Signal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machines

Cognitive radio based network enables opportunistic dynamic spectrum access by sensing, adopting and utilizing the unused portion of licensed spectrum bands. Cognitive radio is intelligent enough to adapt the communication parameters of the unused licensed spectrum. Spectrum sensing is one of the most important tasks of the cognitive radio cycle. In this paper, the auto-correlation function kernel based Support Vector Machine (SVM) classifier along with Welch's Periodogram detector is successfully implemented for the detection of four QPSK (Quadrature Phase Shift Keying) based signals propagating through an AWGN (Additive White Gaussian Noise) channel. It is shown that the combination of statistical signal processing and machine learning concepts improve the spectrum sensing process and spectrum sensing is possible even at low Signal to Noise Ratio (SNR) values up to -50 dB

TSEP: Threshold-sensitive Stable Election Protocol for WSNs

Wireless Sensor Networks (WSNs) are expected to find wide applicability and increasing deployment in near future. In this paper, we propose a new protocol, Threshold Sensitive Stable Election Protocol (TSEP), which is reactive protocol using three levels of heterogeneity. Reactive networks, as opposed to proactive networks, respond immediately to changes in relevant parameters of interest. We evaluate performance of our protocol for a simple temperature sensing application and compare results of protocol with some other protocols LEACH, DEEC, SEP, ESEP and TEEN. And from simulation results it is observed that protocol outperforms concerning life time of sensing nodes used.Comment: 10th IEEE International Conference on Frontiers of Information Technology (FIT 12), 201

FinTech, blockchain and Islamic finance : an extensive literature review

Purpose: The paper aims to review the academic research work done in the area of Islamic financial technology. The Islamic FinTech area has been classified into three broad categories of the Islamic FinTech, Islamic Financial technology opportunities and challenges, Cryptocurrency/Blockchain sharia compliance and law/regulation. Finally, the study identifies and highlights the opportunities and challenges that Islamic Financial institutions can learn from the conventional FinTech organization across the world. Approach/Methodology/Design: The study collected 133 research studies (50 from Social Science Research Network (SSRN), 30 from Research gate, 33 from Google Scholar and 20 from other sources) in the area of Islamic Financial Technology. The study presents the systematic review of the above studies. Findings: The study classifies the Islamic FinTech into three broad categories namely, Islamic FinTech opportunities and challenges, Cryptocurrency/Blockchain sharia compliance and law/regulation. The study identifies that the sharia compliance related to the cryptocurrency/Blockchain is the biggest challenge which Islamic FinTech organizations are facing. During our review we also find that Islamic FinTech organizations are to be considered as partners by the Islamic Financial Institutions (IFI’s) than the competitors. If Islamic Financial institutions want to increase efficiency, transparency and customer satisfaction they have to adopt FinTech and become partners with the FinTech companies. Practical Implications: The study will contribute positively to the understanding of Islamic Fintech for the academia, industry, regulators, investors and other FinTech users. Originality/Value: The study believes to contribute positively to understanding of Fintech based technology like cryptocurrency/Blockchain from sharia perspective.peer-reviewe

Transmission Delay of Multi-hop Heterogeneous Networks for Medical Applications

Nowadays, with increase in ageing population, Health care market keeps growing. There is a need for monitoring of Health issues. Body Area Network consists of wireless sensors attached on or inside human body for monitoring vital Health related problems e.g, Electro Cardiogram (ECG), ElectroEncephalogram (EEG), ElectronyStagmography(ENG) etc. Data is recorded by sensors and is sent towards Health care center. Due to life threatening situations, timely sending of data is essential. For data to reach Health care center, there must be a proper way of sending data through reliable connection and with minimum delay. In this paper transmission delay of different paths, through which data is sent from sensor to Health care center over heterogeneous multi-hop wireless channel is analyzed. Data of medical related diseases is sent through three different paths. In all three paths, data from sensors first reaches ZigBee, which is the common link in all three paths. After ZigBee there are three available networks, through which data is sent. Wireless Local Area Network (WLAN), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunication System (UMTS) are connected with ZigBee. Each network (WLAN, WiMAX, UMTS) is setup according to environmental conditions, suitability of device and availability of structure for that device. Data from these networks is sent to IP-Cloud, which is further connected to Health care center. Main aim of this paper is to calculate delay of each link in each path over multihop wireless channel.Comment: BioSPAN with 7th IEEE International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA 2012), Victoria, Canada, 201