A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Sahu, O. P.
- A New Approach for Self Localization of Wireless Sensor Network
Authors
1 Department of Electronics & Communication Engineering, NIT, Kurukshetra (Haryana), IN
Source
Indian Journal of Science and Technology, Vol 2, No 11 (2009), Pagination: 1-4Abstract
This paper presents a new approach for self localization of wireless sensors. Various algorithms have been proposed for localization of wireless sensor networks and are based on computational measurements. The suggested approaches estimate the location of sensors implemented with concepts of functionalities and future scopes. The proposed algorithm relies on a range measurement technique between a pair of nodes and their arrangement to cover maximum area surrounding the main node. Hence, a confident position of sensor is established. The evident advantage of the algorithm is that it requires less number of sensor nodes and saves the constructional cost of a wireless sensor network.Keywords
Localization, Sensors, Node, Wireless Sensor Networks (WSN)References
- Adam Dunkels (2007) Lightweight layered communication stack for sensor networks. Proc. Eur. Conf. on Wireless Sensor Networks (EWSN), Netherlands. Vol. 91, No 8 pp. 1247- 1256.
- Biswas P and Ye Y (2006) A distributed method for solving semi definite programs arising from adhoc wireless sensor network localization, in Multiscale Optimization Methods and applications J. Nonconvex Optim. Appl. Vol. 82, pp. 69-84.
- Ceveher V, Chellapa R and McClellan J (2007) Gaussian approximations for energy-based detection and localization in sensor networks. IEEE Statistical Signal Processing Workshop. Vol.14, pp. 40
- Chen Y, Francisco J, Trappe W and Martin RP (2006) A practical approach to landmark deployment for indoor localization. Proc. 3rd Annual IEEE Commun. Soc. Conf. on Sensor, Mesh & Ad Hoc Commun. & Networks (SECON).
- Elnahrawy E, Li X and Martin RP (2009) The limits of localization using signal strength: a comparative study. Proc. Ist IEEE Intl. Conf. on Sensor & Adhoc Commun. & Networks (SECON).
- Jianfeng Qu, Yi Chai and Simon X. Yang (2009) A real-time de-noising algorithm for e-noses in a wireless sensor network. J. Sensors. 9(2), 895-908.
- Jin Z, Jian Ping, Yu Si, Wang Ya, Ping Z and Guang L (2009) Survey on position based routing algorithms in wireless sensor networks. J. Algorithms. 2, 158- 182.
- Joakim Eriksson, Adam Dunkels, Niclas Finne, Fredrik Österlind and Thiemo Voigt (2007) MSPSim an extensible simulator for msp430-equipped sensor boards. Proc. Eur. Conf. on Wireless Sensor Networks (EWSN), Poster/Demo session, Delft, Netherlands. Vol. 4373, pp. XIII, 358.
- Mao Chen Liu, Ching Liang Dai, Chih Hua Chan and Chyan Chyi Wu (2009) Manufacture of a polyaniline nanofiber ammonia sensor integrated with a readout Circuit using the CMOS-MEMS technique. J. Sensors. Vol.9 (2), pp. 869-880.
- Messer H and Thehybrid Cramer Rao (2006) lower bound Practice to theory. J. Sensor Array & Multi Channel Processing. Vol.89, pp. 304–307.
- Sotiris Nikoletseas and Paul G. Spirakis (2009) Review: probabilistic distributed algorithms for energy efficient routing and tracking. J. Wireless Sensor Networks Algorithms. Vol. 2(1), pp. 121-157.
- Srinivasan A and Wu J (2007) A survey on secure localization in wireless sensor networks. Wireless and Mobile Communications, CRC Press/Taylor & Francis Group, Boca Raton/London.
- Venkatesh S (2007) The design and modelling of ultra-wideband position-location networks. Ph.D. Dissertation, Virginia Polytechnic Institute & State Univ. (Virginia Tech).
- Venkatesh S and Michael Buehrer R (2007) Multiple access insights from bounds on sensor localization. Mobile and Portable Radio Research Group (MPRG), Virginia Tech, Blacksburg.
- Wan Z, Zhang J and Zhu H (2008) On energy-efficient and low latency media access control protocol for wireless sensor networks. Proc. IEEE WCNC. Vol.5, pp. 148-164.
- Software Defined Radio (SDR) 4-bit QAM Modem Using Lab-VIEW for Gaussian Channel
Authors
1 Communication Engineering Department,University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, IN
2 Communication Engineering Department, NIT, Kurukshetra, IN
3 Electronics and Communication Engineering Department, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, IN
4 Electronics Science Department, Kurukshetra University, Kurukshetra, IN
Source
Wireless Communication, Vol 3, No 4 (2011), Pagination: 237-245Abstract
A Software Defined Radio (SDR) is a reconfigurable radio, in which channel modulation waveforms are defined in software. In this paper Software Defined Radio (SDR) 4-bit QAM Modem for Gaussian Channel is implemented using abVIEW software. LabVIEW is a graphical development environment with built-in functionality for simulation, data acquisition, instrument control, measurement analysis, and data presentation. The aim of this paper is to simulate SDR for next generation wireless communication having Gaussian channel and Adaptive Filter is used to remove Gaussian noise present in received signal and minimize the effect of Intersymbol Interference. It is obvious from the Simulation results that SDR is suitable for Gaussian channel giving Optimum Performance.
Keywords
Software Defined Radio, QAM Modem, Gaussian Channel, Adaptive Filter, ISI, LabVIEW Graphical Programming.- A Review on Channel Equalization for Software Defined Radio
Authors
1 Electronics and Communication Engineering Department, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, IN
2 Electronics and Communication Engineering Department, NIT, Kurukshetra, IN
3 Electronics and Communication Engineering Department, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, IN
4 Electronics Science Department, Kurukshetra University, Kurukshetra, IN
Source
Wireless Communication, Vol 3, No 3 (2011), Pagination: 206-213Abstract
We provide a brief overview over the development of software-defined radio system and channel equalization techniques. Software Defined Radio (SDR) is an all new technology being developed in the 21st century. The primary goal of Software Defined Radio is to replace as many analog components and hardwired digital VLSI devices of the transceiver as possible with programmable devices. One of the major practical problems in digital communication systems is channel distortion which causes errors due to Intersymbol Interference (ISI). In order to restore the transmitted sequence and given the observed sequence at the channel output which is accomplished by equalizers. In this paper Nonlinear equalizers, Adaptive equalizers, Fuzzy equalizers, Neural equalizers are underlined. We discuss that which equalizer is best out of these and the reasons for this also proposed.Keywords
Adaptive Equalizers, Fuzzy Equalizers, ISI, Neural Equalizers, Nonlinear Equalizers, SDR.- Vibration Analysis of a V-Groove Edged Cracked Cantilever Beam
Authors
1 Department of Mechanical Engineering, Chouksey Engineering College, Bilaspur, IN