The LoRa Modulation Over Rapidly-Varying Channels: Are the Higher Spreading Factors Necessarily More Robust?

09/02/2020
by   Harishwar Reddy Bapathu, et al.
0

The chirp spread spectrum (CSS) modulation scheme is employed by the physical layer of the Long Range (LoRa) communication technology. In this paper, we examine the performance of CSS over time-varying channels whose gain may change during the reception of a LoRa frame. This is in contrast to the usually employed model in the literature, which assumes the channel gain to be constant throughout a frame. Specifically, we investigate the effects of exponentially correlated Rayleigh fading on the frame-error rate of a CSS receiver in which the channel gain is estimated at the beginning of each frame. Our primary observation is that over rapidly-varying channels, the robustness benefits of the larger spreading factors tend to disappear as the payload size grows. This observation, which is contrary to the common perception that higher spreading factors necessarily provide greater immunity against noise, highlights the need to consider channel characteristics and payload sizes in allocating the spreading factor for reliable and energy-efficient LoRa communications.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/23/2018

On the Diversity of OTFS Modulation in Doubly-Dispersive Channels

Orthogonal time frequency space (OTFS) is a 2-dimensional (2D) modulatio...
research
03/23/2022

Deep Channel Prediction: A DNN Framework for Receiver Design in Time-Varying Fading Channels

In time-varying fading channels, channel coefficients are estimated usin...
research
09/16/2023

Differential Modulation for Short Packet Transmission in URLLC

One key feature of ultra-reliable low-latency communications (URLLC) in ...
research
03/18/2021

On the Characterizations of OTFS Modulation over multipath Rapid Fading Channel

Orthogonal time frequency space (OTFS) modulation has been confirmed to ...
research
07/16/2020

Robust adaptive steganography based on dither modulation and modification with re-compression

Traditional adaptive steganography is a technique used for covert commun...
research
09/16/2019

Statistical and Machine Learning-based Decision Techniques for Physical Layer Authentication

In this paper we assess the security performance of key-less physical la...
research
05/16/2018

Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks

Channel modeling is a critical topic when considering designing, learnin...

Please sign up or login with your details

Forgot password? Click here to reset