Advancements in Wireless Network Optimization and Medium Access Control

The field of wireless networking is witnessing significant advancements in optimization and medium access control techniques. Recent developments focus on improving network performance, fairness, and efficiency in various scenarios, including mobile networks and heterogeneous wireless networks. Innovative approaches, such as fairness-differentiated handover schemes and fully decentralized multi-agent reinforcement learning, are being proposed to address the challenges of mobility and spectrum sharing. Additionally, data-driven optimization methods, including Bayesian optimization and transfer learning, are being applied to optimize network parameters and improve mobility management. The integration of artificial intelligence and machine learning techniques is also leading to the development of more efficient medium access control protocols, tailored to the needs of 6G wireless systems. Noteworthy papers include:

  • A fairness-differentiated handover scheme that improves the performance of cell-free massive MIMO under mobility.
  • A fully decentralized multi-agent reinforcement learning approach that achieves fairness in dynamic spectrum access without coordination.
  • A data-driven optimization framework that uses Bayesian optimization and transfer learning to optimize 3GPP handover parameters.

Sources

Cell-Free Massive MIMO Under Mobility: A Fairness-Differentiated Handover Scheme

Fair Dynamic Spectrum Access via Fully Decentralized Multi-Agent Reinforcement Learning

Geo2ComMap: Deep Learning-Based MIMO Throughput Prediction Using Geographic Data

Data-driven Optimization and Transfer Learning for Cellular Network Antenna Configurations

Balancing Subjectivity and Objectivity in Network Selection: A Decision-Making Framework Towards Digital Twins

An Efficient Reservation Protocol for Medium Access: When Tree Splitting Meets Reinforcement Learning

Data-Driven Design of 3GPP Handover Parameters with Bayesian Optimization and Transfer Learning

Medium Access for Push-Pull Data Transmission in 6G Wireless Systems

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