Long range (LoRa) demonstrates high potential in supporting massive Internet-of-Things (IoT) applications. In this paper, we study the resource allocation in energy harvesting (EH)-enabled LoRa networks with imperfect spreading factor (SF) orthogonality. We maximize the user fairness in terms of the minimum time-averaged throughput while jointly optimizing the SF assignment, the EH time duration, and the transmit power of all LoRa users. First, we provide a general expression of the packet collision time between LoRa users which depends on the SFs and EH duration requirements of each user. Then, we develop two SF allocation schemes that either assure fairness or not for the LoRa users. Within this, we optimize the EH time and the power allocation for single and multiple uplink transmission attempts. For the single uplink transmission attempt, the optimal power allocation is obtained using bisection method. For the multiple uplink transmission attempts, the suboptimal power allocation is derived using concave-convex procedure (CCCP). Our results unearth new findings. Firstly, we demonstrate that the unfair SF allocation algorithm outperforms the others in terms of the minimum data rate. Additionally, we observe that co-SF interference is the main limitation in the throughput performance, and not really energy scarcity.

中文翻译：

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SF 正交性不完美的基于能量收集的 LoRa 网络中的用户公平性

远程 (LoRa) 显示出在支持大规模物联网 (IoT) 应用程序方面的巨大潜力。在本文中，我们研究了具有不完美扩展因子 (SF) 正交性的启用能量收集 (EH) 的 LoRa 网络中的资源分配。我们在最小时间平均吞吐量方面最大化用户公平性，同时联合优化所有 LoRa 用户的 SF 分配、EH 持续时间和发射功率。首先，我们提供了 LoRa 用户之间数据包冲突时间的一般表达式，这取决于每个用户的 SF 和 EH 持续时间要求。然后，我们开发了两种 SF 分配方案，以确保 LoRa 用户的公平性或不公平性。在此范围内，我们优化了单个和多个上行链路传输尝试的 EH 时间和功率分配。对于单次上行传输尝试，使用二分法获得最佳功率分配。对于多个上行链路传输尝试，次优功率分配是使用凹凸过程 (CCCP) 得出的。我们的结果揭示了新的发现。首先，我们证明了不公平 SF 分配算法在最小数据速率方面优于其他算法。此外，我们观察到 co-SF 干扰是吞吐量性能的主要限制，而不是真正的能源稀缺。