2 research outputs found
A Call Admission Control Scheme using NeuroEvolution Algorithm in Cellular Networks
This paper proposes an approach for learning call admission control (CAC) policies in a cellular network that handles several classes of traffic with different resource requirements. The performance measures in cellular networks are long term revenue, utility, call blocking rate (CBR) and handoff failure rate (CDR). Reinforcement Learning (RL) can be used to provide the optimal solution, however such method fails when the state space and action space are huge. We apply a form of NeuroEvolution (NE) algorithm to inductively learn the CAC policies, which is called CN (Call Admission Control scheme using NE). Comparing with the Q-Learning based CAC scheme in the constant traffic load shows that CN can not only approximate the optimal solution very well but also optimize the CBR and CDR in a more flexibility way. Additionally the simulation results demonstrate that the proposed scheme is capable of keeping the handoff dropping rate below a pre-specified value while still maintaining an acceptable CBR in the presence of smoothly varying arrival rates of traffic, in which the state space is too large for practical deployment of the other learning scheme.
Recommended from our members
A Connection Admission Control Framework for UMTS based Satellite Systems.An Adaptive Admission Control algorithm with pre-emption control mechanism for unicast and multicast communications in satellite UMTS.
In recent years, there has been an exponential growth in the use of
multimedia applications. A satellite system offers great potential for
multimedia applications with its ability to broadcast and multicast a large
amount of data over a very large area as compared to a terrestrial system.
However, the limited transmission capacity along with the dynamically
varying channel conditions impedes the delivery of good quality multimedia
service in a satellite system which has resulted in research efforts for deriving
efficient radio resource management techniques. This issue is addressed in
this thesis, where the main emphasis is to design a CAC framework which
maximizes the utilization of the scarce radio resources available in the
satellite and at the same time increases the performance of the system for a
UMTS based satellite system supporting unicast and multicast traffic.
The design of the system architecture for a UMTS based satellite system is
presented. Based on this architecture, a CAC framework is designed
consisting of three different functionalities: the admission control procedure,
the retune procedure and the pre-emption procedure. The joint use of these
functionalities is proposed to allow the performance of the system to be
maintained under congestion. Different algorithms are proposed for different
functionalities; an adaptive admission control algorithm, a greedy retune
algorithm and three pre-emption algorithms (Greedy, SubSetSum, and
Fuzzy).
A MATLAB simulation model is developed to study the performance of the
proposed CAC framework. A GUI is created to provide the user with the
flexibility to configure the system settings before starting a simulation. The
configuration settings allow the system to be analysed under different
conditions.
The performance of the system is measured under different simulation
settings such as enabling and disabling of the two functionalities of the CAC
framework; retune procedure and the pre-emption procedure. The simulation
results indicate the CAC framework as a whole with all the functionalities
performs better than the other simulation settings