Hardware Impaired Self-Energized Bidirectional Sensor Networks over Complex Fading Channels

Area of Science:

• Wireless Sensor Networks (WSN)
• Energy Harvesting (EH)
• Internet of Things (IoT)

Background:

• Limited battery life in wireless sensor nodes is a major challenge for WSNs.
• Efficient energy management is crucial for unlocking the full potential of WSNs in the IoT paradigm.
• Energy harvesting techniques are vital for prolonging sensor node operational time.

Purpose of the Study:

• To analyze the performance of a time-switching energy harvesting system for half-duplex bidirectional WSNs.
• To investigate the impact of hardware impairments and fading channels on system efficiency.
• To develop analytical expressions for key performance metrics.

Main Methods:

• Developed rapidly converging infinite-series expressions for performance analysis.
• Focused on outage probability (OP) and achievable throughput.
• Analyzed symbol-error probability (SEP) and considered shadowing effects.

Main Results:

• Provided comprehensive performance analysis for hardware-impaired systems over Hoyt fading channels.
• Derived exact infinite-series expressions for OP and throughput over Rician-shadowed fading channels.
• Investigated asymptotic behavior of performance measures.

Conclusions:

• The proposed time-switching EH scheme offers a viable solution for prolonging WSN battery life.
• The analytical framework provides accurate performance predictions for WSNs in diverse fading environments.
• The study contributes to the efficient design of energy-aware WSNs for IoT applications.