Saved in:
Bibliographic Details
Main Authors: Hernandez, Mario, Bryce, Elijah, Stubberud, Peter, Saberinia, Ebrahim, Morris, Brendan
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2509.14523
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918143369150464
author Hernandez, Mario
Bryce, Elijah
Stubberud, Peter
Saberinia, Ebrahim
Morris, Brendan
author_facet Hernandez, Mario
Bryce, Elijah
Stubberud, Peter
Saberinia, Ebrahim
Morris, Brendan
contents We present a Software Defined Radio (SDR)-based IEEE 802.11p testbed for distributed Vehicle-to-Vehicle (V2V) communication. The platform bridges the gap between network simulation and deployment by providing a modular codebase configured for cost-effective ADALM-Pluto SDRs. Any device capable of running a Docker with ROS, executing Matlab and interface with a Pluto via USB can act as a communication node. To demonstrate collaborative sensing, we share LiDAR point clouds between nodes and fuse them into a collective perception environment. We evaluated a theoretical model for leveraging decentralized storage systems (IPFS and Filecoin), analyzing constraints such as node storage convergence, latency, and scalability. In addition, we provide a channel quality study.
format Preprint
id arxiv_https___arxiv_org_abs_2509_14523
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Software-Defined Radio Testbed for Distributed LiDAR Point Cloud Sharing with IEEE 802.11p in V2V Networks
Hernandez, Mario
Bryce, Elijah
Stubberud, Peter
Saberinia, Ebrahim
Morris, Brendan
Networking and Internet Architecture
We present a Software Defined Radio (SDR)-based IEEE 802.11p testbed for distributed Vehicle-to-Vehicle (V2V) communication. The platform bridges the gap between network simulation and deployment by providing a modular codebase configured for cost-effective ADALM-Pluto SDRs. Any device capable of running a Docker with ROS, executing Matlab and interface with a Pluto via USB can act as a communication node. To demonstrate collaborative sensing, we share LiDAR point clouds between nodes and fuse them into a collective perception environment. We evaluated a theoretical model for leveraging decentralized storage systems (IPFS and Filecoin), analyzing constraints such as node storage convergence, latency, and scalability. In addition, we provide a channel quality study.
title A Software-Defined Radio Testbed for Distributed LiDAR Point Cloud Sharing with IEEE 802.11p in V2V Networks
topic Networking and Internet Architecture
url https://arxiv.org/abs/2509.14523