A Robust and Energy-Efficient Wireless Sensor Network for Radiometry Monitoring

Wireless sensor networks used for radiometry monitoring must ensure long-term operation, reliable data delivery, and efficient utilization of limited energy resources in harsh and remote environments. Conventional clustering protocols often suffer from rapid energy depletion, unreliable communication, and limited spectral efficiency, especially when battery replacement is impractical. This paper proposes a robust and energy-efficient wireless sensor network framework that integrates vice-cluster-head–based routing, radio-frequency energy harvesting–aware power control with large-scale fading decoding, and turbo trellis coded modulation to enhance reliability and transmission performance. The proposed design improves network robustness through backup-assisted clustering, efficient use of harvested energy via fairness-based power allocation, and reliable data transmission without bandwidth expansion. Simulation results demonstrate substantial performance gains over conventional protocols. The proposed system achieves a network lifetime of 1300 ± 137 h, representing improvements of 20.3% over vice-cluster-head low-energy adaptive clustering hierarchy routing and 57.8% over the low-energy adaptive clustering hierarchy protocol, while energy efficiency increases to 89%. Latency is reduced to 3.8 ± 0.2 ms, and spectral efficiency reaches 5.34 bps/Hz, exceeding the max–min fairness benchmark by up to 151% under wireless power transfer constraints. Parameter analysis further shows that a downlink energy harvesting duration of 25 channel uses provides an effective balance between lifetime and throughput, while shared pilot allocation with moderate pilot length ensures reliable channel estimation. These results demonstrate that the proposed framework provides a practical and high-performance solution for radiometry-monitoring applications requiring continuous operation, efficient energy usage, and reliable data transmission.