Pilot symbol assisted channel estimation for OFDM-based cognitive radio systems

Manasseh, Emmanuel; Ohno, Shûichi; Nakamoto, Masayoshi

doi:10.1186/1687-6180-2013-51

Cited by 15 publications

(3 citation statements)

References 23 publications

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“…In our investigation, we seek a reduced system complexity and a reliable detection accuracy in the edge detection and the PU detection phases. The channel estimate at each subband can be provided by the pilot-insertion method after being identified [33].…”

Section: The Proposed Wideband Spectrum Sensing Approachmentioning

confidence: 99%

A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

Moawad

Yao²,

Mansour

et al. 2020

IEEE Open J. Commun. Soc.

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Multiband spectrum access plays an essential role in cognitive radio systems so as to increase the network's throughput through wideband spectrum sensing. It includes identifying the number of subbands comprising a wide spectrum by edge detection, and also examining their occupancy through primary user detection techniques. Despite the offered accuracy of the wavelet-based approaches, their complexity becomes a drawback. Remarkably, the features revealing property of cepstral analysis and its implementation simplicity make it a suitable candidate for signal detection. Motivated by these reasons, this paper presents a wideband spectrum sensing approach based on cepstral analysis. First, we propose the differential log spectral density algorithm for the edge detection phase in order to detect the spectral boundaries within the wideband of interest. Also, we present a mathematical framework of the proposed algorithm and an expression for the detection threshold of the proposed detector is derived. The simulation results have showed a superior performance of the edge detection algorithm to different wavelet-based techniques at low-to-medium noise power. Used in conjunction with denoising, the proposed edge detector shows good detection results at low signal-to-noise ratio. For the primary user detection phase, we introduce the improved passband autocepstrum detector to tackle the misdetection problem of noise-like signals and it outperforms different state-of-the-art techniques. Finally, the uncertainty problem of the subbands center frequencies is addressed and the baseband autocepstrum detector is introduced as a potential solution to improve signal detection in frequency selective fading.

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Section: The Proposed Wideband Spectrum Sensing Approachmentioning

confidence: 99%

A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

Moawad

Yao²,

Mansour

et al. 2020

IEEE Open J. Commun. Soc.

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show abstract

“…A pilot design method for OFDM‐based CR was presented to minimize mean squared errors (MSE) of the LS channel estimation . A pilot design method was presented as an optimization problem that minimizes the MSE of the LS channel estimate of the frequency‐selective channel . In Manasseh et al a pilot design method using convex optimization was proposed to minimize the MSE.…”

Section: Related Workmentioning

confidence: 99%

“…It is important to compare between the sub-optimal and optimal estimation algorithms in terms of computational complexity, which is calculated in terms of the number of floating-point operations (flops) required per iteration. The initial estimation of the EM algorithm is given by Equation (18). In this equation, a p is (M × L), r is (M × 1), h is (L × 1), and M = ((M p +M s )(N+v)+L − 1).…”

Section: Computational Complexity Calculationmentioning

confidence: 99%

Effects of imperfect channel sensing and estimation on the performance of cognitive radio systems

El-Hamid

Hassan

Zekry

et al. 2019

Int J Communication

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Summary In realistic scenarios of cognitive radio (CR) systems, imperfect channel sensing may occur due to false alarms and miss detections. Channel estimation between the secondary user transmitter and another secondary user receiver is another challenge in CR systems, especially for frequency‐selective fading channels. In this context, this paper presents a study of the effects of imperfect channel sensing and channel estimation on the performance of CR systems. In particular, different methods of channel estimation are analyzed under channel sensing imperfections. Initially, a CR system model with channel sensing errors is described. Then, the expectation maximization (EM) algorithm is implemented in order to learn the channel fading coefficients. By exploiting the pilot symbols and the detected symbols at the secondary user receiver, we can estimate the channel coefficients. We further compare the proposed EM estimation algorithm with different estimation algorithms such as the least squares (LS) and linear minimum mean square error (LMMSE). The expressions of channel estimates and mean squared errors (MSE) are determined, and their dependencies on channel sensing uncertainty are investigated. Finally, to reduce the complexity of EM algorithm, a sub‐optimal algorithm is also proposed. The obtained results show that the proposed sub‐optimal algorithm provides a comparable bit error rate (BER) performance with that of the optimal one yet with less computational complexity.

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A Hybrid of BFO and MCS Algorithms for Channel Estimation of Cognitive Radio System

Manjith¹

2015

Arab J Sci Eng

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Pilot symbol assisted channel estimation for OFDM-based cognitive radio systems

Cited by 15 publications

References 23 publications

A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

A Wideband Spectrum Sensing Approach for Cognitive Radios Based on Cepstral Analysis

Effects of imperfect channel sensing and estimation on the performance of cognitive radio systems

A Hybrid of BFO and MCS Algorithms for Channel Estimation of Cognitive Radio System

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