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Diversity Performance Analysis on Multiple HAP Networks.

Feihong Dong1,2, Min Li3, Xiangwu Gong4,5

  • 1College of Communications Engineering, PLA University of Science and Technology, 88 Houbiaoying Rd., Nanjing 210007, China. dfh_sinlab@hotmail.com.

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Summary
This summary is machine-generated.

This study introduces a virtual MIMO (V-MIMO) model using multiple high altitude platforms (HAPs) to enhance wireless sensor network (WSN) data rates. The V-MIMO model significantly boosts network performance in shadowed Rician fading channels.

Keywords:
average symbol error ratechannel state informationhigh altitude platformmultiple assets in viewshadowed Rician fadingsystem capacityvirtual multiple-input multiple-outputwireless sensor networks

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Area of Science:

  • Wireless communication networks
  • Signal processing
  • Information theory

Background:

  • High-data-rate transmission is a key challenge in wireless sensor networks (WSNs).
  • High altitude platforms (HAPs) serve as crucial communication relays for WSNs and future wireless networks.
  • Multiple-input multiple-output (MIMO) techniques enhance network performance through diversity and multiplexing gains.

Purpose of the Study:

  • To propose a virtual MIMO (V-MIMO) model by networking multiple HAPs using the multiple assets in view (MAV) concept.
  • To analyze the diversity performance of the V-MIMO model in a shadowed Rician fading channel.
  • To investigate system capacity under perfect and unknown channel state information (CSI) conditions.

Main Methods:

  • Development of a V-MIMO model integrating multiple HAPs with MAV.
  • Derivation of probability density function (PDF) and cumulative distribution function (CDF) for received signal-to-noise ratio (SNR).
  • Calculation of average symbol error rate (ASER) for BPSK and QPSK modulation schemes.
  • Analysis of ergodic capacity considering various SNRs and Rician factors.

Main Results:

  • The probability density function (PDF) and cumulative distribution function (CDF) of the received SNR were derived.
  • Average symbol error rate (ASER) for BPSK and QPSK was calculated for the V-MIMO model.
  • System capacity was studied for both perfect and unknown channel state information (CSI).
  • Ergodic capacity was analyzed for different network configurations, SNRs, and Rician factors.

Conclusions:

  • The proposed V-MIMO model significantly improves the performance of HAP networks in WSNs.
  • Utilizing MAV for overlapping coverage enhances network efficiency with V-MIMO techniques.
  • The performance analysis is validated by simulation results, demonstrating the effectiveness of the proposed approach.