School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea.
Research Institute for Computer and Information Communication, Chungbuk National University, Cheongju 28644, Republic of Korea.
Sensors (Basel). 2022 Nov 30;22(23):9332. doi: 10.3390/s22239332.
Long range (LoRa) is one of the most successful low-power wide-area networking technologies because it is ideally suited for long-distance, low-bit rate, and low-power communications in the unlicensed sub-GHz spectrum utilized for Internet of things (IoT) networks. The effectiveness of LoRa depends on the link budget (i.e., spreading factor (SF), bandwidth (BW), and transmission power (TX)). Due to the near-far effect, the allocation of a link budget to LoRa devices (LDs) in large coverage regions is unfair between them depending on their distance to the GW. Thus, more transmission opportunities are given to some LDs to the detriment of other LD's opportunities. Numerous studies have been conducted to address the prevalent near-far fairness problem. Due to the absence of a tractable analytical model for fairness in the LoRa network, however, it is still difficult to solve this problem completely. Thus, we propose an SF-partition-based clustering and relaying (SFPCR) scheme to achieve enormous LD connectivity with fairness in IoT multihop LoRa networks. For the SF partition, the SFPCR scheme determines the suitable partitioning threshold point for bridging packet delivery success probability gaps between SF regions, namely, the lower SF zone (LSFZ) and the higher SF zone (HSFZ). To avoid long-distance transmissions to the GW, the HSFZ constructs a density-based subspace clustering that generates clusters of arbitrary shape for adjacent LDs and selects cluster headers by using a binary score representation. To support reliable data transmissions to the GW by multihop communications, the LSFZ offers a relay LD selection that ideally chooses the best relay LD to extend uplink transmissions from LDs in the HSFZ. Through simulations, we show that the proposed SFPCR scheme exhibits the highest success probability of 65.7%, followed by the FSRC scheme at 44.6%, the mesh scheme at 34.2%, and lastly the cluster-based scheme at 29.4%, and it conserves the energy of LDs compared with the existing schemes.
长距离 (LoRa) 是最成功的低功耗广域网技术之一,因为它非常适合在未经许可的 sub-GHz 频谱中进行远距离、低比特率和低功耗通信,这些频谱用于物联网 (IoT) 网络。LoRa 的有效性取决于链路预算(即,扩频因子 (SF)、带宽 (BW) 和传输功率 (TX))。由于远近效应,在大面积覆盖区域中,为 LoRa 设备 (LD) 分配链路预算对它们来说是不公平的,这取决于它们到 GW 的距离。因此,一些 LD 获得了更多的传输机会,而其他 LD 的机会则受到损害。已经进行了许多研究来解决普遍存在的远近公平性问题。然而,由于 LoRa 网络中公平性没有可行的分析模型,因此仍然很难完全解决这个问题。因此,我们提出了一种基于 SF 分区的聚类和中继 (SFPCR) 方案,以在物联网多跳 LoRa 网络中实现巨大的 LD 连接和公平性。对于 SF 分区,SFPCR 方案确定了用于桥接 SF 区域之间分组投递成功率差距的合适分区阈值点,即较低的 SF 区域 (LSFZ) 和较高的 SF 区域 (HSFZ)。为了避免向 GW 进行远距离传输,HSFZ 构建了基于密度的子空间聚类,为相邻 LD 生成任意形状的簇,并使用二进制分数表示选择簇头。为了通过多跳通信支持可靠的数据传输到 GW,LSFZ 提供了一种中继 LD 选择,理想情况下选择最佳的中继 LD 来扩展来自 HSFZ 中 LD 的上行链路传输。通过仿真,我们表明,所提出的 SFPCR 方案表现出最高的成功概率 65.7%,其次是 FSRC 方案 44.6%、网格方案 34.2%,最后是基于簇的方案 29.4%,与现有方案相比,它还能节省 LD 的能量。