Result: The Multi-Cluster Fluctuating Two-Ray Fading Model

Title:
The Multi-Cluster Fluctuating Two-Ray Fading Model
Source:
Digibug. Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)
Publication Status:
Preprint
Publisher Information:
Institute of Electrical and Electronics Engineers (IEEE), 2024.
Publication Year:
2024
Document Type:
Academic journal Article
ISSN:
1558-2248
1536-1276
DOI:
10.1109/twc.2023.3315732
DOI:
10.48550/arxiv.2212.02448
Rights:
IEEE Copyright
CC 0
CC BY
Accession Number:
edsair.doi.dedup.....df05594678ad83c47a1f7c633bc47864
Database:
OpenAIRE

Further Information

We introduce a new class of fading channels, built as the superposition of two fluctuating specular components with random phases, plus a clustering of scattered waves: the Multi-cluster Fluctuating Two-Ray (MFTR) fading channel. The MFTR model emerges as a natural generalization of both the fluctuating two-ray (FTR) and the $κ$-$μ$ shadowed fading models through a more general yet equally mathematically tractable model. This generalization enables the presence of additional multipath clusters in the purely ray-based FTR model, and the convenience of the new underlying fading channel model is discussed in depth. Then, we derive all the chief probability functions of the MFTR model (e.g., probability density function (PDF), cumulative density function (CDF), and moment generation function) in closed-form, having {a mathematical complexity similar to} other fading models in the state-of-the-art. We also provide two additional analytical formulations for the PDF and the CDF: (i) in terms of a continuous mixture of $κ$-$μ$ shadowed distributions, and (ii) as an infinite discrete mixture of Gamma distributions. Such expressions enable to conduct performance analysis under MFTR fading by directly leveraging readily available results for the $κ$-$μ$ shadowed or Nakagami-$m$ cases, respectively. The performance of wireless communications systems undergoing MFTR fading is exemplified in terms of a classical benchmarking metric like the outage probability, both in exact and asymptotic forms, and the amount of fading.
This work was submitted to the IEEE for publication on May 31, 2022