# An Adaptive Data Rate Algorithm for Power-Constrained End Devices in Long Range Networks
## 1 Introduction  
LoRa (long range), proposed by Semtech, employs chirp spread spectrum technology. In low-power wide area networks (LPWAN), LoRa offers advantages such as low power consumption, long transmission distance, strong anti-interference capability, and high network capacity [1]. LoRaWAN, built on LoRa technology, is suitable for a variety of remote IoT applications. Since end devices are often deployed in environments that are difficult to maintain and rely on battery power, they need to operate in a low-power state for extended periods to prolong battery life. The physical layer of LoRa technology employs specific modulation and coding schemes [2, 3], allowing devices to select an appropriate data transmission rate based on the scenario. The data rate is adjusted by configuring the spreading factor (SF) and bandwidth(BW), and signals with different SFs do not interfere with each other. Gateways in a LoRa network can simultaneously demodulate LoRa signals with different SFs and BWs. LoRaWAN (long range wide area network), an open standard maintained by the LoRa Alliance, operates as an MAC layer protocol on top of LoRa and is designed to handle traffic from large numbers of low-power devices. LoRa technology is widely used in applications such as smart homes, precision agriculture [4; 5], smart metering, and remote healthcare [6; 7], favored for its low cost, long transmission distance, ease of deployment, and excellent scalability. Its chirp spread spectrum modulation technology allows flexible adjustment of the data rate, achieving wide coverage and low power consumption. In practical operation, the link of a LoRa network is affected by the low power consumption of EDs and environmental factors. The communication link is unstable and time-varying, requiring an evaluation and optimization of link stability. Since Class A EDs in LoRa networks use the ALOHA scheme for transmission, a fixed data rate cannot guarantee optimal network performance. The typical architecture of a LoRaWAN network includes end devices (EDs), gateways (GWs), network server (NS), and application server (AS), as shown in Figure 1. The GW and EDs use a star topology, where the ED transmits data to the GW using LoRa modulation. The GW forwards the data to the NS, which processes the data and sends them to the application server. The GW is responsible only for data forwarding and does not participate in data processing. Most existing adaptive data rate (ADR) algorithms are based on the LoRaWAN architecture, primarily operating on the NS side and typically optimizing only the uplink communication link of EDs or certain aspects of network performance [8]. To address this limitation, this paper first establishes an evaluation model for the stability and reliability of the communication link. Then, based on the characteristics of data transmission from EDs in a LoRa network, models for ED power consumption, network throughput, and ED latency are constructed. Based on these models, an ADR algorithm is proposed that optimizes overall network performance based on the communication link state. Through a two-level optimization--link state and network performance--the algorithm aims to reduce ED power consumption while improving network performance. The remainder of this paper is organized as follows. Section 2 reviews the current research on ADR algorithms for LoRa networks. Section 3 constructs a link state evaluation model using the weighted combination method based on the characteristics of LoRa communication links. Section 4 determines the performance evaluation methods for LoRa networks by establishing models for network throughput, average power consumption of EDs, and average latency of EDs. Section 5 introduces the algorithm for obtaining selectable parameters for EDs based on link state and the ADR control method based on network performance optimization. Section 6 presents the verification and analysis of the algorithm. Section 7 summarizes the paper and describes future work to be carried out. Figure 1: LoRaWAN network architecture.