Outage probability of dual-hop cooperative communication networks over the Nakagami-m fading channel with RF energy harvesting

Vinh, Hoang Duc; Hoang, Tran Manh; Hiep, Pham Thanh

doi:10.1007/s12243-020-00821-z

Cited by 2 publications

(1 citation statement)

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“…As elements such as the spatial distribution of network nodes, wireless channel fading characteristics, and other factors influence the interference distribution in wireless networks, current analyses of wireless multi-hop networks primarily concentrate on interference and outage probability, as well as capacity and throughput assessments. For example, Vinh et al [14] derived the system outage probability based on a specific fading model for a relayed two-hop collaborative relaying system containing multiple relay nodes for a pair of communication users using amplify-and-forward and decode-and-forward protocols, respectively. Olmedo et al [15] proposed a wireless TCP protocol improvement considering Negative Acknowledgment (NACK), which allowed for distinguishing between losses due to congestion and losses due to wireless channel problems.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Internet of Vehicles Mesh Networks Based on Actual Switch Models

Hu,

Ren,

Cheng

et al. 2024

Electronics

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The rapid growth of the automotive industry has exacerbated the conflict between the complex traffic environment, increasing communication demands, and limited resources. Given the imperative to mitigate traffic and network congestion, analyzing the performance of Internet of Vehicles (IoV) mesh networks is of great practical significance. Most studies focus solely on individual performance metrics and influencing factors, and the adopted simulation tools, such as OPNET, cannot achieve the dynamic link generation of IoV mesh networks. To address these problems, a network performance analysis model based on actual switches is proposed. First, a typical IoV mesh network architecture is constructed and abstracted into a mathematical model that describes how the link and topology changes over time. Then, the task generation model and the task forwarding model based on actual switches are proposed to obtain the real traffic distribution of the network. Finally, a scientific network performance indicator system is constructed. Simulation results demonstrate that, with rising task traffic and decreasing node caching capacity, the packet loss rate increases, and the task arrival rate decreases in the network. The proposed model can effectively evaluate the network performance across various traffic states and provide valuable insights for network construction and enhancement.

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Section: Related Workmentioning

confidence: 99%