Abstract

This paper proposes a blockchain-based automated frequency coordination system (BAFCS) for secure and reliable spectrum sharing without causing any harmful interference to an existing system. For the exact assessment of whether the incumbent is interfered with by the spectrum sharer, the received signal strength (RSS) associated with the incumbent should be measured with sufficient accuracy at every location within the area of interest. However, since it requires brute force to carry out empirical measurements around an entire region, to lessen the burden, only the confined portion of the RSSs associated with the incumbent as a kind of primary user are observed and the omitted residuals are conventionally estimated by carrying out the well-known Kriging interpolation with regard to the geostatistical characteristics. This paper proposes a frequency coordination system capable of identifying whether a requested frequency band can be eligible for spectrum sharing while exchanging adequate information over blockchain network to confirm the usability. This paper proposes the Support Vector Machine (SVM)-based Kriging interpolation for recapitulating the radio environment map (REM) when only a fraction of the RSS measurements is acquired by the voluntary sensing participant (VSP). The nonparametric modeling approach for variograms proposed in this paper was determined to have a vital role in making a confident decision regarding spectrum sharing. The simulation result confirmed the effectiveness and the superiority of the proposed BAFCS with several affirmative features, such as enabling the consensus-based approval of spectrum sharing, the secure transaction of the information, and reliable assurance of no harmful interference.

Highlights

  • With the prosperity of the fifth generation (5G) era, various types of vertical services, such as autonomous vehicles, drones, and the massive internet of things (IoT), are readily deployed in the real world [1]

  • Once the validity of the spectrum sharing is confirmed upon the consensus process, the FB-USER is informed that they have permission for spectrum sharing and the SS-OWNER remits this to the voluntary sensing participant (VSP)

  • We proposed a blockchain-based automated frequency coordination system that realized secure and trusted spectrum sharing upon a unanimous consensus basis without any intentional human intervention

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Summary

Introduction

With the prosperity of the fifth generation (5G) era, various types of vertical services, such as autonomous vehicles, drones, and the massive internet of things (IoT), are readily deployed in the real world [1]. The blockchain-based automated frequency coordination system (BAFCS) proposed in this paper uses these two essential approaches, essentially running on a blockchain validating spectrum sharing in accordance with assessing the degree of interference with the support of REM recapitulation powered by SVM regression. In regard to the secure transactions of information encompassing the status of spectrum utilization related to the incumbent, the empirical sensing data, etc., the overall functions composing the proposed BAFCS are introduced. There are five key features in the proposed BAFCS as follows: Collecting ESD from the domain-delegated VSPs to configure the REM in the region of interest; Recapitulating the site-specific REM with the assistance of the Kriging interpolation; Rewarding the coin to the VSPs with the comprehensive assessment; Transacting the information and exchanging the cryptocurrency as verified by smart contracts; and Deciding whether the request for the spectrum sharing is approved. Once the validity of the spectrum sharing is confirmed upon the consensus process, the FB-USER is informed that they have permission for spectrum sharing and the SS-OWNER remits this to the VSPs

Recapitulation of Site-Specific REM Using SVM-Based Kriging Interpolation
Variogram Exploitation with Given Site-Specific Sensing Measurements
SVM-Based Kriging Interpolation Model
Simulation
Performance Analysis of the Proposed REM Recapitulation
Conclusions
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