Performance Analysis of Secure and Scalable AI Driven Resource Allocation in 6G Using SMPC
Implementation plan:
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Step 1: Initially, we Design a 6G RAN architecture model with distributed 30 edge nodes, 10 UE and centralized RIC.
Step 2: Then, we Apply additive secret-sharing to securely mask node data with masking time per RIC loop is under 10 ms
Step 3: Next, we Distribute masked data across peer nodes to the RIC by enforcing transmission time within the 10 ms RIC control loop.
Step 4: Next, we Implement two-round SMPC protocol using additive sharing with total operation (masking, sending, unmasking) completed within the 10 ms cycle.
Step 5: Next, we Apply real-time federated Q-learning for power/resource allocation by Each edge node trains locally, the RIC aggregates models securely and efficiently within each control loop.
Step 6: Finally, we plot performance metrics for the following
6.1: Number of edge nodes vs. Latency (ms)
6.2: Number of edge nodes vs. Resource Allocation (%)
6.3: Number of edge nodes vs. Communication Overhead (KB/s)
Software Requirements:
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1. Development Tool: Matlab-R2024a
2. Operating System: Windows-11 (64-bit)
Note:
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1) If the plan does not meet your requirements, provide detailed steps, parameters, models, or expected results in advance. Once implemented, changes won’t be possible without prior input; otherwise, we’ll proceed as per our implementation plan.
2) If the plan satisfies your requirement, Please confirm with us.
3) Project based on Simulation only, not a real time project.
4) Please understand that any modifications made to the confirmed implementation plan will not be made after the project development.
