Energy Consumption Perspective on Coded Cooperative Systems Liwen Yu and Andrej Stefanov.

Slides:



Advertisements
Similar presentations
CELLULAR COMMUNICATIONS. LTE Data Rate Requirements And Targets to LTE  reduced delays, in terms of both connection establishment and transmission.
Advertisements

Decentralized Reactive Clustering in Sensor Networks Yingyue Xu April 26, 2015.
The Impact of Channel Estimation Errors on Space-Time Block Codes Presentation for Virginia Tech Symposium on Wireless Personal Communications M. C. Valenti.
AALTO UNIVERSITY School of Science and Technology Wang Wei
Power limited Cooperative Diversity in Rayleigh Fading for Wireless Ad-hoc Networks July 20, 2006 Nam-Soo Kim, Ye Hoon Lee Cheongju Univ., Seoul National.
1 Cooperative Transmissions in Wireless Sensor Networks with Imperfect Synchronization Xiaohua (Edward) Li, Mo Chen and Wenyu Liu Department of Electrical.
Cooperative Multiple Input Multiple Output Communication in Wireless Sensor Network: An Error Correcting Code approach using LDPC Code Goutham Kumar Kandukuri.
Wireless Sensor Networks Energy Efficiency Issues
Optimization of pilot Locations in Adaptive M-PSK Modulation in a Rayleigh Fading Channel Khaled Almustafa Information System Prince Sultan University.
Joint Multi-Access and Routing as a Stochastic Game for Relay Channel Yalin Evren Sagduyu, Anthony Ephremides Objective and Motivation * Objective: Analyze.
Location Estimation in Sensor Networks Moshe Mishali.
Cross Layer Design in Wireless Networks Andrea Goldsmith Stanford University Crosslayer Design Panel ICC May 14, 2003.
Collaborative Wireless Networks Computer Laboratory Digital Technology Group Wireless Communications Today Wireless communications today has evolved into.
1 University of Freiburg Computer Networks and Telematics Prof. Christian Schindelhauer Wireless Sensor Networks 5th Lecture Christian Schindelhauer.
Adaptive Self-Configuring Sensor Network Topologies ns-2 simulation & performance analysis Zhenghua Fu Ben Greenstein Petros Zerfos.
How to Turn on The Coding in MANETs Chris Ng, Minkyu Kim, Muriel Medard, Wonsik Kim, Una-May O’Reilly, Varun Aggarwal, Chang Wook Ahn, Michelle Effros.
12- OFDM with Multiple Antennas. Multiple Antenna Systems (MIMO) TX RX Transmit Antennas Receive Antennas Different paths Two cases: 1.Array Gain: if.
Wireless MESH network Tami Alghamdi. Mesh Architecture – Mesh access points (MAPs). – Mesh clients. – Mesh points (MPs) – MP uses its Wi-Fi interface.
1. 2  What is MIMO?  Basic Concepts of MIMO  Forms of MIMO  Concept of Cooperative MIMO  What is a Relay?  Why Relay channels?  Types of Relays.
COGNITIVE RADIO FOR NEXT-GENERATION WIRELESS NETWORKS: AN APPROACH TO OPPORTUNISTIC CHANNEL SELECTION IN IEEE BASED WIRELESS MESH Dusit Niyato,
International Technology Alliance In Network & Information Sciences International Technology Alliance In Network & Information Sciences 1 Cooperative Wireless.
Does Packet Replication Along Multipath Really Help ? Swades DE Chunming QIAO EE Department CSE Department State University of New York at Buffalo Buffalo,
A Framework for Energy- Scalable Communication in High-Density Wireless Networks Telvis Calhoun Wireless Sensor Networks CSC Dr. Li 8/27/2008.
Coded Transmit Macrodiversity: Block Space-Time Codes over Distributed Antennas Yipeng Tang and Matthew Valenti Lane Dept. of Comp. Sci. & Elect. Engg.
Protocols for Self-Organization of a Wireless Sensor Network K. Sohrabi, J. Gao, V. Ailawadhi, and G. J. Pottie IEEE Personal Comm., Oct Presented.
A Simple and Effective Cross Layer Networking System for Mobile Ad Hoc Networks Wing Ho Yuen, Heung-no Lee and Timothy Andersen.
Low-Power Wireless Sensor Networks
Stochastic sleep scheduling (SSS) for large scale wireless sensor networks Yaxiong Zhao Jie Wu Computer and Information Sciences Temple University.
Michael Murphy, Huthasana Kalyanam, John Hess, Vance Faber, Boris Khattatov Fusion Numerics Inc. Overview of Current Research in Sensor Networks and Weather.
Low Complexity Virtual Antenna Arrays Using Cooperative Relay Selection Aggelos Bletsas, Ashish Khisti, and Moe Z. Win Laboratory for Information and Decision.
1 Core-PC: A Class of Correlative Power Control Algorithms for Single Channel Mobile Ad Hoc Networks Jun Zhang and Brahim Bensaou The Hong Kong University.
Wireless Sensor Networks COE 499 Energy Aware Routing
Energy-Efficient Protocol for Cooperative Networks IEEE/ACM Transactions on Networking, Apr Mohamed Elhawary, Zygmunt J. Haas Yong Zhou
Overview of Research Activities Aylin Yener
Copyright: S.Krishnamurthy, UCR Power Controlled Medium Access Control in Wireless Networks – The story continues.
Wireless Mobile Communication and Transmission Lab. Chapter 8 Application of Error Control Coding.
Ch 11. Multiple Antenna Techniques for WMNs Myungchul Kim
Computer Networks Group Universität Paderborn TANDEM project meeting Protocols, oversimplification, and cooperation or: Putting wireless back into WSNs.
Collaborative Communications in Wireless Networks Without Perfect Synchronization Xiaohua(Edward) Li Assistant Professor Department of Electrical and Computer.
نیمسال اوّل افشین همّت یار دانشکده مهندسی کامپیوتر مخابرات سیّار (626-40) ارتباطات همکارانه.
EE 6332, Spring, 2014 Wireless Communication Zhu Han Department of Electrical and Computer Engineering Class 11 Feb. 19 th, 2014.
Cross-Layer Optimization in Wireless Networks under Different Packet Delay Metrics Chris T. K. Ng, Muriel Medard, Asuman Ozdaglar Massachusetts Institute.
A Distributed Relay-Assignment Algorithm for Cooperative Communications in Wireless Networks ICC 2006 Ahmed K. Sadek, Zhu Han, and K. J. Ray Liu Department.
1 Blind Channel Identification and Equalization in Dense Wireless Sensor Networks with Distributed Transmissions Xiaohua (Edward) Li Department of Electrical.
11/25/2015 Wireless Sensor Networks COE 499 Localization Tarek Sheltami KFUPM CCSE COE 1.
X. Li, W. LiuICC May 11, 2003A Joint Layer Design Smart Contention Resolution Random Access Wireless Networks With Unknown Multiple Users: A Joint.
Motivation Wireless Communication Environment Noise Multipath (ISI!) Demands Multimedia applications  High rate Data communication  Reliability.
Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project Competitive Scheduling in Wireless Networks with Correlated Channel State Ozan.
Hybrid Indirect Transmissions (HIT) for Data Gathering in Wireless Micro Sensor Networks with Biomedical Applications Jack Culpepper(NASA), Lan Dung, Melody.
Cross-Layer Schemes for Antenna Array Based Wireless Ad Hoc Networks – Design and Analysis Jayakrishnan Mundarath Jointly Advised by : Prof. Parmesh Ramanathan.
Link-Utility-Based Cooperative MAC Protocol for Wireless Multi-Hop Networks Yong Zhou, Ju Liu, Lina Zheng, Chao Zhai, He Chen National Mobile Communications.
Variable Bandwidth Allocation Scheme for Energy Efficient Wireless Sensor Network SeongHwan Cho, Kee-Eung Kim Korea Advanced Institute of Science and Technology.
An Energy-Efficient Geographic Routing with Location Errors in Wireless Sensor Networks Julien Champ and Clement Saad I-SPAN 2008, Sydney (The international.
A Simple Transmit Diversity Technique for Wireless Communications -M
Copyright 2003 Exploiting Macrodiversity in Dense Multihop Networks and Relay Channels Matthew C. Valenti Assistant Professor Lane Dept. of Comp. Sci.
MIMO: Challenges and Opportunities Lili Qiu UT Austin New Directions for Mobile System Design Mini-Workshop.
Cooperative Diversity Using Distributed Turbo Codes Bin Zhao and Matthew C. Valenti Lane Dept. of Comp. Sci. & Elect. Eng. West Virginia.
1 M. H. Ahmed and Salama Ikki Memorial University Newfoundland, Canada Chapter 3 To Cooperate or Not to Cooperate? That Is the Question!
Multicast Scaling Laws with Hierarchical Cooperation Chenhui Hu, Xinbing Wang, Ding Nie, Jun Zhao Shanghai Jiao Tong University, China.
Chance Constrained Robust Energy Efficiency in Cognitive Radio Networks with Channel Uncertainty Yongjun Xu and Xiaohui Zhao College of Communication Engineering,
Adaptive radio-frequency resource management for MIMO MC-CDMA on antenna selection Jingxu Han and Mqhele E Dlodlo Department of Electrical Engineering.
Efficient Geographic Routing in Multihop Wireless Networks Seungjoon Lee*, Bobby Bhattacharjee*, and Suman Banerjee** *Department of Computer Science University.
1 Effectiveness of Physical and Virtual Carrier Sensing in IEEE Wireless Ad Hoc Networks Fu-Yi Hung and Ivan Marsic WCNC 2007.
SYNERGY: A Game-Theoretical Approach for Cooperative Key Generation in Wireless Networks Jingchao Sun, Xu Chen, Jinxue Zhang, Yanchao Zhang, and Junshan.
Wireless Communication Co-operative Communications
Presented by Hermes Y.H. Liu
Wireless Communication Co-operative Communications
Protocols.
Baofeng Ji,Bingbing Xing,Huahong Ma Chunguo Li,Hong Wen,Luxi Yang
Protocols.
Presentation transcript:

Energy Consumption Perspective on Coded Cooperative Systems Liwen Yu and Andrej Stefanov

Motivation User cooperation represents and efficient approach of introducing diversity in both centralized and distributed wireless networks. For distributed networks such as multi-hop ad-hoc networks, cooperative communication can combine the following two advantages:  The power savings provided by multi-hopping;  The spatial diversity provided by the antennas of separate wireless mobile nodes.

Problem Formulation Objective:  Derive the transmission energy consumption for a coded cooperative system given a target frame error rate (FER) requirement.  Analyze the potential energy benefits cooperation bring to the wireless networks over direct transmission. Channel Model and User- cooperation System Model:

Approach  FER performance of a coded cooperative system can be expressed as:  The upper bound on the probability of confusing two code words c with e for the cooperative block fading channel is:  For a particular channel code in a quasi-static or block fading channel, the pair-wise error probability (PEP) of any error event as a function of the received SNR is parallel to the FER versus received SNR for medium to high SNR values.

Results  Utilizing offsets to relate the FER and PEP, a close form expression of the energy consumption for a coded cooperative system is obtained.  Only location information of cooperation users is needed for the estimation of energy consumption. It can be quickly implemented in energy-constrained wireless ad-hoc networks, where due to the limited power available or delay constraint, extensive computations are not desirable.

Results (cont’d)  The estimation agrees with the exact expressions and simulation results well. It is rather accurate, especially in medium to high SNR ranges.

Numerical Example: How to choose a “partner” to minimize the transmission energy ?  System setup: users in the network are only aware of location information of users that are within the routing circles; Rate ¼ ( ) convolutional code is used; Channel power gain=1e-4; Noise spectral density N0=1.6e-20 W/Hz; Operating frequency=2.4 GHz;  Equivalence of the two metrics, 1) Min FER, 2) Min energy when choosing a “partner” to cooperate is shown.

Future Work Incorporate energy consumed by other parts of the circuitry besides the power amplifiers to the analysis of coded cooperative systems. Design energy-efficient cooperative routing protocol for ad-hoc wireless communication systems.