35,546 research outputs found
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
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
Parallel detrended fluctuation analysis for fast event detection on massive PMU data
("(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")Phasor measurement units (PMUs) are being rapidly deployed in power grids due to their high sampling rates and synchronized measurements. The devices high data reporting rates present major computational challenges in the requirement to process potentially massive volumes of data, in addition to new issues surrounding data storage. Fast algorithms capable of processing massive volumes of data are now required in the field of power systems. This paper presents a novel parallel detrended fluctuation analysis (PDFA) approach for fast event detection on massive volumes of PMU data, taking advantage of a cluster computing platform. The PDFA algorithm is evaluated using data from installed PMUs on the transmission system of Great Britain from the aspects of speedup, scalability, and accuracy. The speedup of the PDFA in computation is initially analyzed through Amdahl's Law. A revision to the law is then proposed, suggesting enhancements to its capability to analyze the performance gain in computation when parallelizing data intensive applications in a cluster computing environment
Simulation Analysis of Medium Access Techniques
This paper presents comparison of Access Techniques used in Medium Access
Control (MAC) protocol for Wireless Body Area Networks (WBANs). Comparison is
performed between Time Division Multiple Access (TDMA), Frequency Division
Multiple Access (FDMA), Carrier Sense Multiple Access with Collision Avoidance
(CSMA/CA), Pure ALOHA and Slotted ALOHA (S-ALOHA). Performance metrics used for
comparison are throughput (T), delay (D) and offered load (G). The main goal
for comparison is to show which technique gives highest Throughput and lowest
Delay with increase in Load. Energy efficiency is major issue in WBAN that is
why there is need to know which technique performs best for energy conservation
and also gives minimum delay.Comment: NGWMN with 7th IEEE International Conference on Broadband and
Wireless Computing, Com- munication and Applications (BWCCA 2012), Victoria,
Canada, 201
Parallel detrended fluctuation analysis for fast event detection on massive PMU data
("(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")Phasor measurement units (PMUs) are being rapidly deployed in power grids due to their high sampling rates and synchronized measurements. The devices high data reporting rates present major computational challenges in the requirement to process potentially massive volumes of data, in addition to new issues surrounding data storage. Fast algorithms capable of processing massive volumes of data are now required in the field of power systems. This paper presents a novel parallel detrended fluctuation analysis (PDFA) approach for fast event detection on massive volumes of PMU data, taking advantage of a cluster computing platform. The PDFA algorithm is evaluated using data from installed PMUs on the transmission system of Great Britain from the aspects of speedup, scalability, and accuracy. The speedup of the PDFA in computation is initially analyzed through Amdahl's Law. A revision to the law is then proposed, suggesting enhancements to its capability to analyze the performance gain in computation when parallelizing data intensive applications in a cluster computing environment
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