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Cooperative Transmission in Mobile Wireless Sensor Networks with Multiple Carrier Frequency Offsets: A Double-Differential Approach

Author

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  • Kun Zhao
  • Kegang Pan
  • Bangning Zhang

Abstract

As a result of the rapidly increasing mobility of sensor nodes, mobile wireless sensor networks (MWSNs) would be subject to multiple carrier frequency offsets (MCFOs), which result in time-varying channels and drastically degrade the network performance. To enhance the performance of such MWSNs, we propose a relay selection (RS) based double-differential (DD) cooperative transmission scheme, termed RSDDCT, in which the best relay sensor node is selected to forward the source sensor node’s signals to the destination sensor node with the detect-and-forward (DetF) protocol. Assuming a Rayleigh fading environment, first, exact closed-form expressions for the outage probability and average bit error rate (BER) of the RSDDCT scheme are derived. Then, simple and informative asymptotic outage probability and average BER expressions at the large signal-to-noise ratio (SNR) regime are presented, which reveal that the RSDDCT scheme can achieve full diversity. Furthermore, the optimum power allocation strategy in terms of minimizing the average BER is investigated, and simple analytical solutions are obtained. Simulation results demonstrate that the proposed RSDDCT scheme can achieve excellent performance over fading channels in the presence of unknown random MCFOs. It is also shown that the proposed optimum power allocation strategy offers substantial average BER performance improvement over the equal power allocation strategy.

Suggested Citation

  • Kun Zhao & Kegang Pan & Bangning Zhang, 2014. "Cooperative Transmission in Mobile Wireless Sensor Networks with Multiple Carrier Frequency Offsets: A Double-Differential Approach," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-13, April.
  • Handle: RePEc:hin:jnlmpe:853821
    DOI: 10.1155/2014/853821
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    Cited by:

    1. Furqan Alam & Ahmed Almaghthawi & Iyad Katib & Aiiad Albeshri & Rashid Mehmood, 2021. "iResponse: An AI and IoT-Enabled Framework for Autonomous COVID-19 Pandemic Management," Sustainability, MDPI, vol. 13(7), pages 1-52, March.

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