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Research Article Open access CC BY 4.0

Some Aspects of Blockchain-Enabled Radio Access Networks (B-RAN) Modeling: Review and Theoretical Study

V. Kontorovich

Journal of Advances in Mathematics and Computer Science · pp. 44–60 · Published 12 Aug 2022

10.9734/jamcs/2022/v37i730464

Abstract

The impressive growth of the demand for wireless services for 5G and beyond, particularly encouraged by the Internet of Things, Internet of Everything, etc., raised up the importance of the problems related to the drastic increase (among others) of spectrum efficiency of the systems. In this regard two opportunistic trends were recently discussed by practical professionals and academicians: non-orthogonal spectrum sharing (NOMA transmission) for user equipment (UE) at physical layer level and decentralized Blockchain-enabled Radio Access (B-RAN) paradigm at network layer label. Both of them promise a significant growth on the transmission rate and the spectrum efficiency with low latency, etc. not only for 5G networks, but further, towards 6G networks and so on. Moreover, it is a fact that the number of published works for B-RAN (some of them considered hereafter) is very impressive, however, the attention to its modeling aspects is rather limited. The presented material is dedicated to present an approach for the practical small-scale modeling for the case of high-dimensional B-RAN based on continuous-time Markov processes with discrete set of states (N>>1) and self-similar processes for its traffic modeling.

Blockchain Markov models stochastic differential equations self similar processes

References (20)

  1. 1 Self‐Similar Processes in Telecommunications [DOI]
  2. 2 Epidemic Information Dissemination in Mobile Social Networks With Opportunistic Links [DOI]
  3. 3 Blockchain-enabled wireless communications: a new paradigm towards 6G [DOI]
  4. 4 Practical Modeling and Analysis of Blockchain Radio Access Network [DOI]
  5. 5 Statistics for Long-Memory Processes [DOI]
  6. 6 On self-similar traffic in ATM queues: definitions, overflow probability bound, and cell delay distribution [DOI]
  7. 7 Stochastic Methods and their Applications to Communications: Stochastic Differential Equations Approach
  8. 8 Comments on SIC Design for SISO NOMA Systems Over Doubly Selective Channels [DOI]
  9. 9 Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent [DOI]
  10. 10 Simulation of robust chaotic signal with given properties [DOI]
  11. 11 Nonlinear Filtering of Chaos for Real Time Applications [DOI]
  12. 12 Nonlinear Filtering of Chaos for Real Time Applications [DOI]
  13. 13 Study on the chaotic nature of wireless traffic [DOI]
  14. 14 Mathematical model on malicious attacks in a mobile wireless network with clustering [DOI]
  15. 15 Modeling and Simulation of Self-Similar Traffic in Wireless IP Networks [DOI]
  16. 16 Detection, Estimation, And Modulation Theory
  17. 17 System Identification [DOI]
  18. 18 Introduction to Queuing Theory [DOI]
  19. 19 Practical Modeling and Analysis of Blockchain Radio Access Network [DOI]
  20. 20 Queuing theory with heavy tails and network traffic modeling

Cited by 9

Research on the Fundamental Principles and Key Technologies of Blockchain-Enabled Mobile Communication Wireless Access Networks

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Modeling Blockchain-Based Wireless Access: A Queuing Perspective

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Hierarchical Blockchain Radio Access Networks: Architecture, Modelling, and Performance Assessment

Vasileios Kouvakis, Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos · IEEE Open Journal of the Communications Society · 2024

Blockchain-Driven Resource Management in Wireless Communications and Networks: Models, Approaches, and Applications

Mei-Ning Wu, Xintong Ling, Jia-Heng Wang · IEEE Communications Surveys and Tutorials · 2026

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