论文标题
一种新型的PHY层方法，用于使用自适应符号周期来提高LORA的数据速率
A Novel PHY Layer Approach for Enhanced Data Rate in LoRa using Adaptive Symbol Periods
论文作者
论文摘要
Lorawan已成为有前途的低功率广阔网络网络技术之一，可在物联网中实现远程感应和监视应用程序。 Lorawan中使用的Lora物理层的数据速率较低，因此增加了数据包持续时间。在密集的Lorawan网络方案中，具有简单的媒体访问协议（例如Aloha），数据包碰撞概率随数据包持续时间的增加而增加。由于对碰撞数据包的重新推荐增加，这会降低全部网络吞吐量。数据速率的任何增加都可以直接降低数据包持续时间。因此，在本文中，我们提出了一种新颖的方法来通过使用物理层中的自适应符号周期来提高洛拉通信系统中的数据速率。据我们所知，这是首次尝试使用自适应符号时期来提高LORA系统数据速率的尝试。还分析了拟议方法在符号降低时所需的符号开销和位误差性能下降的权衡。我们已经表明，对于还原因子\（β\），数据速率直接增加\（1/β\）次。
LoRaWAN has emerged as one of the promising low-power wide-area network technologies to enable long-range sensing and monitoring applications in Internet of Things. The LoRa physical layer used in LoRaWAN suffers from low data rates and thus increases packet duration. In a dense LoRaWAN network scenario with simple media access protocol like ALOHA, the packet collision probability increases with increase in packet duration. This degrades over-all network throughput because of increased re-transmissions of collided packets. Any increase in data rate directly reduces the packet duration. Thus, in this paper, we have proposed a novel approach to enhance the data rate in LoRa communication system by using adaptive symbol periods in physical layer. To the best of our knowledge, this is the first attempt at using adaptive symbol periods to enhance data rate of the LoRa system. The trade-off of the proposed approach in terms of required symbol overhead and degradation in bit error rate performance due to symbol period reduction has also been analysed. We have shown that for reduction factor \(β\), the data rate directly increases \(1/β\) times.
