研究目的
Investigating the design of efficient receivers compliant with IEEE 802.15.4 for low power IoT applications, focusing on a robust phase noise compensation method and a dual-mode receiver to cater to diverse IoT applications.
研究成果
The proposed DSSS-aided residual phase noise compensation method and dual-mode receiver significantly improve error rate performance for critical IoT applications and optimize power consumption for sustainable applications. The receiver's adaptability to channel conditions and application requirements demonstrates its potential for diverse IoT applications, with future work focusing on integration with low-power RF sections for fully integrated solutions.
研究不足
The proposed method may not perform optimally in rapidly changing communication environments, such as vehicular networks or ocean sensor mesh networks, due to the need for rapid mode switching which could increase latency and power consumption.
1:Experimental Design and Method Selection:
The study involves the design and implementation of a dual-mode receiver with a novel residual phase noise compensation algorithm. The methodology includes theoretical models for phase noise compensation and detailed procedures for FPGA prototyping and ASIC implementation.
2:Sample Selection and Data Sources:
The experiments utilize IEEE 802.15.4 compliant signals with introduced frequency offset and AWGN noise to simulate channel conditions.
3:4 compliant signals with introduced frequency offset and AWGN noise to simulate channel conditions.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: The study employs Xilinx Kintex-7 FPGA KC705 for prototyping and UMC 0.18 μm CMOS technology for ASIC implementation.
4:18 μm CMOS technology for ASIC implementation.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The workflow includes signal generation with specified parameters, application of the proposed phase noise compensation method, and performance evaluation in terms of BER, PER, power consumption, and hardware utilization.
5:Data Analysis Methods:
Performance metrics such as BER, PER, and power consumption are analyzed using MATLAB simulations and hardware measurements.
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