On the Error Rate of the LoRa Modulation with Interference

Abstract

LoRa is a chirp spread-spectrum modulation developed for the Internet of Things. In this work, we examine the performance of LoRa in the presence of both additive white Gaussian noise and interference from another LoRa user. To this end, we extend an existing interference model, which assumes perfect alignment of the signal of interest and the interference, to the more realistic case where the interfering user is neither chip- nor phase-aligned with the signal of interest and we derive an expression for the error rate. We show that the existing aligned interference model overestimates the effect of interference on the error rate. Moreover, we prove two symmetries in the interfering signal and we derive low-complexity approximate formulas that can significantly reduce the complexity of computing the symbol and frame error rates compared to the complete expression. Finally, we provide numerical simulations to corroborate the theoretical analysis and to verify the accuracy of our proposed approximations.

Accepted for publication in IEEE Transactions on Wireless Communications, arXiv admin note: substantial text overlap with arXiv:1905.00439

References in corpus (6)

• Understanding the limits of LoRaWAN
• Low Power Wide Area Network Analysis: Can LoRa Scale?
• On the LoRa Modulation for IoT: Waveform Properties and Spectral Analysis
• Analysis of Latency and MAC-layer Performance for Class A LoRaWAN
• Mathematical model of LoRaWAN channel access with capture effect
• LoRa Symbol Error Rate Under Non-Chip- and Non-Phase-Aligned Interference

Cited by in corpus (11)

• A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges
• A Low-Complexity LoRa Synchronization Algorithm Robust to Sampling Time Offsets
• LoRa-RL: Deep Reinforcement Learning for Resource Management in Hybrid Energy LoRa Wireless Networks
• Theoretical Performance of LoRa System in Multi-Path and Interference Channels
• Analysis of the reliability of LoRa
• HybNet: A Hybrid Deep Learning -- Matched Filter Approach for IoT Signal Detection
• LoRa Backscatter Communications: Temporal, Spectral, and Error Performance Analysis
• Union Bounds on the Symbol Error Probability of LoRa Modulation for Flat Rician Block Fading Channels
• Design and Performance Analysis of a New STBC-MIMO LoRa System
• LoRa Fine Synchronization with Two-Pass Time and Frequency Offset Estimation
• Performance Analysis of a Two-Hop Relaying LoRa System