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Distributed Sequential Detection for Cooperative Spectrum Sensing in Cognitive Internet of Things.

Jun Wu1,2, Zhaoyang Qiu1, Mingyuan Dai1

  • 1School of Communication Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.

Sensors (Basel, Switzerland)
|January 26, 2024
PubMed
Summary

To address spectrum scarcity for internet of things (IoT) devices, a collaborative spectrum sensing (CSS) framework was developed. This framework optimizes sensing time and decision costs for IoT devices to efficiently identify available spectrum without interfering with primary users.

Keywords:
cooperative spectrum sensingcost functioninternet of thingsensing timesequential detection rule

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Area of Science:

  • Wireless Communication
  • Internet of Things (IoT)
  • Spectrum Management

Background:

  • Increasing demand for wireless spectrum due to proliferation of IoT devices.
  • Spectrum scarcity poses a significant challenge for IoT device connectivity and performance.
  • Existing methods lack efficient spectrum utilization strategies for IoT networks.

Purpose of the Study:

  • To introduce a collaborative spectrum sensing (CSS) framework for IoT devices.
  • To address the challenges of sensing time and decision costs in spectrum sensing.
  • To optimize spectrum access for IoT devices while avoiding interference with primary users (PUs).

Main Methods:

  • Development of a distributed cognitive IoT model with sequential decision rules.
  • Definition of sensing time and cost functions for IoT devices.
  • Formulation of an average cost optimization problem in CSS.
  • Application of person-by-person optimization (PBPO) and dynamic programming to solve the optimal sensing time problem.

Main Results:

  • Numerical simulations validate the proposed framework's effectiveness.
  • The framework successfully minimizes global false alarm and miss detection probabilities.
  • Achieved minimal average cost across various observation costs and thresholds.

Conclusions:

  • The proposed CSS framework provides an efficient solution for spectrum scarcity in IoT environments.
  • Optimized sensing strategies reduce operational costs for IoT devices.
  • The model ensures reliable spectrum access for IoT devices without compromising primary user communications.