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Spectrum Sharing for Internet of Things: A Survey (1810.04408v1)

Published 10 Oct 2018 in cs.IT, cs.NI, and math.IT

Abstract: The Internet of Things (IoT) is a promising paradigm to accommodate massive device connections in 5G and beyond. To pave the way for future IoT, the spectrum should be planed in advance. Spectrum sharing is a preferable solution for IoT due to the scarcity of available spectrum resource. In particular, mobile operators are inclined to exploit the existing standards and infrastructures of current cellular networks and deploy IoT within licensed cellular spectrum. Yet, proprietary companies prefer to deploy IoT within unlicensed spectrum to avoid any licence fee. In this paper, we provide a survey on prevalent IoT technologies deployed within licensed cellular spectrum and unlicensed spectrum. Notably, emphasis will be on the spectrum sharing solutions including the shared spectrum, interference model, and interference management. To this end, we discuss both advantages and disadvantages of different IoT technologies. Finally, we identify challenges for future IoT and suggest potential research directions.

Citations (176)

Summary

  • The paper presents a comprehensive review of spectrum sharing methods, comparing licensed, unlicensed, and ambient backscatter approaches for IoT.
  • It evaluates technical trade-offs, including energy consumption, coverage, and interference mitigation, across various IoT technologies.
  • The study identifies future research directions, such as inter-operator sharing and edge computing, to enhance IoT network performance.

Overview of Spectrum Sharing Techniques in IoT

The paper "Spectrum Sharing for Internet of Things: A Survey" explores the multifaceted landscape of spectrum sharing solutions pertinent to Internet of Things (IoT) applications. The IoT paradigm, which encapsulates diverse smart systems, fundamentally relies on wireless connectivity to integrate myriad devices into centralized networks for enhanced data processing and operational control. As the 5G era and beyond usher in massive device connections, efficient spectrum planning is crucial given the scarcity of available spectrum resources.

Licensing Considerations and IoT Technologies

The authors categorize IoT technologies based on their deployment within either licensed cellular spectrum or unlicensed spectrum. Licensed spectrum solutions, like eMTC and NB-IoT, capitalize on current cellular network infrastructures. Contrarily, proprietary technologies often opt for the unlicensed spectrum to escape licensing costs. Both eMTC and NB-IoT are standardized within LTE frameworks to optimize cost, energy consumption, coverage, and connectivity. These technologies employ centralized spectrum management avoiding interference between IoT and cellular links.

Within unlicensed spectrum, technologies such as Bluetooth, ZigBee, LoRaWAN, and SigFox exhibit variability in scope and application. They utilize ISM bands, deploying techniques such as frequency hopping (Bluetooth) and DSSS (ZigBee) to mitigate interference. LoRaWAN and SigFox further advance the spectrum sharing narrative with duty cycle restrictions and deployment in sub-GHz ISM bands.

Ambient Backscatter Communication

The paper extends the IoT spectrum sharing discussion to include ambient backscatter communication. This technique engenders ultra-low-power, inexpensive solutions by leveraging electromagnetic signals in the environment, applicable across both licensed and unlicensed spectrums. It challenges traditional wireless communication design, necessitating innovative interference management at receivers and revealing a spectrum sharing paradigm conducive to short-range transmissions.

Comparative Analysis and Future Directions

IoT spectrum sharing technologies manifest distinct advantages and limitations. Licensed solutions promise extensive coverage and QoS guarantees at a premium. Unlicensed alternatives provide cost efficiency but with compromised QoS, whereas ambient backscatter offers minimal hardware costs at the expense of range limitations. The authors advocate exploration beyond conventional designs, urging research into emerging scenarios, enhanced theoretical frameworks, and novel spectrum resources such as millimeter wave technology.

Implications and Speculative Observations

The exploration into inter-operator spectrum sharing and edge computing signifies not merely technical evolution but a fundamental shift in the network paradigm for IoT. By providing alternate paths to manage complex traffic models, these innovations spur progressive design methodologies necessary for accommodating vast IoT data volumes. Undoubtedly, such developments herald transformative changes in communication protocols and strategies.

Conclusion

In concluding their survey, the authors present a comprehensive synthesis of existing IoT technologies, extending an invitation to further probe into dynamic spectrum sharing solutions as IoT ecosystems expand. The highlighted challenges and proposed directions underscore the imperative for continuous innovation, making fundamental contributions to the strategic planning required for future IoT landscapes.