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Power Efficient Wireless Sensor Networks with Distributed Transmission-Induced Space Spreading

Power Efficient Wireless Sensor Networks with Distributed Transmission-Induced Space Spreading. Xiaohua (Edward) Li and N. Eva Wu Department of Electrical and Computer Engineering State University of New York at Binghamton {xli, evawu}@binghamton.edu http://ucesp.ws.binghamton.edu/~xli.

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Power Efficient Wireless Sensor Networks with Distributed Transmission-Induced Space Spreading

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  1. Power Efficient Wireless Sensor Networks with Distributed Transmission-Induced Space Spreading Xiaohua (Edward) Li and N. Eva Wu Department of Electrical and Computer Engineering State University of New York at Binghamton {xli, evawu}@binghamton.edu http://ucesp.ws.binghamton.edu/~xli

  2. Major Contributions • Resolve the conflict between transmission energy efficiency and fault tolerance • Propose distributed space-spreading for • Efficient/robust blind signal detection • Transmission energy efficiency • Network reliability

  3. 1.1. Sensor Network Challenges • How to improve transmission energy efficiency in deep-faded near-ground communications? • How to improve fault tolerance and network reliability with low cost sensors suffering from high failure rate? • How to resolve the conflict between energy efficiency and fault tolerance? They have contradictory requirements on redundancy. Multi-hop Wireless Sensor Network

  4. 1.2 Strategies for the Challenges • Distributed multi-transmission with space-spreading • Transmission redundancy provides diversity for energy efficiency • Transmission redundancy provides fault tolerance Scrambled Parallel Transmission from J Sensors

  5. Why can we use multi-transmission? • Wireless transmission is broadcasting • a data packet can be received/retransmitted by multiple sensors • There are always multiple standby sensors ready for multi-transmission • Energy in standby state is in the same level as in receiving state • How to perform multi-transmission? • Distributed space-spreading: scrambled parallel transmission (the above figure) • Distributed space-time coding: to appear in Electronics Letters, 2003.

  6. 2. Space Spreading and Blind Symbol Estimation • Sensor j in cluster i transmits the same signal s(n) with different PN scrambling: • A sensor in cluster i+1 receives (separately) signals from all sensors j:

  7. 3. Energy Efficiency Analysis • Transmission energy efficiency comes from the diversity of the scrambled parallel transmission • Major results:

  8. Power ratio of single-transmission to multi-transmission for 15 dB SNR with Probability B. Multi-transmission can be more than 30 dB more energy efficient.

  9. 4. Fault-Tolerance Analysis

  10. Example: For design life TD=2000 packets, J=2 is better and has reliability 0.89. However, for reliability 0.99, J=10 is better, though with a shorter design life TD=1000 packets.

  11. 5. Simulations • Multi-transmission: • New batch & adaptive algorithms: J=8 sensors. • Single-transmission: • DSSS with Rake receiver: processing gain 8. • Blind CMA • Training MMSE equalization

  12. Compare space-spreading with spectrum-spreading (DSSS)

  13. Transmission power (normalized with that of the new batch algorithm) required to achieve symbol-error-rate (SER) 0.01 • Multi-transmission-based space-spreading has higher energy efficiency, longer sensor lifetime, and higher reliability.

  14. 6. Conclusions • Propose a new space-spreading scheme for wireless sensor networks to achieve • transmission energy efficiency • blind symbol estimation • transmission/network reliability • Resolve the conflict between energy efficiency and fault tolerance via transmission redundancy

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