In the last decade, the advancement of the Internet of Things (IoT) has caused unlicensed radio spectrum, especially the 2.4 GHz ISM band, to be immensely crowded with smart wireless devices that are used in a wide range of application domains. Due to their diversity in radio resource use and channel access techniques, when collocated, these wireless devices create interference with each other, known as Cross-Technology Interference (CTI), which can lead to increased packet losses and energy consumption. CTI is a significant problem for low-power wireless networks, such as IEEE 802.15.4, as it decreases the overall dependability of the wireless network. To improve the performance of low-power wireless networks under CTI conditions, we propose a data-driven proactive receiver-aware MAC protocol, LUCID, based on interference estimation and white space prediction. We leverage statistical analysis of real-world traces from two indoor environments characterised by varying channel conditions to develop CTI prediction methods. The CTI models that generate accurate predictions of interference behaviour are an intrinsic part of our solution. LUCID is thoroughly evaluated in realistic simulations and we show that depending on the application data rate and the network size, our solution achieves higher dependability, 1.2% increase in packet delivery ratio and 0.02% decrease in duty-cycle under bursty indoor interference than state of the art alternative methods.
翻译:过去十年来,互联网“东西”的进步导致无证无线电频谱,特别是2.4 GHz ISM波段,导致无证无线电频谱,特别是2.4 GHz ISM波段,在广泛应用领域使用的智能无线装置极为拥挤。由于无线电资源使用和频道接入技术的多样性,这些无线装置在合用同一地点时造成相互干扰,称为跨技术干涉(CTI),这可能导致包装损失和能源消耗增加。CTI是低功率无线网络,如IEEE 802.15.4等低功率无线网络的一个严重问题,因为它降低了无线网络的总体可靠性。为了改进CTI条件下低功率无线网络的性能,我们根据干扰估计和白色空间预测,提出了以数据驱动的主动接收器对MACM协议LUCID。我们利用对两个室内环境真实世界痕迹的统计分析来开发CTI预测方法。CTI产生干扰行为的准确预测模型是我们解决方案的内在部分。LUCID在现实的模拟中进行彻底评估,根据0.02号标准交付率和0.2%的交付率,我们根据0.BMLUF的交付率计算,取决于应用率率的交付率,取决于0.1%的交付率率的交付率。