Communication control and information integration for sensor networks

首先，通过降低通信开销，提高了传感器节点的工作时间，同时也提高了整个观测区域的覆盖时间。其次，作为对发射机放大器功率节省的贡献，本研究提出了基于遗传算法的OFDM信号峰值功率降低方法。此外，作为有效的信息集成技术，本研究提出了基于集成学习的矢量量化算法，具有良好的泛化能力和良好的时间效率。

Firstly, this study improved the operating time of sensor nodes by reducing the communication cost and also improved the coverage time of the whole observation area. Secondary, as a contribution to the power saving of transmitter amplifier, this study proposed GA based peak power reduction methods for OFDM signal. Further, as effective information integration techniques, this study proposed vector quantization algorithms based on ensemble learning that have good generalization ability and good time efficiency.