Master Thesis WiFi HaLow Mesh Network Feasibility Study

Problem statement

This Master Thesis in Software Engineering focuses on the comprehensive evaluation of WiFi HaLow (IEEE 802.11ah) technology for implementing distributed mesh networks in IoT and remote connectivity scenarios. The research combines theoretical analysis empirical testing and practical implementation to assess the viability of WiFi HaLow as a foundation for robust long-range wireless mesh communications.

Research Objectives

The thesis aims to:

• Investigate operational boundaries of WiFi HaLow mesh networks including maximum effective range environmental resilience (weather conditions terrain obstacles) and geographical deployment constraints
• Analyze performance characteristics such as throughput capabilities latency packet loss rates and network stability under varying load conditions
• Conduct market and technology assessment of available WiFi HaLow chipsets compatible microcontrollers/microprocessors and development platforms from current suppliers
• Evaluate mesh networking protocols and their compatibility with WiFi HaLows sub-GHz characteristics including self-healing capabilities and scalability
• Develop a proof-of-concept implementation demonstrating key findings through a functional mesh network prototype with performance benchmarking

Outcomes/Deliverables

The thesis will provide a comprehensive feasibility analysis supported by empirical data a comparative study of existing solutions and a working demonstration that validates theoretical findings.

This research contributes to understanding WiFi HaLows potential for next-generation IoT infrastructure and long-range wireless communications.

You will of course have the opportunity to shape the thesis based on your knowledge skills and discoveries during the project.

Scope of master thesis project

Two students completing 30 credits each (20 weeks) onsite at the Lund office

Qualifications :

Your profile

In order to be successful in the project with think you are:

• Student in Information Technology Computer Science Electronics Math or Physics.
• Required knowledge / courses on data science cybersecurity and AI
• Experienced with or have at least some knowledge of programming in Python C or similar.
• Self-driven able to challenge yourself and gain the experience needed to move the project forward.
• A person with team spirit social skills and a curiosity for exploring new technology areas.

Additional Information :

Why choose Bosch:

In 2022 for the third year in a row Bosch have received the Worlds Best Employer award from Forbes/Statista ranking us among the top 3% of the worlds most attractive employers.

At Bosch we believe that diversity is our strength. We look at diversity in gender generation nationalities and culture as our advantage. We believe mixed teams to be more successful because they utilize the potential offered by different perspectives and solution strategies. We therefore promote mixed teams at all levels and draw on the entire talent pool.

Remote Work :

No

Employment Type :

Part-time