This project is design based on the thesis "Artificial Neural Network-Based Cellular Network Predictive System for Resource Allocation".Matlab program is devloped for five Resource Allocation Techniques and Algorithms as given below,

  • Resource Allocation Techniques using Neural Networks
  • Resource Allocation Techniques using Genetic Algorithms
  • Resource Allocation Techniques using Optimization Methods
  • Resource Allocation Techniques using Evolutionary Algorithms
  • Resource Allocation Techniques using Fuzzy Logic

The scope of this project is limited to the application to the development of predictive and resource allocation model that predicts future mean traffic intensity in a cellular 2 network from its historical data and automatically allocate the resource appropriately. From the predictions made, channels will be allocated to cells within the network in advance to efficiently service the predicted traffic. Finally, the model will be implemented by developing an application software that can be deployed in a cellular network environment to predict the future mean traffic and to allocate channels that will be required to service the predicted traffic intensity based on the inverse Erlang-B formula.

Design Key Points

  • Get following Parameters for Network.
Call Setup Success Rate (Cssr)
Drop Call Rate (Dcr)
Standalone Dedicated Channel (Sdcch)
Blocking Rate (Sdcchblk)
Sdcch Loss Rate (Sdcchloss)
Handover Success Rate (Hosr)
Call Setup Blocking Rate (Callsetblk)
Traffic Channel Blocking Rate (Tchblk)
Traffic Channel Mean Traffic (Tchmean)
  • Select any One Network Resource Allocation Model Algorithm 
Neural Network
Genetic Algorithm
Optimization Methods
Evolutionary Algorithm
Fuzzy Logic
  • Feed all parameters to resource allocation model
  • Get Resource Value

You can DOWNLOAD Neural Network Matlab code and reference documents.Request design files for academic purpose,contact

SIMULATION VIDEO DEMO