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Mathematical modeling and performance evaluation of BeRAN for 6G wireless networks

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Abstract

The evolution of mobile applications and services is constantly growing in the artificial intelligence (AI) and Internet of Things (IoT) era, confronting many distinctive difficulties to existing network architectures. In order to meet the constantly growing demand for internet services, the blockchain radio access network (B-RAN), a decentralized radio access approach, has emerged. Yet, many issues of B-RAN modeling to be clarified and are hard to define. In this article, we present a novel Blockchain-empowered Radio Access Network (BeRAN) paradigm and in-depth fundamental mathematical modeling of the proposed framework by building a capacity and latency trade-off relationship using the queuing model. In addition, a novel resource aggregation and network sharing mechanism has been proposed, and we investigated BeRAN's performance on both permissioned and permissionless Blockchain in terms of end-to-end latency and network capacity based on the queuing model. Moreover, the blockchain communication overhead and network base station (BS) load are considered to understand BeRAN's performance better. In addition, comparing the proposed BeRAN with the existing RAN and Proof-of-Work (PoW) frameworks improved the average throughput by 36.04% and resource utilization percentage by 28.7%. On the other hand, this mechanism reduced the average latency by 66.14% and average access time by 58.8% compared to the existing RAN framework. It is concluded from the simulation results that the proposed BeRAN mechanism can be used for various security applications of sixth-generation (6G) wireless networks with improved efficacy and privacy.

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  1. Department of Electronics and Communication Engineering, National Institute of Technology, Warangal, Telangana, India

    Vuppula Roopa & Himansu Shekhar Pradhan

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Correspondence to Himansu Shekhar Pradhan.

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Roopa, V., Pradhan, H.S. Mathematical modeling and performance evaluation of BeRAN for 6G wireless networks. J Supercomput 79, 16479–16528 (2023). https://doi.org/10.1007/s11227-023-05321-0

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