A distributed AI/ML framework for D2D Transmission Mode Selection in 5G and beyond

Computer Science

• Artificial Intelligence 100%
• Machine Learning 100%
• Power Consumption 100%
• sum rate 100%
• Spectral Efficiency 100%
• Execution Time 33%
• clustering approach 33%
• Algorithmic Approach 33%
• Device-To-Device 33%
• Distributed Artificial Intelligence 33%
• Multi-Access Edge Computing 33%
• Exchanged Message 33%
• Comparative Evaluation 33%
• Quality of Service 33%
• Performance Gain 33%
• Fair Comparison 33%
• Mobile Device 33%
• Aggregated Data 33%

Keyphrases

• ML Frameworks 100%
• Unsupervised ML 66%
• Execution Delay 33%
• Fair Comparison 33%
• ML Techniques 33%
• Time Execution 33%
• Fuzzy ART 33%
• Device-to-device 33%
• Aggregated Data Rate 33%
• Performance Gain 33%