• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2362-2378
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• 2017

To mitigate the performance degradation caused by performance anomaly, a number of channel assignment algorithms have been proposed for multi-rate wireless mesh networks. However, network conditions have not been fully considered for routing process in these algorithms. In this paper, a joint scheme called Multi-rate Dijkstra's Shortest path - Rate Separated (MDSRS) is proposed, combining routing metrics and channel assignment algorithm. In MDSRS, the routing metric are determined through the synthesized deliberations of link costs and rate matches; then the rate separated channel assignment is operated based on the determined routing metric. In this way, the competitions between high and low rate links are avoided, and performance anomaly problem is settled, and the network capacity is efficiently improved. Theoretical analysis and NS-3 simulation results indicate that, the proposed MDSRS can significantly improve the network throughput, and decrease the average end-to-end delay as well as packet loss probability. Performance improvements could be achieved even in the heavy load network conditions.

• Journal of the Korea Society of Computer and Information
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• v.18 no.6
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• pp.37-45
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• 2013

In the absence of a single deterministic rule for the channel assignment problems, heuristic algorithms are predominantly employed to partly solve the problems. This paper thus proposes deterministic rules for the channel assignment problems. These deterministic rules have successfully yielded the optimal solution when applied to the Philadelphia's 9 case examples.

• 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.

• 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.

• IE interfaces
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• v.16 no.3
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• pp.311-321
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• 2003

We propose the improved channel assignment and management methods for an efficient use of traffic channel resource for supporting 12.2 Kbps, 64 Kbps, and 384 Kbps traffic with the different quality of service(QoS) in the radio network controller(RNC) in asynchronous IMT-2000 system. We consider two types of traffic channel block assignments for utilizing the traffic channel efficiently; the Completely Shared(CS) channel assignment and the Partially Dedicated and Partially Shared(PDPS) channel assignment. The former is that all traffic channel blocks are completely shared with all traffic types. The latter is that some traffic channel block is independently assigned to each traffic type and the other blocks are completely shared with some traffic type. We also propose the traffic channel management method which consists of the block and task management step, for efficiently assigning, releasing, and managing the channel resource. Finally, we evaluate the performance through various numerical examples when applying our proposed channel block assignment and resource management methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.339-347
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• 1993

The channel assignment problem in a mobile communication system is a NP-complete combinatorial optimization problem, in which the calculation time increases exponentially as the range of the problem is extended. This paper adapts a conventional Hopfield neural network model to the channel assignment problem to relieve the calculation time by means of the parallelism supplied from the neural network. In the simulation study, we checked the feasability of such a parallel method for the fixed channel assignment with uniform, and nouniform channel requirements, and for the dynamic channel assignment with considering continously varying channel requirements.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.439-448
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• 1999

In this paper, two optimization algorithms based on artificial neural networks and genetic algorithms are proposed for cellular radio channel assignment problems. The channel assignment process is characterized as minimization of the energy function which represents constraints of the channel assignment problems. All three constraints such as the co-channel constraint, the adjacent channel constraint and the co-site channel constraint are considered. In the neural networks approach, certain techniques such as the forced assignment and the changing cell order are developed, and in the genetic algorithms approach, data structure and proper genetic operators are developed to find optimal solutions, As simulation results, the convergence rates of the two approaches are presented and compared.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2648-2665
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• 2022

Device-to-device (D2D) multicast has become a promising technology to provide specific services within a small geographical region with a high data rate, low delay and low energy consumption. However, D2D multicast communications are allowed to reuse the same channels with cellular uplinks and result in mutual interference in a cell. In this paper, an intelligent channel assignment algorithm is designed in D2D underlaid cellular networks with the target of maximizing network throughput. We first model the channel assignment problem to be a throughput maximizing problem which is NP-hard. To solve the problem in a feasible way, a novel channel assignment algorithm is proposed. The key idea is to find the appropriate cellular communications and D2D multicast groups to share a channel without causing critical interference, i.e., finding a channel for a D2D multicast group which generates the least interference to network based on current channel assignment status. In order to show the efficacy and effectiveness of our proposed algorithm, a novel search algorithm is proposed to find the near-optimal solution as the baseline for comparisons. Simulation results show that the proposed algorithm improves the network throughput.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11A
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• pp.870-877
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• 2011

IEEE 802.11 devices are widely used, and terminals can be equipped with multiple IEEE 802.11 interfaces as low-cost IEEE 802.11 devices are deployed. The off-the-shelf IEEE 802.11 devices provide multiple channels and multiple data rates. In practical multi-channel networks, since there is channel heterogeneity which indicates that channels have different signal characteristics for the same node, channels should be efficiently assigned to improve network capacity. In addition, in multi-rate networks, low-rate links severely degrade the performance of high-rate links on the same channel, which is known as performance anomaly. Therefore, in this paper, we propose a heterogeneity aware channel assignment (HACA) algorithm that improves network performance by reflecting channel heterogeneity and performance anomaly. Through NS-2 simulations, we validate that the HACA algorithm shows improved performance compared with existing channel assignment algorithms that do not reflect channel heterogeneity.