Interference and Coverage Analysis in Coexisting RF and Dense TeraHertz Wireless Networks
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Abstract (arXiv)
This paper develops a stochastic geometry framework to characterize the statistics of the downlink interference and coverage probability of a typical user in a coexisting terahertz (THz) and radio frequency (RF) network. We first characterize the exact Laplace Transform (LT) of the aggregate interference and coverage probability of a user in a THz-only network. Then, for a coexisting RF/THz network, we derive the coverage probability of a typical user considering biased received signal power association (BRSP). The framework can be customized to capture the performance of a typical user in various network configurations such as THz-only, opportunistic RF/THz, and hybrid RF/THz. In addition, asymptotic approximations are presented for scenarios where the intensity of THz BSs becomes large or molecular absorption coefficient in THz approaches to zero. Numerical results demonstrate the accuracy of the derived expressions and extract insights related to the significance of the BRSP association compared to the conventional reference signal received power (RSRP) association in the coexisting network.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jun 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 1.
3 papers.
- 2022Reinforcement Learning for Joint V2I Network Selection and Autonomous Driving Policiescited by 7
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- 2021Deep Unsupervised Learning for Generalized Assignment Problems: A Case-Study of User-Association in Wireless Networkscited by 4
- 2024Generalized Multi-Objective Reinforcement Learning with Envelope Updates in URLLC-enabled Vehicular Networks18 May 2024
- 2022Reinforcement Learning for Joint V2I Network Selection and Autonomous Driving Policies3 Aug 2022
- 2021Deep Unsupervised Learning for Generalized Assignment Problems: A Case-Study of User-Association in Wireless Networks26 Mar 2021