Signal Strength based Communication in Wireless Sensor Networks (Sensor Network Estimation) Imran S. Ansari EE 242 Digital Communications and Coding (Fall.

Slides:



Advertisements
Similar presentations
Localization algorithms for wireless sensor networks M.Srbinovska, C.Gavrovski Ss.Cyril and Methodius University, Skopje Faculty of Electrical Engineering.
Advertisements

Using Cramer-Rao-Lower-Bound to Reduce Complexity of Localization in Wireless Sensor Networks Dominik Lieckfeldt, Dirk Timmermann Department of Computer.
Min Song 1, Yanxiao Zhao 1, Jun Wang 1, E. K. Park 2 1 Old Dominion University, USA 2 University of Missouri at Kansas City, USA IEEE ICC 2009 A High Throughput.
SELECT: Self-Learning Collision Avoidance for Wireless Networks Chun-Cheng Chen, Eunsoo, Seo, Hwangnam Kim, and Haiyun Luo Department of Computer Science,
A Novel Finger Assignment Algorithm for RAKE Receivers in CDMA Systems Mohamed Abou-Khousa Department of Electrical and Computer Engineering, Concordia.
The development & integration of a Real-Time X-Ray image transfer system over a wireless network Final Year Project Presentation Capt David Clarke.
Target Tracking Algorithm based on Minimal Contour in Wireless Sensor Networks Jaehoon Jeong, Taehyun Hwang, Tian He, and David Du Department of Computer.
Department of electrical and computer engineering An Equalization Technique for High Rate OFDM Systems Mehdi Basiri.
© 2005, it - instituto de telecomunicações. Todos os direitos reservados. Gerhard Maierbacher Scalable Coding Solutions for Wireless Sensor Networks IT.
Dynamic Localization Control for Mobile Sensor Networks S. Tilak, V. Kolar, N. Abu-Ghazaleh, K. Kang (Computer Science Department, SUNY Binghamton)
Do You See What I See (DYSWIS) Aditya Muthyala (am3551) School of Engineering and Applied Science Columbia University, Fall 2011.
On Tree-Based Convergecasting in Wireless Sensor Networks V. Annamalai, S. K. S. Gupta, L. Schwiebert IEEE 2003 Speaker : Chi-Chih Wu.
Versatile low power media access for wireless sensor networks Joseph PolastreJason HillDavid Culler Computer Science Department University of California,Berkeley.
1 Sensor Placement and Lifetime of Wireless Sensor Networks: Theory and Performance Analysis Ekta Jain and Qilian Liang, Department of Electrical Engineering,
Yanyan Yang, Yunhuai Liu, and Lionel M. Ni Department of Computer Science and Engineering, Hong Kong University of Science and Technology IEEE MASS 2009.
Energy-efficient Multiple Targets Tracking Using Target Kinematics in Wireless Sensor Networks Akond Ashfaque Ur Rahman, Mahmuda Naznin, Md. Atiqul Islam.
Power Consumption Measurement and Clock Synchronization on Low-Power Wireless Sensor Networks Author : Yu-Ping Chen, Quincy Wu 1.
ECE 4371, Fall, 2014 Introduction to Telecommunication Engineering/Telecommunication Laboratory Zhu Han Department of Electrical and Computer Engineering.
1 Secure Cooperative MIMO Communications Under Active Compromised Nodes Liang Hong, McKenzie McNeal III, Wei Chen College of Engineering, Technology, and.
3D Tomography using Efficient Wavefront Picking of Traveltimes Abdullah AlTheyab and G. T. Schuster King Abdullah University of Science and Technology.
Exposure In Wireless Ad-Hoc Sensor Networks Seapahn Meguerdichian Computer Science Department University of California, Los Angeles Farinaz Koushanfar.
Authors: Sheng-Po Kuo, Yu-Chee Tseng, Fang-Jing Wu, and Chun-Yu Lin
M-GEAR: Gateway-Based Energy-Aware Multi-Hop Routing Protocol
2008/2/191 Customizing a Geographical Routing Protocol for Wireless Sensor Networks Proceedings of the th International Conference on Information.
A Multi-Channel MAC Protocol for Wireless Sensor Networks Chen xun, Han peng, He qiu-sheng, Tu shi-liang, Chen zhang-long The Sixth IEEE International.
Localization With Mobile Anchor Points in Wireless Sensor Networks
Minimal Hop Count Path Routing Algorithm for Mobile Sensor Networks Jae-Young Choi, Jun-Hui Lee, and Yeong-Jee Chung Dept. of Computer Engineering, College.
(Semi) Blind Channel Estimation & Data Recovery in OFDM Presented by: Ahmed Abdul Quadeer Electrical Engineering Department 2 nd Graduates Seminar Day.
Energy-Efficient Protocol for Cooperative Networks IEEE/ACM Transactions on Networking, Apr Mohamed Elhawary, Zygmunt J. Haas Yong Zhou
Adaptive Data Aggregation for Wireless Sensor Networks S. Jagannathan Rutledge-Emerson Distinguished Professor Department of Electrical and Computer Engineering.
CHANNEL ESTIMATION FOR MIMO- OFDM COMMUNICATION SYSTEM PRESENTER: OYERINDE, OLUTAYO OYEYEMI SUPERVISOR: PROFESSOR S. H. MNENEY AFFILIATION:SCHOOL OF ELECTRICAL,
Distributed State-Estimation Using Quantized Measurement Data from Wireless Sensor Networks Li Chai with Bocheng Hu Professor College of.
Multi-Criteria Routing in Pervasive Environment with Sensors Santhanakrishnan, G., Li, Q., Beaver, J., Chrysanthis, P.K., Amer, A. and Labrinidis, A Department.
Distance Estimation by Constructing The Virtual Ruler in Anisotropic Sensor Networks Yun Wang,Kai Li, Jie Wu Southeast University, Nanjing, China, Temple.
A Distributed Relay-Assignment Algorithm for Cooperative Communications in Wireless Networks ICC 2006 Ahmed K. Sadek, Zhu Han, and K. J. Ray Liu Department.
An Energy-Efficient MAC Protocol for Wireless Sensor Networks Qingchun Ren and Qilian Liang Department of Electrical Engineering, University of Texas at.
1 Blind Channel Identification and Equalization in Dense Wireless Sensor Networks with Distributed Transmissions Xiaohua (Edward) Li Department of Electrical.
College of Engineering Anchor Nodes Placement for Effective Passive Localization Karthikeyan Pasupathy Major Advisor: Dr. Robert Akl Department of Computer.
2017/4/25 INDOOR LOCALIZATION SYSTEM USING RSSI MEASUREMENT OF WIRELESS SENSOR NETWORK BASED ON ZIGBEE STANDARD Authors:Masashi Sugano, Tomonori Kawazoe,
ELECTIONEL ECTI ON ELECTION: Energy-efficient and Low- latEncy sCheduling Technique for wIreless sensOr Networks Shamim Begum, Shao-Cheng Wang, Bhaskar.
X. Li, W. LiuICC May 11, 2003A Joint Layer Design Smart Contention Resolution Random Access Wireless Networks With Unknown Multiple Users: A Joint.
Secure In-Network Aggregation for Wireless Sensor Networks
Performance Study of Localization Techniques in Zigbee Wireless Sensor Networks Ray Holguin Electrical Engineering Major Dr. Hong Huang Advisor.
Orthogonal Frequency Division Multiplexing
Dr. Sudharman K. Jayaweera and Amila Kariyapperuma ECE Department University of New Mexico Ankur Sharma Department of ECE Indian Institute of Technology,
Sanjay K. Dhurandher, Mohammad S. Obaidat, Fellow of IEEE and Fellow of SCS, Siddharth Goel and Abhishek Gupta CAITFS, Division of Information Technology,
Variable Bandwidth Allocation Scheme for Energy Efficient Wireless Sensor Network SeongHwan Cho, Kee-Eung Kim Korea Advanced Institute of Science and Technology.
A Throughput-Adaptive MAC Protocol for Wireless Sensor Networks Zuo Luo, Liu Danpu, Ma Yan, Wu Huarui Beijing University of Posts and Telecommunications.
Data Transmission Mechanism for Multiple Gateway System Xuan He, Yuanchen Ma and Mika Mizutani, 6th International Conference on New Trends in Information.
A Multi-Channel Cooperative MIMO MAC Protocol for Wireless Sensor Networks(MCCMIMO) MASS 2010.
An Energy-Efficient Geographic Routing with Location Errors in Wireless Sensor Networks Julien Champ and Clement Saad I-SPAN 2008, Sydney (The international.
Adaptive Tracking in Distributed Wireless Sensor Networks Lizhi Yang, Chuan Feng, Jerzy W. Rozenblit, Haiyan Qiao The University of Arizona Electrical.
GLIDER: Gradient Landmark-Based Distributed Routing for Sensor Networks Qing Fang, Jie Gao, Leonidas J. Guibas, Vin de Silva, Li Zhang Department of Electrical.
1 GPS-Free-Free Positioning System for Wireless Sensor Networks Farid Benbadis, Timur Friedman, Marcelo Dias de Amorim, and Serge Fdida IEEE WCCN 2005.
A Low-Complexity Universal Architecture for Distributed Rate-Constrained Nonparametric Statistical Learning in Sensor Networks Avon Loy Fernandes, Maxim.
Cross-Layer Scheduling for Power Efficiency in Wireless Sensor Networks Mihail L. Sichitiu Department of Electrical and Computer Engineering North Carolina.
A Cluster Based On-demand Multi- Channel MAC Protocol for Wireless Multimedia Sensor Network Cheng Li1, Pu Wang1, Hsiao-Hwa Chen2, and Mohsen Guizani3.
A Load-Balanced Guiding Navigation Protocol in Wireless Sensor Networks Wen-Tsuen Chen Department of Computer Science National Tsing Hua University Po-Yu.
EM-MAC: A Dynamic Multichannel Energy-Efficient MAC Protocol for Wireless Sensor Networks ACM MobiHoc 2011 (Best Paper Award) Lei Tang 1, Yanjun Sun 2,
A Multicast Routing Algorithm Using Movement Prediction for Mobile Ad Hoc Networks Huei-Wen Ferng, Ph.D. Assistant Professor Department of Computer Science.
A Protocol for Tracking Mobile Targets using Sensor Networks H. Yang and B. Sikdar Department of Electrical, Computer and Systems Engineering Rensselaer.
An Orthogonal Resource Allocation Algorithm to Improve the Performance of OFDMA-based Cellular Wireless Systems using Relays Woonsik Lee, Minh-Viet Nguyen,
I-Hsin Liu1 Event-to-Sink Directed Clustering in Wireless Sensor Networks Alper Bereketli and Ozgur B. Akan Department of Electrical and Electronics Engineering.
A Bit-Map-Assisted Energy- Efficient MAC Scheme for Wireless Sensor Networks Jing Li and Georgios Y. Lazarou Department of Electrical and Computer Engineering,
Cooperative Location-Sensing for Wireless Networks Charalampos Fretzagias and Maria Papadopouli Department of Computer Science University of North Carolina.
Deploying Sensors for Maximum Coverage in Sensor Network Ruay-Shiung Chang Shuo-Hung Wang National Dong Hwa University IEEE International Wireless Communications.
Energy Efficient Data Management in Sensor Networks Sanjay K Madria Web and Wireless Computing Lab (W2C) Department of Computer Science, Missouri University.
Distributed Localization Using a Moving Beacon in Wireless Sensor Networks IEEE Transactions on Parallel and Distributed System, Vol. 19, No. 5, May 2008.
I owa S tate U niversity Laboratory for Advanced Networks (LAN) Coverage and Connectivity Control of Wireless Sensor Networks under Mobility Qiang QiuAhmed.
Department of Electrical Engineering, National Taiwan University of Science and Technology EURASIP Journal on Wireless Communications and Networking.
Presentation transcript:

Signal Strength based Communication in Wireless Sensor Networks (Sensor Network Estimation) Imran S. Ansari EE 242 Digital Communications and Coding (Fall 2009) Department of Electrical Engineering Division of Physical Sciences and Engineering King Abdullah University of Science and Technology December 12, 2009

KAUST King Abdullah University of Science and Technology2 OUTLINE Introduction Related Work Proposed Design Setup Implementation (Algorithm) Results Analysis Conclusion Future Work

KAUST King Abdullah University of Science and Technology3 OUTLINE Introduction Related Work Proposed Design Setup Implementation (Algorithm) Results Analysis Conclusion Future Work

Introduction WSNs – Wireless Sensor Networks Characteristics/Features Reducing the actual sensor nodes in action!!

KAUST King Abdullah University of Science and Technology5 OUTLINE Introduction Related Work Proposed Design Setup Implementation (Algorithm) Results Analysis Conclusion Future Work

Related Work Nodes compress data and encode their observations before transmission MSE (Mean Square Error) is one of the prime criterion for the performance analysis of WSNs. Coherent vs. Orthogonal Power and BW constraints MAC is coherent Gaussian Waveforms Nodes requirement threshold

KAUST King Abdullah University of Science and Technology7 OUTLINE Introduction Related Work Proposed Design Setup Implementation (Algorithm) Results Analysis Conclusion Future Work

Proposed Design - Setup

Proposed Design – Algorithm (Implementation) Event Source At the Sensor Nodes Session of ‘t’ time intervals Threshold setting process Status of the nodes Begin Transmission

Proposed Design – Algorithm (Implementation) At the BS (receiver’s) end Session of ‘t’ time intervals Threshold setting process Receives data and performs following calculations

Proposed Design – Algorithm (Implementation)

Hence, the complete process is repeated for next time interval.

KAUST King Abdullah University of Science and Technology14 OUTLINE Introduction Related Work Proposed Design Setup Implementation (Algorithm) Results Analysis Conclusion Future Work

Results Analysis

KAUST King Abdullah University of Science and Technology17 OUTLINE Introduction Related Work Proposed Design Setup Implementation (Algorithm) Results Analysis Conclusion Future Work

Conclusion WSNs can be made more efficient The proposed design lead to quite successful and positive results

KAUST King Abdullah University of Science and Technology19 OUTLINE Introduction Related Work Proposed Design Setup Implementation (Algorithm) Results Analysis Conclusion Future Work

Extend this work to more complex situations and assumptions Perform practical modeling of the proposed design

Thank you!! Queries??