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 language | English |
|---|---|
| Pages (from-to) | 8012-8044 |
| Number of pages | 33 |
| Journal | Journal of the Franklin Institute |
| Volume | 358 |
| Issue number | 15 |
| DOIs | |
| State | Published - Oct 2021 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2021 The Franklin Institute
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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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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