A random access scheme based on dynamic allocation of PRACH resources for smart grid communication

Peng, Fenghua; Feng, Feifei; Yan, Bo; Zhang, Jie

doi:10.1109/iccsn.2017.8230180

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…This work develops a DRL algorithm based on a round-robin approach, which outperforms in terms of network performance as well as improving cache hit ratio and reducing transmission delay. Starting from the resource situation of device access, [23] proposes a random access mechanism based on the dynamic allocation of physical random access channel (PRACH) resources. It will adjust the PRACH configuration index according to high-priority overloads, thereby alleviating RAN congestion.…”

Section: Related Work a Development Of Smart Gridmentioning

confidence: 99%

Multi-Target-Aware Energy Orchestration Modeling for Grid 2.0: A Network Virtualization Approach

et al. 2023

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Smart Grid -Grid 2.0, is a promising grid scenario due to its low cost, high reliability, and high security. However, the high-intensity complex task interaction and the differentiated quality of service (QoS) requirements pose challenges to the energy orchestration of the dynamic and time-varying smart grid. In addition, Network Virtualization (NV) technology is widely utilized to decouple physical network resources. In this work, based on Virtual Network Embedding (VNE), we propose an energy orchestration strategy to better support the operation and maintenance of Grid 2.0. Specifically, a series of constraint indicators for energy orchestration is first formulated. Second, based on the advantages of deep reinforcement learning (DRL), a five-layer architecture energy orchestration model is proposed. It frequently extracts the grid energy matrix as the state input, adopts two-stage actions to reasonably orchestrate the grid energy, and combines the reward mechanism of DRL to effectively interact with the environment. Finally, we conduct experiments in a simulation environment and demonstrate the advantages of the proposed strategy through analysis and comparison.

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Section: Related Work a Development Of Smart Gridmentioning

confidence: 99%

Multi-Target-Aware Energy Orchestration Modeling for Grid 2.0: A Network Virtualization Approach

et al. 2023

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Service-Aware Resource Allocation Based on RAN Slicing for Smart Grid

Meng

Wang

Ding

et al. 2019

Innovative Mobile and Internet Services in Ubiquitous Computing

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Adaptive Out-of-band Radio Preamble Contention for Optimizing Virtual Resource in B5G/5G NR^*

Chang,

Lin

2024

2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)

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A random access scheme based on dynamic allocation of PRACH resources for smart grid communication

Cited by 4 publications

References 14 publications

Multi-Target-Aware Energy Orchestration Modeling for Grid 2.0: A Network Virtualization Approach

Multi-Target-Aware Energy Orchestration Modeling for Grid 2.0: A Network Virtualization Approach

Service-Aware Resource Allocation Based on RAN Slicing for Smart Grid

Adaptive Out-of-band Radio Preamble Contention for Optimizing Virtual Resource in B5G/5G NR^*

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A random access scheme based on dynamic allocation of PRACH resources for smart grid communication

Cited by 4 publications

References 14 publications

Multi-Target-Aware Energy Orchestration Modeling for Grid 2.0: A Network Virtualization Approach

Multi-Target-Aware Energy Orchestration Modeling for Grid 2.0: A Network Virtualization Approach

Service-Aware Resource Allocation Based on RAN Slicing for Smart Grid

Adaptive Out-of-band Radio Preamble Contention for Optimizing Virtual Resource in B5G/5G NR*

Contact Info

Product

Resources

About

Adaptive Out-of-band Radio Preamble Contention for Optimizing Virtual Resource in B5G/5G NR^*