Grant-Free Power Allocation for Ultra-Dense Internet of Things Environments: A Mean-Field Perspective
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866913218513862656 |
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| author | Nadif, Sami Sabir, Essaid Elbiaze, Halima Haqiq, Abdelkrim |
| author_facet | Nadif, Sami Sabir, Essaid Elbiaze, Halima Haqiq, Abdelkrim |
| contents | Grant free access, in which each Internet of Things (IoT) device delivers its packets through a randomly selected resource without spending time on handshaking procedures, is a promising solution for supporting the massive connectivity required for IoT systems. In this paper, we explore grant free access with multi packet reception capabilities, with an emphasis on ultra low end IoT applications with small data sizes, sporadic activity, and energy usage constraints. We propose a power allocation scheme that integrates the IoT device's traffic and energy budget by using a stochastic geometry framework and meanfield game theory to model and analyze mutual interference among active IoT devices.We also derive a Markov chain model to capture and track the IoT device's queue length and derive the successful transmission probability at steady state. Simulation results illustrate the optimal power allocation strategy and show the effectiveness of the proposed approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_00008 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Grant-Free Power Allocation for Ultra-Dense Internet of Things Environments: A Mean-Field Perspective Nadif, Sami Sabir, Essaid Elbiaze, Halima Haqiq, Abdelkrim Networking and Internet Architecture Computer Science and Game Theory Grant free access, in which each Internet of Things (IoT) device delivers its packets through a randomly selected resource without spending time on handshaking procedures, is a promising solution for supporting the massive connectivity required for IoT systems. In this paper, we explore grant free access with multi packet reception capabilities, with an emphasis on ultra low end IoT applications with small data sizes, sporadic activity, and energy usage constraints. We propose a power allocation scheme that integrates the IoT device's traffic and energy budget by using a stochastic geometry framework and meanfield game theory to model and analyze mutual interference among active IoT devices.We also derive a Markov chain model to capture and track the IoT device's queue length and derive the successful transmission probability at steady state. Simulation results illustrate the optimal power allocation strategy and show the effectiveness of the proposed approach. |
| title | Grant-Free Power Allocation for Ultra-Dense Internet of Things Environments: A Mean-Field Perspective |
| topic | Networking and Internet Architecture Computer Science and Game Theory |
| url | https://arxiv.org/abs/2402.00008 |