Sum-Rate Maximization In OFDMA Downlink Systems

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€ 30.00 — 250.00 EUR
I have attached a paper that aims at allocating radio resources: MCS index, Resource Blocks, and Power for the users of just one base station.
The authors modeled the problem as a MILP problem, but they didn’t use a MILP solver.
Instead, they developed their own algorithm.
We are only interested in the MILP problem.
here is a link of the matlab documentation for MILP :
https://fr.mathworks.com/help/optim/ug/intlinprog.html

you have to solve The MILP problem of the paper in MATLAB
Solving the MILP problem in the paper using MATLAB, GUROBI, or CPLEX; solvers that are faster than MATLAB and can be called from within Matlab.

Then you will run the simulation for multiple times; you will registers the inputs: For eg.
Position of users, noise channel gain, throughput demand…., and you will register the output: Users allocation, MCS indexes, RBs, Power on RBs
You will use the inputs and outputs to train a deep learning model( maybe a recurrent neural network) using deep learning toolbox in Matlab
Then compare the performance of the RNN model to the ILP model on a data set that wasn’t used for training.
Neural NetworksTelecoms EngineeringNetwork EngineeringRadio Access Network Commissioning

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