Conditional Most-Correlated Distribution-Based Load-Balancing Scheme for Hybrid LiFi/WiGig Network.

Area of Science:

• Wireless Communication Networks
• Network Engineering
• Signal Processing

Background:

• High-speed wireless communication demands efficient load balancing in hybrid networks.
• Traditional load-balancing strategies struggle with dynamic user distribution, requiring complex computations.
• Integrating Light Fidelity (LiFi) and Wireless Gigabit Alliance (WiGig) presents unique load-balancing challenges.

Purpose of the Study:

• To develop an adaptable and efficient load-balancing (LB) strategy for hybrid LiFi-WiGig networks.
• To introduce a two-step conditional algorithm that balances performance and computational complexity.
• To enhance system performance through a novel correlation-weighted voting method.

Main Methods:

• Proposed a two-step Conditional Most-Correlated Distribution (CMCD) algorithm.
• Implemented a low-complexity Most-Correlated Distribution (MCD) scheme with a performance threshold.
• Developed a Correlation-Weighted Majority Voting (CWMV) method for decision making.

Main Results:

• The CMCD algorithm offers a controllable performance-complexity trade-off.
• The CWMV method leverages historical data for improved decision accuracy.
• Simulation results demonstrate a significant increase in overall system performance.

Conclusions:

• The proposed CMCD and CWMV algorithms provide effective solutions for load balancing in hybrid LiFi-WiGig networks.
• These methods enhance system adaptability and efficiency in dynamic user environments.
• The study highlights a practical approach to managing resources in next-generation wireless systems.