Low-Cost Software Defined Radio Solutions for High Altitude Applications
Abstract
LoRa (Long Range) and LoRaWAN (Long Range Wide Area Network) are complementary technologies designed to enable low-power, long-range wireless communication for Internet of Things (IoT) applications. LoRa operates at the physical layer using Chirp Spread Spectrum (CSS) modulation, which encodes data using chirp signals—linear frequency sweeps that offer resilience to noise and Doppler effects. The spreading factor (SF) and bandwidth (BW) are critical parameters in LoRa modulation: increasing the spreading factor improves range and noise immunity but decreases data rate, whereas increasing bandwidth allows for higher data rates at the cost of receiver sensitivity. LoRaWAN operates at the MAC (Media Access Control) and network layers, providing standardized communication protocols and secure data exchange. Understanding how data rate impacts bandwidth and system performance is essential for optimizing throughput, battery life, and range in real-world deployments. Software-defined radios (SDRs) are commonly used to evaluate and monitor these signals. Devices like the RTLSDR offer an ultra-low-cost solution suitable for fundamental spectral analysis but are limited in frequency range and transmit capability. In contrast, the Analog Devices PlutoSDR and the HackRF One by Great Scott Gadgets provide more extensive frameworks: the PlutoSDR supports full-duplex operation and is tightly integrated with ADI's libiio framework, offering high flexibility for embedded development. The HackRF, while half-duplex, offers broad frequency coverage and robust community support. Price and architectural flexibility further differentiate these SDR platforms, influencing their suitability for LoRa/LoRaWAN experimentation and deployment.
Keywords: Software-Defined, Radio, LoRa, LoRaWAN, SDR, Pluto, RTL-SDR, HackRF
How to Cite:
Beaver, B. M. & Nelson, M. E., (2025) “Low-Cost Software Defined Radio Solutions for High Altitude Applications”, Academic High Altitude Conference 2025(1). doi: https://doi.org/10.31274/ahac.20210
Downloads:
Download PDF
View PDF
434 Views
121 Downloads
