# LoRa Resource Allocation Algorithm for Higher Data Rates
## 2 Related Work  
Recent studies in the literature have explored various methods to enhance the data rate of LoRa by modifying its Chirp Spread Spectrum (CSS) modulation. [PERSON] et al. (2019) proposed the use of Interleaved Chirp Spreading (ICS) alongside traditional chirp spreading. This technique incorporates an additional bit into the LoRa symbol for ICS, leading to a 42% increase in capacity. Building on this concept, a Slope Shift Keying (SSK) approach with ICS was introduced in (2019), which utilizes a combination of up, down, and interleaved up-and-down chirp modulation. This method further boosts the data rate, achievinga 28.6% improvement compared to the standard CSS LoRa with the same SF and BW. [PERSON] [8] proposed a new index modulation for LoRa that utilizes multiple quasi-orthogonal chirps modulated under different SFs, enabling it to carry more information compared to the conventional LoRa. [PERSON] et al. [9] introduced the frequency shift chirp spread spectrum modulation that exploits index modulation (FSCSS-IM) to increase the data rate. Instead of one chirp at a time, FSCSS-IM transmits multiple chirps simultaneously. In [10], Time-Domain Multiplexing (TDM) is employed for LoRa modulation, distributing bits of a symbol across different SFs. This method doubles the data rate with a minor degradation in BER, particularly at the lower SF of 7. Additionally, in [11], authors introduced a data rate enhancement approach known as PATCH (Phase-based Additional Channel), which utilizes the phase of the chirp signal as an additional channel. This technique can boost the BR by up to 28.57% for SF = 7. [PERSON] et al. [12] introduced a cooperative framework for transmitting large files over LoRa. They developed an algorithm that leverages neighboring nodes, selecting them based on their SF and packet success rate to share portions of the data. To facilitate communication between nodes, the framework utilizes a high data rate medium like Wi-Fi for exchanging algorithmic messages among the neighbors. Some research efforts have proposed enhancements to the network access techniques for the LoRa communication protocol. For instance, a dynamic spreading factor allocation algorithm was introduced in [13] to maximize the data rate for the communication link. This algorithm optimizes the data rate by considering the hop count, ensuring that higher SFs are assigned to links with fewer hops or clusters that are closer, thereby equalizing the packet travel time or Time on Air (ToA). The approach is capacity-focused, utilizing an iterative process to allocate SFs, enhancing overall network performance. The LoRaWAN Gateway (GW) is not full-duplex, and relies on an Adaptive Data Rate (ADR) to adjust the SF. However, this adjustment becomes impractical when the GW is mobile at speeds above 2 km/h. In such scenarios, the GW must frequently switch SF and channels to communicate with end devices (EDs), leading to significant overhead and reducing goodput to as low as 20%. To address this, Cantor [14] was implemented in a single-GW LoRaWAN network to gather network parameters from EDs, optimize the Packet Reception Rate (PRR), and estimate the actual downlink (DL) PRR using an optimization algorithm. By employing a regression model (WW: Wane and Wax, representing alternate increase and decrease), Cantor more accurately determines PRR and improves goodput by up to 70%. Additionally, Cantor's use of windowing for acknowledgments (ACK) shows better performance with higher SFs. The distance-based SF allocation using the Exponential Windowing Scheme (EWS) [15] is designed to reduce co-SF interference and improve network capacity. This approach utilizes an offline optimization algorithm, making it particularly effective for static EDs. The method achieves a PDR improvement of 18.2% to 55.25% compared to similar SF allocation algorithms. However, a significant drawback is the exponential decrease in data throughput as the number of EDs increases from 1000 to 8000.