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Multihop Weibull-fading communications: Performance analysis framework and applications

  • Abdelaziz Soulimani
  • , Mustapha Benjillali*
  • , Hatim Chergui
  • , Daniel B. da Costa
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

The paper presents a comprehensive closed-form performance analysis framework for multihop communications over Weibull fading channels. This framework may be of interest in different applications in the contexts of beyond-5G (B5G) and Internet of Things (IoT) use cases. The analyzed scheme consists generally of multiple regenerative relays, and we also consider generalized high-order quadrature amplitude modulation (M-QAM) transmissions. To take into consideration the channel fading, we adopt the Weibull model for its largely flexible ability to cover different channel conditions in different application contexts. The end-to-end performance is evaluated in terms of outage probability, bit error probability (BER), symbol error probability (SER), block error rate (BLER), ergodic capacity, and energy efficiency (EE). For all the metrics, we present exact closed-form expressions—along with their asymptotic behavior—capitalizing on the powerful generalized hypergeometric functions. To illustrate the utility of the obtained analytical results, we derive two BER- and EE-optimal transmit power allocation strategies, and we discuss the resulting performance gains. The exactness of our analysis is illustrated by numerical examples, and assessed via Monte-Carlo simulations for different system and channel parameters. Finally, as a secondary contribution, and noting the increasing popularity of single and bivariate Fox's H-function, we provide generalized MATLAB codes for computing these functions which are of practical utility in many fields.

Original languageEnglish
Pages (from-to)8012-8044
Number of pages33
JournalJournal of the Franklin Institute
Volume358
Issue number15
DOIs
StatePublished - Oct 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 The Franklin Institute

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications
  • Applied Mathematics

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