mmWave for Rural Wireless

Exploring mmWave as a wireless solution for rural broadband connectivity

This project conducted a comprehensive survey of millimeter-wave (mmWave) technology as a potential wireless solution for rural broadband connectivity.[15] The research addressed the critical digital divide faced by rural communities, where traditional wired infrastructure deployment is often economically unfeasible due to low population density and high infrastructure costs.[2]

Real-World Motivation: This research was directly informed by my practical experience deploying networks at PrairieOaks, a rural community in LeClaire, Iowa. The environmental challenges, connectivity issues, and user needs encountered during that deployment provided critical insights that shaped the theoretical analysis and simulation parameters in this mmWave research.

Table of Contents

  1. Main Goals
  2. Technical Approach
  3. Research Methodology
  4. Technical Challenges and Solutions
  5. Project Deliverables
  6. Learning Outcomes
  7. Simulation Results and Visualizations
  8. Project Impact
  9. Technologies and Tools
  10. References

Main Goals

  1. Conduct comprehensive mmWave technology survey
    • Analyze mmWave as wireless solution for rural broadband connectivity
    • Evaluate performance under various environmental conditions
    • Compare with alternative wireless technologies (TVWS, 5G)
    • Assess economic feasibility for rural deployments

  2. Address rural digital divide challenges
    • Investigate current rural connectivity limitations
    • Analyze cost-effective deployment strategies
    • Evaluate regional collaboration models
    • Develop policy recommendations for rural broadband

  3. Validate theoretical findings through simulation
    • Utilize NYUSIM framework for empirical validation
    • Test performance under various rain conditions
    • Compare 38 GHz vs 75 GHz frequency bands
    • Analyze channel characteristics and path loss modeling

Technical Approach

mmWave Technology Analysis

The project focused on millimeter-wave technology operating in the 30-300 GHz frequency range:

  • Frequency Bands: Primary analysis of 38 GHz and 75 GHz bands for rural deployments
  • Advantages: High throughput (sub-gigabit speeds), low latency, cost-effective deployment
  • Challenges: Rain fade, atmospheric absorption, limited range, environmental sensitivity
  • Applications: Point-to-point links, backhaul networks, rural broadband infrastructure
Key Research Areas

1. Rural Broadband Case Study Analyzed Canadian rural broadband initiatives, particularly the SWIFT (Southwestern Integrated Fibre Technology Inc.) consortium approach:

  • Access Disparity: 87.4% of metropolitan households vs 45.6% of rural households had access to 50 Mbps/10 Mbps speeds
  • Regional Collaboration: Regional models outperform federal-only approaches
  • Community Involvement: Local community participation crucial for successful deployment
  • Policy Implications: Bottom-up approaches more effective than top-down solutions

2. Wireless Network Redundancy & QoS Comprehensive comparison of mmWave with TV White Space (TVWS) technology:

Performance Metrics:[3]

  • mmWave: 12.66 ms RTT, 18.19 ms jitter, sub-gigabit throughput
  • TVWS: 40 ms RTT, 5 ms jitter, ~30 Mbps throughput
  • Failover Strategy: 5 GHz backup radios for environmental mitigation
  • Reliability: mmWave superior for speed, TVWS better for reliability

3. Rain Fade Mitigation Advanced techniques for addressing environmental challenges:

  • Massive MIMO: Increasing antenna count at base stations for improved reliability
  • Statistical Water-Filling (SWF): Near-optimal performance despite imperfect CSI
  • Dynamic Routing: Shortest-path algorithm for traffic rerouting during capacity changes
  • Frequency Selection: 38 GHz vs 75 GHz performance under various rain conditions

Rain Attenuation Findings:[6][7]

  • Low Rain Rates (30-60 mm/h): Minimal signal attenuation, acceptable performance
  • High Rain Rates (60+ mm/h): Significant performance degradation, connection loss possible
  • Frequency Comparison: 38 GHz performs better than 75 GHz under adverse conditions
  • Mitigation Strategies: Power adjustment, frequency switching, adaptive routing
Simulation Framework

Utilized NYUSIM (New York University Simulator) for empirical validation:[1]

  • Rain Rate Testing: Simulated various rainfall conditions (45-130 mm/hr)
  • Frequency Comparison: 38 GHz vs 75 GHz performance analysis
  • Path Loss Modeling: Line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios
  • Power Delay Profile (PDP): Channel characterization under different conditions

Research Methodology

Literature Review Process

Comprehensive analysis of over 15 research papers covering:

  • mmWave Channel Modeling: Statistical models and simulation frameworks
  • Rain Fade Mitigation: Environmental impact analysis and countermeasures
  • Rural Broadband Deployment: Case studies and policy analysis
  • 5G Fixed Wireless: Performance evaluation in rural environments
  • Massive MIMO Systems: Multi-antenna configurations for mmWave
Case Study Analysis

Real-world experience at PrairieOaks, rural community in LeClaire, Iowa:

  • Existing Infrastructure: Multiple Verizon hotspots with inadequate coverage
  • Performance Issues: Data caps, poor peak-hour performance, spotty coverage
  • User Impact: WWOOF/HelpX workers, Sangha Zoom meetings affected
  • Solution Requirements: Reliable, high-speed internet for community needs
Simulation Validation

NYUSIM framework implementation for empirical validation:

  • Parameter Configuration: 300m point-to-point links, directional/omni-directional antennas
  • Environmental Testing: Rain rates 45-130 mm/hr for extreme conditions
  • Frequency Analysis: 38 GHz vs 75 GHz performance comparison
  • Channel Characterization: LOS/NLOS scenarios, power delay profiles

Technical Challenges and Solutions

Rain Fade Mitigation

Challenge: Significant signal attenuation during rainfall, especially at higher frequencies[6] Solution:

  • Implemented massive MIMO systems with increased antenna count[5]
  • Developed statistical water-filling techniques for near-optimal performance[7]
  • Utilized dynamic routing algorithms for traffic rerouting during capacity changes[8]
  • Established frequency selection strategies (38 GHz preferred over 75 GHz)
Frequency Selection

Challenge: Balancing performance vs environmental sensitivity across frequency bands Solution:

  • Comprehensive comparison of 38 GHz vs 75 GHz under various conditions
  • Empirical validation through NYUSIM simulations
  • Performance optimization for rural deployment scenarios
  • Adaptive frequency switching based on environmental conditions
Network Redundancy

Challenge: Ensuring reliable connectivity in rural environments with limited infrastructure[10] Solution:

  • Hybrid deployment strategies combining mmWave with lower-frequency failover[12]
  • Multi-tier user systems with administrative controls
  • Real-time monitoring and adaptive network topology
  • Comprehensive QoS implementation for critical applications[4]

Project Deliverables

Comprehensive Survey Paper
  • Technical Analysis: mmWave technology evaluation for rural deployments
  • Performance Comparison: mmWave vs TVWS and other wireless technologies
  • Environmental Impact: Rain fade analysis and mitigation strategies
  • Economic Assessment: Cost-benefit analysis for rural broadband deployment
Simulation Results
  • NYUSIM Validation: Empirical data supporting theoretical findings
  • Performance Metrics: Throughput, latency, and reliability measurements
  • Environmental Testing: Rain attenuation analysis under various conditions
  • Channel Characterization: Power delay profiles and path loss modeling
Policy Recommendations
  • Regional Collaboration: SWIFT-like consortium models for rural broadband
  • Community Involvement: Local participation in deployment decisions
  • Public-Private Partnerships: Bridging the rural digital divide
  • Infrastructure Planning: Strategic deployment strategies for low-density areas

Learning Outcomes

This project significantly enhanced my technical and research capabilities:

Technical Expertise:

  • mmWave Technology: Deep understanding of millimeter-wave communication systems
  • Simulation Frameworks: NYUSIM implementation and validation techniques
  • Wireless Networks: Rural broadband deployment strategies and challenges
  • Environmental Analysis: Rain fade impact and mitigation techniques

Research Skills:

  • Literature Review: Comprehensive analysis of wireless communication research
  • Case Study Analysis: Real-world problem identification and solution development
  • Simulation Design: Parameter configuration and empirical validation
  • Policy Analysis: Rural broadband initiatives and regional collaboration models

Professional Development:

  • Technical Writing: Comprehensive survey paper development
  • Data Analysis: Simulation results interpretation and presentation
  • Problem-Solving: Environmental challenges and technical mitigation strategies
  • Academic Research: Formal research methodology and documentation

Simulation Results and Visualizations

The NYUSIM simulations provided critical insights into mmWave performance under various environmental conditions. The simulation parameters and results are detailed below:

NYUSIM Parameter Configuration
NYUSIM Parameter Configuration: Simulation framework configured with specific parameters to analyze mmWave performance under various environmental conditions, focusing on rainfall impact and human blockage scenarios.
Path Loss Analysis Under Rainfall Conditions
Path Loss Analysis: Comparison of 38 GHz vs 75 GHz frequency performance under 130 mm/hr rainfall conditions. The analysis demonstrates the significant impact of rainfall on mmWave signal propagation, with 75 GHz showing more severe attenuation compared to 38 GHz under identical conditions.
Rain Attenuation Comparison
Rain Attenuation Comparison: Direct comparison of 38 GHz vs 75 GHz performance across all rain rates. This comparison clearly shows that 75 GHz experiences significantly higher attenuation than 38 GHz across all rain rates, validating the frequency selection strategy for rural deployments.
Power Delay Profile Analysis

Omni-directional Power Analysis:

Omni-directional Power Analysis: Comparison of power delay profiles under clear conditions vs 45 mm/hr rainfall

Directional Power Analysis:

Directional Power Analysis: Beamforming performance comparison under clear vs rainy conditions
Network Performance Analysis
Network Performance Analysis: Effect of number of stations and sectors on saturation throughput. These analyses demonstrate the impact of network density and sector configuration on overall system performance, crucial for rural deployment planning.
Advanced mmWave Applications
Advanced mmWave Applications: Agricultural networks with IoT approach[14], high-speed train scenario performance, and urban intersection scenario performance. These applications demonstrate the versatility of mmWave technology across different deployment scenarios.
System Architecture and Performance
System Architecture and Performance: Multi-node configuration with mobile station, achievable rate analysis under pilot contamination, and absolute path loss analysis at 38 GHz. These analyses provide comprehensive insights into mmWave system performance under various conditions.

Key Simulation Results

  • Rain Attenuation: Significant impact at rates >60 mm/hr
  • Frequency Effects: 75 GHz shows worse attenuation than 38 GHz
  • Throughput Performance: 495 Mbps median case under severe conditions (45 mm/hr)
  • Availability: 99.999% reliability achieved with proper mitigation strategies

Simulation Parameters:

  • Distance: 300m point-to-point links
  • Antennas: Directional and omni-directional configurations
  • Rain Rates: 45, 130 mm/hr for extreme conditions
  • Frequencies: 38 GHz and 75 GHz comparison

Project Impact

This mmWave rural wireless research contributes significantly to addressing the digital divide:

Technical Contributions:

  • Comprehensive Survey: Detailed analysis of mmWave for rural broadband applications[15]
  • Empirical Validation: NYUSIM simulation results supporting theoretical findings[1]
  • Performance Analysis: Quantitative comparison with alternative technologies[3]
  • Mitigation Strategies: Practical solutions for environmental challenges[6]

Policy Implications:

  • Regional Models: SWIFT consortium approach for rural broadband deployment[2]
  • Community Engagement: Local participation in infrastructure decisions
  • Economic Feasibility: Cost-effective alternatives to traditional wired infrastructure
  • Scalable Solutions: Replicable models for rural connectivity initiatives

Social Impact:

  • Digital Inclusion: Bridging connectivity gaps in rural communities
  • Economic Development: Enabling remote work and digital services
  • Educational Access: Supporting online learning and telemedicine
  • Community Empowerment: Local control over broadband infrastructure

Technologies and Tools

  • NYUSIM: Statistical channel simulation for mmWave deployments
  • MATLAB: Data analysis and visualization
  • Literature Review: Comprehensive survey of existing research
  • Case Study Analysis: Real-world deployment scenarios

References

[1] Sun, S., MacCartney, G. R., and Rappaport, T. S. A novel millimeter-wave channel simulator and applications for 5G wireless communications. In 2017 IEEE International Conference on Communications (ICC). pp. 1–7. (Paris, France, 2017).

[2] Hambly, H., and Rajabiun, R. Rural broadband: Gaps, maps and challenges. Telematics and Informatics. Volume 60. pp. 101565. 2021.

[3] Abozariba, R., Davies, E., Broadbent, M., and Race, N. Evaluating the Real-World Performance of 5G Fixed Wireless Broadband in Rural Areas. In 2019 IEEE 2nd 5G World Forum (5GWF). pp. 465–470. (Dresden, Germany, 2019).

[4] Kiran, M. P. R. S., and Rajalakshmi, P. Saturated throughput analysis of IEEE 802.11 ad EDCA for high data rate 5G-IoT applications. IEEE Transactions on Vehicular Technology. Volume 68. Issue 5. pp. 4774–4785. 2019.

[5] Zhao, L., Wei, Z., Ng, D. W. K., Yuan, J., and Reed, M. C. Multi-Cell Hybrid Millimeter Wave Systems: Pilot Contamination and Interference Mitigation. IEEE Transactions on Communications. Volume 66. Issue 11. pp. 5740–5755. 2018.

[6] Budalal, A., Rafiqul, I., Habaebi, M., and Rahman, T. The effects of rain fade on millimetre wave channel in tropical climate. Bulletin of Electrical Engineering and Informatics. Volume 8. Issue 2. pp. 653–664. 2019.

[7] Zhang, Y. -P., Wang, P., and Goldsmith, A. Rainfall Effect on the Performance of Millimeter-Wave MIMO Systems. IEEE Transactions on Wireless Communications. Volume 14. Issue 9. pp. 4857–4866. 2015.

[8] Peric, M., Peric, D., Todorovic, B., and Popovic, M. Dynamic Rain Attenuation Model for Millimeter Wave Network Analysis. IEEE Transactions on Wireless Communications. Volume 16. Issue 4. pp. 1–1. 2016.

[9] Kanhere, O., and Rappaport, T. S. Position locationing for millimeter wave systems. In 2018 IEEE Global Communications Conference (GLOBECOM). pp. 206–212. (Abu Dhabi, UAE, 2018).

[10] Thornburg, A., Bai, T., and Heath, R. W. Performance Analysis of Outdoor mmWave Ad Hoc Networks. IEEE Transactions on Signal Processing. Volume 64. Issue 15. pp. 4065–4079. 2016.

[11] Fozi, M., Sharafat, A. R., and Bennis, M. Fast MIMO Beamforming via Deep Reinforcement Learning for High Mobility mmWave Connectivity. IEEE Journal on Selected Areas in Communications. Volume 40. Issue 1. pp. 127–142. 2022.

[12] Gerasimenko, M., Moltchanov, D., Gapeyenko, M., Andreev, S., and Koucheryavy, Y. Capacity of Multiconnectivity mmWave Systems With Dynamic Blockage and Directional Antennas. IEEE Transactions on Vehicular Technology. Volume 68. Issue 4. pp. 3534–3549. 2019.

[13] Dutta, S., Barati, C. N., Ramirez, D., Dhananjay, A., Buckwalter, J. F., and Rangan, S. A Case for Digital Beamforming at mmWave. IEEE Transactions on Wireless Communications. Volume 19. Issue 2. pp. 756–770. 2020.

[14] Nie, S., et al. mmWave on a Farm: Channel Modeling for Wireless Agricultural Networks at Broadband Millimeter-Wave Frequency. In 2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). pp. 388–396. (Singapore, 2022).

[15] Rappaport, T. S., et al. Millimeter wave mobile communications for 5G cellular: It will work! IEEE Access. Volume 1. pp. 335–349. 2013.

This project was completed as part of CPR E 543 (Wireless Communication Systems) at Iowa State University.