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الصفحة الرئيسية

Trained Neural Network on selecting DL speed for eNodeB

السنة الأكاديمية: 
2013
الطلاب: 
Dyala Fatayer
Oswa Ayoub
Tamarah Al-Joudeh

 

 

This project presents a new concept in the communication world, by linking LTE with Self-Organizing Networks (SON). The main idea is to use a Feed-Forward Back Propagation Network. In SON, we are concerned about training the network to select the required actual DL speed Mbps (BW) according to the code per service type. This can be accomplished by giving all possible service types a code number, which is used as an input matrix. On the other hand, we give each service type the bandwidth it requires in LTE system to serve with a good quality and use it as a target matrix, both matrices (input, target) are used as an input to the training process in the Feed-Forward Back Propagation Network. At the end of training the eNodeB will be able to choose the appropriate bandwidth for each service type automatically, leading to better utilization of system.

 

 

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