Literature Database Entry


Sascha Rösler, "Opportunistic Routing in LoRa-based Wireless Mesh Networks," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), October 2022. (Advisor: Anatolij Zubow; Referees: Falko Dressler and Thomas Sikora)


LoRa is a promising technology for the growing area of the wide range Internet of Things (IoT). This thesis presents a mesh network using a preconfigured modulation scheme to overcome the range reduction of LoRa in the 2.4 GHz band. In detail, this thesis analyses the End-to-End (E2E) Packet Error Rate (PER), the E2E delay and the channel usage of a Cross-Layer (CL) routing protocol, of an Opportunistic Routing (OR) routing protocol and of a traditional routing protocol on slow fading channels. OR enables macro spacial diversity by using different nodes as receivers of the same transmission. The presented simulator LoRaNetworkNodeSim simulates networks on Medium Access Control (MAC) layer level. The results of the simulation show that OR is the best routing protocol in case of a dense network. Nevertheless, it needs more channel resources if the network is sparse. Improving the traditional routing protocol with a strategy of using only links with a given link budget or decreasing the beacon interval with its network topology updates do not reduce the E2E PER as much as the OR protocol does.

Quick access

BibTeX BibTeX


Sascha Rösler

BibTeX reference

    author = {R{\"{o}}sler, Sascha},
    title = {{Opportunistic Routing in LoRa-based Wireless Mesh Networks}},
    advisor = {Zubow, Anatolij},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {10},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Master's Thesis},
    year = {2022},

Copyright notice

Links to final or draft versions of papers are presented here to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or distributed for commercial purposes without the explicit permission of the copyright holder.

The following applies to all papers listed above that have IEEE copyrights: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

The following applies to all papers listed above that are in submission to IEEE conference/workshop proceedings or journals: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

The following applies to all papers listed above that have ACM copyrights: ACM COPYRIGHT NOTICE. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or

The following applies to all SpringerLink papers listed above that have Springer Science+Business Media copyrights: The original publication is available at

This page was automatically generated using BibDB and bib2web.

Last modified: 2024-07-16