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Optimizing the Performance of Pure ALOHA for LoRa-Based ESL

机译:优化纯Aloha对基于Lora的ESL的性能

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摘要

(1) Background: The scientific development in the field of industrialization demands the automization of electronic shelf labels (ESLs). COVID-19 has limited the manpower responsible for the frequent updating of the ESL system. The current ESL uses QR (quick response) codes, NFC (near-field communication), and RFID (radio-frequency identification). These technologies have a short range or need more manpower. LoRa is one of the prominent contenders in this category as it provides long-range connectivity with less energy harvesting and location tracking. It uses many gateways (GWs) to transmit the same data packet to a node, which causes collision at the receiver side. The restriction of the duty cycle (DC) and dependency of acknowledgment makes it unsuitable for use by the common person. The maximum efficiency of pure ALOHA is 18.4%, while that of slotted ALOHA is 36.8%, which makes LoRa unsuitable for industrial use. It can be used for applications that need a low data rate, i.e., up to approximately 27 Kbps. The ALOHA mechanism can cause inefficiency by not eliminating fast saturation even with the increasing number of gateways. The increasing number of gateways can only improve the global performance for generating packets with Poisson law having a uniform distribution of payload of 1~51 bytes. The maximum expected channel capacity usage is similar to the pure ALOHA throughput. (2) Methods: In this paper, the improved ALOHA mechanism is used, which is based on the orthogonal combination of spreading factor (SF) and bandwidth (BW), to maximize the throughput of LoRa for ESL. The varying distances (D) of the end nodes (ENs) are arranged based on the K-means machine learning algorithm (MLA) using the parameter selection principle of ISM (industrial, scientific and medical) regulation with a 1% DC for transmission to minimize the saturation. (3) Results: The performance of the improved ALOHA degraded with the increasing number of SFs and as well ENs. However, after using K-mapping, the network changes and the different number of gateways had a greater impact on the probability of successful transmission. The saturation decreased from 57% to 1~2% by using MLA. The RSSI (Received Signal Strength Indicator) plays a key role in determining the exact position of the ENs, which helps to improve the possibility of successful transmission and synchronization at higher BW (250 kHz). In addition, a high BW has lower energy consumption than a low BW at the same DC with a double-bit rate and almost half the ToA (time on-air).
机译:(1)背景:在工业化领域的科学发展要求的电子货架标签(电子货架标签)的automization。 COVID-19具有有限责任的ESL系统的频繁更新的人力。当前ESL使用QR(快速响应)码,NFC(近场通信),和RFID(射频识别)。这些技术在短距离或需要更多的人手。劳拉是该类别中的突出竞争者之一,因为它提供了更能量收集和位置跟踪远程连接。它使用了许多网关(GW的),以相同的数据包发送到一个节点,该节点在接收器侧引起碰撞。占空比(DC)和确认的相关性的限制使得它不适合由普通人使用。纯ALOHA的最大效率是18.4%,而时隙ALOHA的是36.8%,这使得LORA不适于工业用途。它可用于需要低数据速率应用,即,高达大约27 Kbps的。阿罗哈机制可以通过不消除快速饱和,甚至有越来越多的网关会导致效率低下。越来越多的网关只能改善与具有1〜51个字节的有效载荷的均匀分布泊松法生成分组的全局性能。预期的最大信道容量的使用类似于纯ALOHA吞吐量。 (2)方法:在本文中,使用了改进ALOHA机制,该机制是基于扩展因子(SF)和带宽(BW),以最大化LORA的吞吐量为ESL的正交组合。端节点(ENS)的变化的距离(d)被布置基于使用ISM(工业,科学和医疗)用1%的DC调节用于传输到的参数的选择原则的K均值机器学习算法(MLA)尽量减少饱和度。 (3)结果:改进ALOHA的性能日益增加的数量SF的和以及登记护士降解。然而,使用K-映射后,网络变化和不同数量的网关对成功传输的概率的影响更大。饱和度从57%通过使用MLA降至1〜2%。的RSSI(接收信号强度指示符)在决定的EN的准确位置,这有助于提高成功传输和同步在更高的BW(250千赫兹)的可能性中起关键作用。此外,高的BW具有能耗低于在相同的直流低BW具有双比特率和几乎一半的的ToA(时间上空气)。

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