Reliable relay assisted communications for IoT based fall detection

Area of Science:

• Wireless Communication Systems
• Internet of Things (IoT)
• Signal Processing

Background:

• Future Internet of Things (IoT) applications require robust wireless communication, particularly relaying systems combined with Non-Orthogonal Multiple Access (NOMA).
• Fall detection systems for elderly patients are a critical IoT application demanding high communication reliability.

Purpose of the Study:

• To analyze the average signal-to-interference-plus-noise (SINR) performance of a NOMA-based relaying system for a fall detection IoT application.
• To derive closed-form average SINR expressions for both Amplify-and-Forward (AF) and Decode-and-Forward (DF) relaying systems in NOMA.

Main Methods:

• Utilized a NOMA-based relaying system where a source node transmits two symbols to a relay and destination node using superposition coding over Rayleigh fading channels.
• Analyzed two relaying protocols: AF (amplification and re-transmission) and DF (decoding and re-transmission based on NOMA power coefficient).
• Derived closed-form average SINR expressions using Tricomi confluent hypergeometric and Meijer's G functions.

Main Results:

• Derived novel closed-form expressions for the average SINR performance of NOMA-based AF and DF relaying systems.
• The derived analytical expressions for average SINR were validated against simulation results, showing excellent agreement.
• Demonstrated the effectiveness of the NOMA relaying system in improving communication reliability for the fall detection IoT application.

Conclusions:

• The developed analytical expressions provide computationally efficient methods for evaluating the SINR performance of NOMA relaying systems.
• The NOMA-based relaying system shows significant potential for enhancing the reliability of IoT applications like elderly fall detection.
• The study confirms the accuracy of the derived SINR expressions through rigorous simulations.