Integrated RF Transceiver Design and System-Level Validation for Smart Wireless Sensor Networks
Keywords:
RF Transceiver, Wireless Sensor Networks, Low-Power CMOS, Smart IoT, System-Level Validation, Energy Efficiency, Adaptive CommunicationAbstract
Smart Wireless Sensor Networks (WSNs) demand highly integrated, energy-efficient, and interference-resilient RF transceivers capable of sustaining reliable communication in dynamic and resource-constrained environments. This paper presents the design, implementation, and comprehensive system-level validation of a low-power CMOS-based integrated RF transceiver specifically engineered for smart WSN applications operating in the 2.4 GHz ISM band. The proposed architecture incorporates an inductively degenerated low-noise amplifier, quadrature direct-conversion mixer, fractional-N frequency synthesizer, adaptive Class-AB power amplifier, and digitally controlled baseband processing with energy-aware MAC integration. A cross-layer optimization strategy is employed to co-design RF front-end performance with adaptive transmit power control based on real-time RSSI feedback, thereby minimizing unnecessary energy expenditure. Circuit-level simulations are conducted using HSPICE, while system-level performance, including BER and interference tolerance, is validated through MATLAB-based modeling. Hardware-in-the-loop (HIL) experimentation and a 25-node real-time deployment further verify practical feasibility under realistic interference and environmental conditions. The implemented transceiver achieves a receiver sensitivity of −92 dBm, noise figure of 1.9 dB, power-added efficiency of 38%, and bit error rate below 10⁻⁶, while demonstrating a 27% reduction in overall energy consumption compared to conventional IEEE 802.15.4-based modules. Experimental results confirm improved packet delivery ratio, reduced retransmissions, and extended node lifetime through adaptive power scaling. The proposed integrated solution provides a scalable and deployment-ready platform for smart agriculture, industrial monitoring, environmental sensing, and healthcare Internet of Things (IoT) applications.