Multiband Spectrum Sensing and Resource Allocation for IoT in Cognitive 5G Networks
Abstract
The proliferation of the Internet of Things (IoT) demands a diverse and wide range of requirements in terms of latency, reliability, energy efficiency, etc. Future IoT systems must have the ability to deal with the challenging requirements of both users and applications. Cognitive fifth generation (5G) network is envisioned to play a key role in leveraging the performance of IoT systems. IoT systems in cognitive 5G network are expected to provide flexible delivery of broad services and robust operations under highly dynamic conditions. In this paper, we present multiband cooperative spectrum sensing and resource allocation framework for IoT in cognitive 5G networks. Multiband approach can significantly reduce energy consumption for spectrum sensing compared to the traditional single-band scheme. We formulate an optimization problem to determine a minimum number of channels to be sensed by each IoT node in multiband approach to minimize the energy consumption for spectrum sensing while satisfying probabilities of detection and false alarm requirements. We then propose a cross-layer reconfiguration scheme (CLRS) for dynamic resource allocation in IoT applications with different quality-of-service (QoS) requirements including data rate, latency, reliability, economic price, and environment cost. The potential game is employed for crosslayer reconfiguration, in which IoT nodes are considered as the players. The proposed CLRS efficiently allocate resources to satisfy QoS requirements through opportunistic spectrum access. Finally, extensive simulation results are presented to demonstrate the benefits offered by the proposed framework for IoT systems.
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The spectrum sharing in shared/unlicensed spectrum will continue to be one of the main research trends aimed at delivering multigigabit, ultra-reliable, and ultra-low latency connectivity.
“The spectrum sharing in shared/unlicensed spectrum will continue to be one of the main research trends aimed at delivering multigigabit, ultra-reliable, and ultr-low latency connectivity.”
From Future Industry Internet of Things with Zero-trust Security (2024) · cites this paper as Ejaz & Ibnkahla, 2018
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Future Industry Internet of Things with Zero-trust Security
Li, S., Iqbal, M., & Saxena, N. (2024) · Information Systems Frontiers · doi:10.1007/s10796-021-10199-5 · Cited by 128 · see citing works
- Authors
- Ejaz, W., & Ibnkahla, M.
- Affiliations
- Carleton University (CA)
- Venue
- IEEE Internet of Things Journal
- Published
- 2018-02
- Volume
- 5
- Issue
- 1
- Pages
- 150-163
- ISSN
- 2327-4662 (ISSN-L)
- OpenAlex
- W2768653190
- Cited by
- 191
- References
- 45
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 20 · 2023: 19 · 2022: 18 · 2021: 30 · 2020: 34 · 2019: 35 · 2018: 21
- FWCI
- 16.39
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Cognitive Radio Networks and Spectrum Sensing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT Networks and Protocols
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Keywords
- cooperative spectrum sensing, Internet of Things, dynamic resource allocation, potential games, quality of service, opportunistic spectrum access, detection and false alarm probability
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