• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.502-506
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• 2008

The recently proposed "Potential-based" reinforcement learning (RL) method made it possible to combine multiple learnings and expert advices as supervised knowledge within an RL framework. The effectiveness of the approach has been established by a theoretical convergence guarantee to an optimal policy. In this paper, the potential-based RL method is applied to a dynamic channel assignment (DCA) problem in a cellular networks. It is empirically shown that the potential-based RL assigns channels more efficiently than fixed channel assignment, Maxavail, and Q-learning-based DCA, and it converges to an optimal policy more rapidly than other RL algorithms, SARSA(0) and PRQ-learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1535-1554
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• 2016

This paper proposes a novel channel assignment scheme called multi-cluster based dynamic channel assignment (MC-DCA) to improve system performance for the downlink of dense femtocell networks (DFNs) based on orthogonal frequency division multiple access (OFDMA) and frequency division duplexing (FDD). In order to dynamically assign channels for femtocell access points (FAPs), the MC-DCA scheme uses a heuristic method that consists of two steps: one is a multiple cluster assignment step to group FAPs using graph coloring algorithm with some extensions, while the other is a dynamic subchannel assignment step to allocate subchannels for maximizing the system capacity. Through simulations, we first find optimum parameters of the multiple FAP clustering to maximize the system capacity and then evaluate system performance in terms of the mean FAP capacity, unsatisfied femtocell user equipment (FUE) probability, and mean FAP power consumption for data transmission based on a given FUE traffic load. As a result, the MC-DCA scheme outperforms other schemes in two different DFN environments for commercial and office buildings.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.13-20
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• 2006

In cellular mobile communications, how to achieve optimum system capacity with limited frequency spectrum is one of the main research issues. Many dynamic channel assignment (DCA) schemes have been proposed and studied to allocate the channels more efficiently, thus, the capacity of cellular systems is improved. Reuse partitioning (RP) is another technique to achieve higher capacity by reducing the overall reuse distance. In this paper, we present a network-based DCA scheme with the implementation of RP technique, namely dynamic reuse partitioning with interference information (DRP-WI). The scheme aims to minimize the effect of assigned channels on the availability of channels for use in the interfering cells and to reduce their overall reuse distances. The performance of DRP-WI is measured in terms of blocking probability and system capacity. Simulation results have confirmed the effectiveness of DRP-WI scheme. Under both uniform and non-uniform traffic distributions, DRP-WI exhibits outstanding performance in improving the system capacity. It can provide about 100% capacity improvement as compared to conventional fixed channel assignment scheme with 70 system channels.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.824-832
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• 2009

Multi-radio multi-channel Wireless Mesh Network requires an effective management policy to control the assignment of channels to each radio. We concentrated our investigation on modeling method and solution to find a dynamic channel assignment scheme that is adapted to change of network traffic. Multi-path routing scheme was chosen to overwhelm the unreliability of wireless link. For a particular traffic state, our optimization model found a specific traffic distribution over multi-path and a channel assignment scheme that maximizes the overall network throughput. We developed a simple heuristic method for channel assignment by gradually removing clique load to obtain higher throughput. We also presented numerical examples and discussion of our models in comparison with existing research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.68-82
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• 2011

Wireless mesh networks (WMNs) provide high-speed backbone networks without any wired cable. Many researchers have tried to increase network throughput by using multi-channel and multi-radio interfaces. A multi-radio multi-channel WMN requires channel assignment algorithm to decide the number of channels needed for each link. Since the channel assignment affects routing and interference directly, it is a critical component for enhancing network performance. However, the optimal channel assignment is known as a NP complete problem. For high performance, most of previous works assign channels in a centralized manner but they are limited in being applied for dynamic network environments. In this paper, we propose a simple flow estimation algorithm and a hybrid channel assignment algorithm. Our flow estimation algorithm obtains aggregated flow rate information between routers by packet sampling, thereby achieving high scalability. Our hybrid channel assignment algorithm initially assigns channels in a centralized manner first, and runs in a distributed manner to adjust channel assignment when notable traffic changes are detected. This approach provides high scalability and high performance compared with existing algorithms, and they are confirmed through extensive performance evaluations.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1463-1466
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• 2002

This paper suggests the effective channel assignment scheme for mobility prediction handover. For maintaining required quality of service (QoS) during handover, there are handover algorithms these reserve the channel where the movement is predicted. But channel assignment schemes these have been studied are not considered mobility prediction handover. This paper suggests the channel assignment scheme that considers mobility predicted handover. The suggested algorithm maintains dropping probability of handover calls, decreases blocking probability of new calls and increases channel utilization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.4
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• pp.257-265
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• 2013

In this paper, we proposed a Dynamic Channel Assignment (DCA) scheme called Graph Coloring based DCA (GC-DCA) to improve system performance for downlink femtocell networks with high density femto Access Point (AP) deployments. The proposed scheme consists of two steps: one is a femto AP grouping step considering interference and the other is a DCA step considering Signal to Interference plus Noise Ratio (SINR) for femto User Equipments (UEs). Simulation results show that the proposed GC-DCA outperforms other schemes in terms of the mean femto UE capacity and probability of femto UEs which have capacities less than a given transmit rate.

• International Journal of Contents
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• v.1 no.2
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• pp.31-34
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• 2005

The new realtime applications like multimedia and realtime services in a wireless network will be dramatically increased. However, many realtime services of mobile hosts in a cell cannot be continued because of insufficiency of useful channels. Conventional channel assignment approaches didn't properly consider the problem to serve realtime applications in a cell. This paper proposes a new realtime channel assignment algorithm based on time constraint analysis of channel requests. The proposed algorithm dynamically borrows available channels from neighboring cells. It also supports a smooth handoff which continuously serves realtime applications of the mobile hosts.

• The KIPS Transactions:PartC
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• v.11C no.2
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• pp.203-212
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• 2004

There is a rapidly growing demand for wireless telecommunication. The restricted number of channels is a significant bottleneck for the capacity of mobile communication systems. Consequently, when assigning the channels to the different base stations, it is desirable to reuse the same channel af much as possible. It is then important to avoid any possible interference between different mobile users, while satisfying the given demand. The objective of this thesis is to develop a hybrid heuristic algorithm to find the channel assignment method for allocating the channels in an efficient way, which does not violate the compatibility constraints. We also show several benchmarking channel assignment problems using proposed channel assignment method for validation in this thesis.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.25-31
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• 2022

In ultra dense networks (UDNs), macro user equipments (MUEs) have significant interference from small-cell access points (SAPs) since a number of SAPs are deployed in the coverage of macro base stations of 5G mobile communication systems. In this paper, we propose a dynamic channel assignment scheme to increase the performance of MUEs for the uplink of UDNs even though the number of SAPs is increased. The target of the proposed dynamic channel assignment scheme is that the signal-to-interference and noise ratio (SINR) of MUEs is above a given SINR threshold assigning different subchannels to SUEs from those of MUEs. Simulation results show that the proposed dynamic channel assignment scheme outperforms others in terms of the mean MUE capacity even though the mean SUE capacity is decreased a little lower.