• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.792-812
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• 2022

Multi-agent systems often need to achieve the goal of learning more effectively for a task through coordination. Although the introduction of deep learning has addressed the state space problems, multi-agent learning remains infeasible because of the joint action spaces. Large-scale joint action spaces can be sparse according to implicit or explicit coordination structure, which can ensure reasonable coordination action through the coordination structure. In general, the multi-agent system is dynamic, which makes the relations among agents and the coordination structure are dynamic. Therefore, the explicit coordination structure can better represent the coordinative relationship among agents and achieve better coordination between agents. Inspired by the maximization of social group utility, we dynamically construct a factor graph as an explicit coordination structure to express the coordinative relationship according to the utility among agents and estimate the joint action values based on the local utility transfer among factor graphs. We present the application of such techniques in the scenario of multiple intelligent vehicle systems, where state space and action space are a problem and have too many interactions among agents. The results on the multiple intelligent vehicle systems demonstrate the efficiency and effectiveness of our proposed methods.

• ETRI Journal
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• v.45 no.5
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• pp.874-886
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• 2023

A joint resource-optimization scheme is investigated for nonorthogonal multiple access (NOMA)-enhanced scalable video coding (SVC) multicast in unmanned aerial vehicle (UAV)-assisted radio-access networks (RANs). This scheme allows a ground base station and UAVs to simultaneously multicast successive video layers in SVC with successive interference cancellation in NOMA. A video quality-maximization problem is formulated as a mixed-integer nonlinear programming problem to determine the UAV deployment and association, RAN spectrum allocation for multicast groups, and UAV transmit power. The optimization problem is decoupled into the UAV deployment-association, spectrum-partition, and UAV transmit-power-control subproblems. A heuristic strategy is designed to determine the UAV deployment and association patterns. An upgraded knapsack algorithm is developed to solve spectrum partition, followed by fast UAV power fine-tuning to further boost the performance. The simulation results confirm that the proposed scheme improves the average peak signal-to-noise ratio, aggregate videoreception rate, and spectrum utilization over various baselines.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1460-1463
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• 2010

Railway has been pointed to the efficiency of transportation, rapid transit, and comfortable train ride. the construction of railway near the downtown area and station building are increasing for maximization of utilization and convenience. but the heavy of transportation and rapid transit lead to increase noise and vibration. The noise and vibration of railway may cause the civil appeal, decline in the serviceability and insufficiency of environmental standard. In this study, floating slab vibration and repeated connection of devices to support joints and fatigue stress analysis of punching shear performance review was conducted to evaluate the safety.

• ETRI Journal
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• v.36 no.6
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• pp.960-967
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• 2014

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi-channel wireless multihop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems - flow control; next-hop routing; rate allocation and scheduling; power control; and channel allocation - and finally solved by a low-complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.209-231
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• 2007

This paper suggested an approach to characterize travel choice behaviors using the implicit price instead of the indirect utility. The choice criterion to compare the implicit prices of available trip options was developed from the utility maximization problem of a trip maker which is supposed to choose the best option from the available ones differentiated by only by the quantitative attributes such as travel cost and time but also by qualitative attributes such as comfort and safety. The utility maximization problem is constructed under household production theory, and is incorporated with a special kind of joint homogeneous production functions. The implicit price of a certain trip option is the sum of the monetary price and the multiple of travel time and the value-of-travel-time, and the value-of-travel-time refers to the portion of wage, which can be assignable to the trip-making activity. This choice criterion is statistically identifiable, and behaviorally plausible. Moreover, this criterion has the expression simpler than the indirect utility, and therefore could be an effective target of the statistical estimation for travel choice behaviors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3A
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• pp.247-260
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• 2007

This paper solves the problem of finding a suitable sub-channel and power joint allocation method for multiple users in 802.16e OFDMA/TDD cellular systems. The joint allocation is thatfirstly the sub-channel is allocated to the users and then suitable power is allocated. We propose a FASA (Fairness insured Aggressive Sub-channel Allocation) algorithm which is a dynamic channel allocation algorithm considering all users' channel state information conditionally to maximize fairness and throughput. The improved CHC algorithm, which is dynamic power allocation algorithm, is also proposed in this paper The Improved CHC algorithm collects the extra of the downlink transmit power and then re-allocates it to other users. Simulation results show that the proposed improved CHC algorithm additionally increases the fairness and sector throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1569-1586
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• 2015

This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l₁-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.

• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.5 s.120
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• pp.465-470
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• 2007

The co-channel interference is a primary factor of loss in multimedia mobile communications. In this paper, we present a performance of the frequency reuse partitioning to refrain the co-channel interference and maximize system performance. First, we analyze the co-channel interference using the frequency reuse partitioning through the statistical modeling. From this results, we decide on the frequency reuse partitioning for the system throughput which is maximized. Finally, analysis and simulation results show that the frequency reuse partitioning based cellular system can mitigate the co-channel interference and maximize the system throughput. The experimental results show that system throughput is maximized from 0.7 to 0.8 according to traffic road. We can maximize the system throughput using the results with cellular system design parameter.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.11 s.353
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• pp.1-7
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• 2006

This paper consider a code-division multiple-access(CDMA) wireless ad-hoc network in low-SINR regime. In previous research [6], there has been proposed a algorithm for achieving global optimum at high SINR regime, but has not been fully investigated at low-SINR regime. In this paper, we focus on a case where SINR is much smaller than 1, and propose a algorithm that is suitable for low-SINR regime.