Design of RIS-Aided Differential Reflecting LoRa Modulation With Fractional Spreading Factors

Abstract

The rapid proliferation of the Internet of Things (IoT) demands wireless technologies balancing energy efficiency, long-range coverage, and reliable transmission. As a leading low-power wide-area network (LPWAN) solution, LoRa modulation excels in robustness and low-power consumption but faces bottlenecks of limited spectral efficiency (SE) and vulnerability to fading channel constraints for 6G-enabled high-throughput IoT applications. To address these issues, this paper proposes a novel reconfigurable intelligent surfaces aided differential reflecting LoRa modulation with fractional spreading factors (termed as FSF-LoRa-RIS-DRM). The proposed system boosts symbol capacity without expanding bandwidth via fractional spreading factors, and enables the transmission of extra bits through permutations of RIS reflection patterns. Moreover, the proposed system operates without channel state information (CSI) at the receiver, thus eliminating pilot overhead and reducing communication costs. We derive closed-form expressions for the bit error rate (BER), SE, and throughput of the proposed system over Rayleigh fading channels. Extensive simulations validate the theoretical analysis and demonstrate that FSF-LoRa-RIS-DRM outperforms conventional LoRa, phase-shift keying LoRa (PSK-LoRa), and RIS-assisted differential PSK LoRa (LoRa-RIS-DPSK) in terms of SE and reliability. Due to the above advantages, the proposed system provides a promising pathway toward high-throughput, channel-estimation-free, and robust IoT connectivity, aligning with the requirements of future 6G networks for smart cities, industrial automation, and precision agriculture.