Modified Random Forest Approach for Resource Allocation in 5G Network
نویسندگان
چکیده
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 Keywords—5G; Cognitive Radio; Clustering; Fusion Centre; Random Forest
منابع مشابه
Policy Model for Sharing Network Slices in 5G Core Network
As mobile data traffic increases, and the number of services provided by the mobile network increases, service load flows as well, which requires changing in the principles, models, and strategies for media transmission streams serving to guarantee the given nature of giving a wide scope of services in Flexible and cost-effective. Right now, the fundamental question remains what number of netwo...
متن کاملApplication of Learning-based Resource Allocation Scheme for Different UE Antenna Orientations
One of the main tasks of the fifth generation (5G) network systems is the ability to provide high-data rates with always-on connectivity to the everincreasing number of smart devices, especially for high mobility users. By cooperation within a number of the Remote Radio Heads (RRHs), higher system capacity can be achieved based on the Cloud Radio Access Network (CRAN) architecture for the 5G ne...
متن کاملTown trip forecasting based on data mining techniques
In this paper, a data mining approach is proposed for duration prediction of the town trips (travel time) in New York City. In this regard, at first, two novel approaches, including a mathematical and a statistical approach, are proposed for grouping categorical variables with a huge number of levels. The proposed approaches work based on the cost matrix generated by repetitive post-hoc tests f...
متن کاملConstrained consumable resource allocation in alternative stochastic networks via multi-objective decision making
Many real projects complete through the realization of one and only one path of various possible network paths. Here, these networks are called alternative stochastic networks (ASNs). It is supposed that the nodes of considered network are probabilistic with exclusive-or receiver and exclusive-or emitter. First, an analytical approach is proposed to simplify the structure of t...
متن کاملA Bi-level Formulation for Centralized Resource Allocation DEA Models
In this paper, the common centralized DEA models are extended to the bi-level centralized resource allocation (CRA) models based on revenue efficiency. Based on the Karush–Kuhn–Tucker (KKT) conditions, the bi-level CRA model is reduced to a one-level mathematical program subject to complementarity constraints (MPCC). A recurrent neural network is developed for solving this one-level mathematica...
متن کامل