Abstract: According to annual visual network index (VNI) report by the year 2020, 4G will reach its maturity and incremental approach will not meet demand. Only way is to switch to newer generation of mobile technology called as 5G. Resource allocation is critical problem that impact 5G Network operation critically. Timely and accurate assessment of underutilized bandwidth to primary user is necessary in order to utilize it efficiently for increasing network efficiency. This paper presents a decision making system at Fusion center using modified Random Forest. Modified Random Forest is first trained using Database accumulated by measuring different network parameters and can take decision on allocation of resources. The Random Forest is retrained after fixed time interval, considering dynamic nature of network. We also test its performance in comparison with existing AND/OR logic decision logic at Fusion Center

Parnika De and Shailendra Singh, “Modified Random Forest Approach for Resource Allocation in 5G Network” International Journal of Advanced Computer Science and Applications(IJACSA), 7(11), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071152

@article{De2016,
title = {Modified Random Forest Approach for Resource Allocation in 5G Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071152},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071152},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {11},
author = {Parnika De and Shailendra Singh}
}