Performance analysis of Radio Resource Allocation and Interference Management

Title:- Using Federated learning in a distributed D2D communication network for radio resource allocation and interference management in a cell-free network
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Implementation plan:
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Step 1: Initially, we construct a cell-free network with 50 - UEs, 5 - Base Stations.
Step 2: Next, we Implement D2D communications to allow direct communication between UEs.
Step 3: Then, we Implement a federated learning to train a model without sharing data.
Step 4: Next, we develop algorithms for radio resource allocation to allocate frequency resources optimally to D2D pairs.
Step 5: Then, we simulate the network to view the communications between UEs and Base Stations.
step 6: Finally we plot graph for the following
6.1: Accuracy
6.2: Energy Efficiency
6.3: Throughput
Software Requirement:
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1. Development Tool : Ns3.35 with Python
2. Development OS : Ubuntu 22.04 LTS
Note:
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1) If the above plan does not satisfy your requirement, please provide the processing details, like the above step-by-step.
2) Please note that this implementation plan does not include any further steps after it is put into implementation.
3) This project is only based on simulations. Not a real time project.
4) If the above plan satisfies your requirement please confirm with us.
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#RadioResourceAllocation
#InterferenceManagement
#PerformanceAnalysis
#WirelessNetworks
#SpectrumEfficiency
#NetworkOptimization
#QualityofService
#CellularNetworks
#SignalInterference
#networkperformance
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