# LoRa Resource Allocation Algorithm for Higher Data Rates
## 1 Introduction  
LoRa modulation is widely recognized for its long-range, low-power transmission capabilities, making it an attractive option for a broad spectrum of applications. Its efficiency and cost-effectiveness have made LoRa particularly suitable for use in cases that require low data rates, such as environmental monitoring, smart agriculture, and IoT networks. However, the low data rates inherent to LoRa present a challenge for applications that demand higher throughput, such as video surveillance, disaster monitoring, and plant phenotyping. These applications often require the transmission of large image files over long distances in areas where reliable communication infrastructure is lacking. Given its low complexity and energy efficiency, LoRa holds promise in such scenarios. Yet, the existing technology can result in prolonged transmission times, especially when dealing with high-resolution images or when operating under less-than-ideal channel conditions. To address these limitations, research has been focused on enhancing LoRa's performance, aiming to increase its data rate while maintaining its key advantages. In 2016, [PERSON] [1] took the first step towards transmitting images, only a year after the birth of the LoRa framework. In this research, a low-cost, low-power image sensor is presented that implements an image compression technique to reduce the data size for long-range transmissions. [PERSON] et al. [2] proposed an image transmission techniquewith various spreading factors (SFs) which utilized three separate nodes operating on different SFs to collaborate in sending images to their designated peers on the receiver side. Each LoRa node is controlled by a dedicated Raspberry pi and the data segments of the image are distributed among the senders using MQTT protocol. [PERSON] et al. (2019) proposed a lightweight and reliable communication protocol called MPLR, specifically designed for image dispatching over LoRa networks in an agricultural IoT platform. The MPLR protocol optimizes packet transmission by grouping information packets and utilizing bit-vector acknowledgments, which reduces the number of acknowledgment packets required and the associated wait times. To further minimize packet collisions caused by network congestion, MPLR employs a separate channel for transmitting request packets, distinct from the channels used for data and acknowledgment signals. Achieving higher data rates in LoRa communications is also possible by upgrading the modulation technique. However, any modifications to LoRa modulation will render the existing modules incompatible with current applications and new hardware design will be required, resulting in increased complexity. In this paper, we have introduced the LoRa Resource Allocation (LRA) algorithm capable of parallel transmissions of the same data, reducing the total transmission time (\(T_{tx}\)) and increasing the Bit Rate (BR). Inspired by the quasi-orthogonality of Spreading Factors (SFs) in LoRa (2019, 2019), our proposed algorithm utilizes specially designed end devices that consist of two LoRa transceivers connected to a single controller unit, ensuring simple hardware implementation. For the experimental analysis, an image transmission application is chosen. We have investigated all possible parameter combinations affecting \(T_{tx}\) to identify the optimal results in terms of interference, BR, and received image quality. Experimental results show that the proposed algorithm can significantly improve the \(T_{tx}\) and BR compared to a typical LoRa framework for a Line of Sight (LoS) communication link while maintaining a high image quality. The main contributions of this research are as follows:  
1. Proposes a specially designed end device (DED) to practically evaluate the quasi-orthogonality feature of LoRa in SF and RF channels and suggests optimal SF combinations for parallel transmission;
2. Proposes a lightweight, synchronized resource-allocation algorithm for transmission time and bit rate improvement;
3.