicensed access paradigm in maximizing the spectral efficiency draws a great attention to the so-called spectrum sensing (SS) [6][7][8] that is considered as the core of any CR system. Numerous research efforts focusing on the primary signal detection are performed, however many challenges still exist.…”

Section: Introductionmentioning

confidence: 99%

A Novel T–Test Based Spectrum Sensing Technique for SIMO and MIMO Cognitive Radio Networks

et al. 2020

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Cognitive radio (CR) is perceived as an intelligent solution to the incompetence of spectrum utilization. The efficacy of any CR system depends on the accuracy of the spectrum sensing (SS) technology used. Therefore, the SS is considered as a substantial task of the CR systems. In this paper, the SS is handled by a different perspective as a goodness of fit hypothesis testing problem. Therefore, a T-Test based spectrum sensing (TTBSS) algorithm is proposed based on the statistical properties of the student's t-distribution. It does not require any prior knowledge of the primary user (PU) signal. It determines the PU absence/presence by calculating the dissimilarity between the two samples means of the received signal when the PU is present and when the PU is absent. Closed-form expressions for the probability of detection, probability of false alarm, and their associated thresholds are derived considering both single-input multi-output (SIMO) and multi-input multi-output (MIMO) systems configurations. The simulations revealed that the proposed algorithm is superior to the other state-of-the-art PU detection algorithms particularly at low signal-to-noise ratios (SNR) and few samples conditions. Moreover, the TTBSS addressed many problems that restrict the performance of the SS process such as noise uncertainty and interference. In addition, the numerical results are highly matched to the theoretical analyses.

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Machine learning based cluster formation in vehicular communication

et al. 2021

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Efficient GLRT/DOA spectrum sensing algorithm for single primary user detection in cognitive radio systems

Cited by 17 publications

References 26 publications

A Highly Efficient Spectrum Sensing Approach Based on Antenna Arrays Beamforming

A Highly Efficient Spectrum Sensing Approach Based on Antenna Arrays Beamforming

A Novel T–Test Based Spectrum Sensing Technique for SIMO and MIMO Cognitive Radio Networks

Machine learning based cluster formation in vehicular communication

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