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Related Experiment Video

Updated: Jul 30, 2025

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

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Published on: May 2, 2018

Performance Analysis of Wirelessly Powered Cognitive Radio Network with Statistical CSI and Random Mobility.

Nadica Kozić¹, Vesna Blagojević¹, Aleksandra Cvetković²

¹School of Electrical Engineering, University of Belgrade, 11000 Belgrade, Serbia.

Sensors (Basel, Switzerland)

|May 13, 2023

Summary

This summary is machine-generated.

Cognitive radio and wireless power transfer address spectrum scarcity and IoT energy needs. This study analyzes a system with mobile users, deriving key performance metrics for efficient communication.

Keywords:

Internet of Things cognitive radio ergodic capacity outage probability power beacon random waypoint mobility model spectrum sharing statistical channel state information underlay wireless power transfer

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Area of Science:

Wireless Communications
Cognitive Radio Networks
Internet of Things (IoT)

Background:

Rapid growth in 5G services exacerbates spectrum scarcity.
The Internet of Things (IoT) demands efficient energy usage and device powering.
Cognitive radio offers a potential solution to spectrum scarcity.

Purpose of the Study:

To analyze a wirelessly powered underlay cognitive system with statistical channel state information (CSI).
To model a realistic scenario with a randomly moving cognitive user receiver for IoT applications.
To derive performance metrics for the analyzed system.

Main Methods:

Mathematical derivation of closed-form expressions for system performance.
Analysis of an underlay cognitive system sharing spectrum with primary users.
Inclusion of an interference threshold and outage constraint for the primary user.
Modeling of a mobile cognitive user receiver.

Main Results:

Closed-form expressions for outage probability derived.
Closed-form expressions for outage capacity derived.
Closed-form expressions for ergodic capacity derived.

Conclusions:

The derived analytical results provide key performance insights for wirelessly powered cognitive IoT systems.
The study validates analytical findings through independent simulations.
The research contributes to overcoming spectrum scarcity and enabling efficient IoT device powering.