Mustafa Namdar

Dispersed chirp-z transform-based spectrum sensing and utilisation in cognitive radio networks

The authors propose novel spectrum sensing and utilisation schemes for cognitive radio networks using the chirp-z transform. To improve the spectral efficiency, a dispersed chirp-z transform is introduced with the energy detection method. The dispersed chirp-z transform enables one to analyse the dispersed frequency spectrum of any frequency range of interest. The analysis is first focused on the sensing part, including the derivations of closed-form expressions for the optimal detection thresholds minimising the total error rate over additive white Gaussian noise (AWGN), Rayleigh, Rician and log-normally distributed fading channels. Then, the performance analysis of the proposed system is investigated for efficient spectrum utilisation over AWGN and fading channels by presenting the receiver operating characteristics. Conventional and segmented chirp-z transform-based spectrum utilisation techniques are also introduced for performance comparison purposes. Finally, the theoretical framework and the optimal threshold derivations through simulations are verified. The analyses reveal that the proposed schemes have a considerable potential to improve the non-cooperative spectrum sensing and utilisation performance.

Partial spectrum utilization for energy detection in cognitive radio networks

This paper proposes the use of chirp-z transform (CZT) in spectrum sensing to achieve higher frequency resolution in spectrum monitoring. The CZT method can efficiently utilize the dispersed frequency spectrum of any desired band of interest. The performance of the proposed system over additive white Gaussian noise (AWGN) and Rayleigh channels is analyzed and presented through ROC curves. In order to maximize the total error rate performance of the proposed system, the optimal detection threshold expressions are derived in the case of AWGN and Rayleigh faded channels. Afterwards, the optimal detection threshold expressions are validated by simulation and numerical results.

Optimal Detection Thresholds in Spectrum Sensing with Receiver Diversity

We investigate the performance of receiver diversity techniques by considering energy detector based optimal spectrum sensing in cognitive radio networks over Rayleigh fading channel for both non-cooperative and cooperative communication systems. The analysis is first focused on the non-cooperative spectrum sensing part, including the analyses of selection combining (SC), equal gain combining (EGC), and maximal ratio combining (MRC) receiver diversity systems. We derive exact closed-form expressions for the optimal detection thresholds for each diversity scheme. By using these expressions, we present their detection performance compared to the no-diversity case. Then in the second part of this paper, the performance analysis of the proposed system is investigated for amplify-and-forward relaying spectrum sensing with SC, EGC, and MRC diversity techniques in Rayleigh fading channels. Particularly, average detection probability of end-to-end signal-to-noise ratio for SC and EGC schemes and the exact closed-form expressions of the optimal detection threshold for SC, EGC, and MRC schemes are derived. We also present detection performance for the cooperative system compared to the non-cooperative one. The analyses are validated by simulated receiver operating characteristic curves.

Chirp Z transform based spectrum sensing via energy detection

In this study, the performance analysis of Fast Fourier Transform and Chirp Z transform based OFDM systems for cognitive radio networks with energy detector model for the spectrum sensing method is realized. Here, energy detection model for noncooperative spectrum sensing is investigated. On the other hand, the analysis is implemented by segmented Chirp z transform. In this study Chirp z transform based spectrum sensing is proposed for the increase of dispersed spectrum utilization and in this context firstly used in literature. Also with the system model, using inverse fast Fourier transform in transmitter and Chirp z transform in receiver rather than fast Fourier transform, the computational complexity and the processing time are reduced, and performance increase is observed for high signal to noise ratio values.

Spectrum sensing for cognitive radio with selection combining receiver antenna diversity

In this study the performance analysis of energy detector method for the spectrum sensing model in cognitive radio networks over Rayleigh fading channel with selection combining of the receiver diversity technique is examined. Here, energy detector model for non-cooperative spectrum sensing is investigated in which Chirp-z transform is used. The Chirp-z transform is proposed as an efficient algorithm to increase the dispersed frequency spectrum utilization, provides a flexibility to work only on the frequency spectrum of interest. The general closed form mathematical equation of the optimal detection threshold for selection combining receiver diversity technique is derived over Rayleigh fading channel. The performance analysis of the proposed system model is investigated with the optimal detection threshold value and presented through ROC curve for different SNR values. The achieved results validate the spectrum sensing performance increase in selection combining of the receiver antenna diversity technique, compared to the no diversity case.

Performance Analysis of the Differential Evolution and Particle Swarm Optimization Algorithms in Cooperative Wireless Communications

In this study, we evaluate the performance of differential evolution (DE) and particle swarm optimization (PSO) algorithms in free-space optical (FSO) and mobile radio communications systems. In particular, we obtain the optimal transmission distances for multiple-relay nodes in FSO communication systems and optimal relay locations in mobile radio communications systems for the cooperative-diversity networks, using both algorithms. We investigate the performance comparison of DE and PSO algorithms for the parallel decode-and-forward (DF) relaying. Then, we analyze the cost functions. Furthermore, we present the execution time and the stability of the DE and PSO algorithms.

Outage and BER performances of indoor relay-assisted hybrid RF/VLC systems

In this study, the authors analyse the outage performance of the indoor relay-assisted hybrid radio frequency (RF)/visible light communication (VLC) systems. They derive closed-form expressions for the outage probability of the end-to-end signal-to-noise ratio. Then they obtain the optimal approximation parameter with optimising the outage probability using the differential evolution algorithm. Moreover, they analysed the average bit error rate (BER) performance of the hybrid RF/optical system using pulse position modulation method while assuming the timing error in synchronisation. Finally, they present some numerical results utilising the newly derived exact closed-form expressions.

Selective sampling and otsu algorithm based spectrum sensing in cognitive radio networks

In this study, the performance analysis of the spectrum sensing in cognitive radio networks is investigated with the energy detector method over Rician fading channels with the selective sampling and Otsu algorithm. Here, a new method based on noise reduction using the wavelet transform is proposed. Performance analysis of the proposed system model over Rician fading channels is presented by receiver operating characteristic curves for different signal to noise ratio values. The results show that the spectrum sensing performance increases when the selective sampling and Otsu algorithm are used at the receiver.

Optimum Wavelet Transform-Based ECG Compressionand Dissimilarity Measureson Noise Performance Analysis

In this study, an optimum wavelet transform-based ECG compression technique is proposed and its noise performance analysis is investigated. The major addressed issue is guaranteeing an error limit as small as possible measured by the percent root mean square difference (PRD) for the reconstructed ECG signal at every segment while keeping the compression ratio (CR) as large as possible with reasonable implementation complexity. For this purpose, an optimum wavelet transform-based compression algorithm is developed. Noise effects on the normal and the arrhythmia signal is analyzed based on the compression ratio (CR) and the reconstruction distortion. The similarity measurement is used as a criterion to analyze how much the original signal is similar or closer to the reconstructed one. Two numerical metrics PRD and CR are used as the major performance evaluation parameters to analyze the results of the implemented method quantitatively. Using the developed technique, different types of orthonormal wavelets are compared.