Abstract
In this paper, we propose the α-Lomax distribution as a new compound fading channel model. This new distribution generalizes the recently introduced Lomax fading channel model. It is worth noting that the Lomax distribution is a decreasing function, whereas the α-Lomax is unimodal function, offering greater flexibility in modeling wireless fading channels. In particular, we derive closed-form expressions for the probability density function and cumulative distribution function for the instantaneous signal-to-noise ratio (SNR). Additionally, we provide closed-form expressions for several fundamental performance metrics, including outage probability, average bit error rate, and channel capacity. Furthermore, we derive closedform expression for the average block-length error rate in short-packet communications. Moreover, we fit the PDF of the proposed channel model to empirical data obtained from a device-to-device communication system. We also offer simple and accurate approximations for these expressions in the high SNR regime.
| Original language | English |
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| Title of host publication | 2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 83-88 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350376715 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024 - Abu Dhabi, United Arab Emirates Duration: 17 Nov 2024 → 20 Nov 2024 |
Publication series
| Name | 2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024 |
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Conference
| Conference | 2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024 |
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| Country/Territory | United Arab Emirates |
| City | Abu Dhabi |
| Period | 17/11/24 → 20/11/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- Compound fading
- Gamma distribution
- Lomax distribution
- Rayleigh distribution
- wireless communications
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Signal Processing
- Instrumentation