• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1884-1903
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• 2019

Device-to-Device (D2D) communications can provide proximity based services in the future 5G cellular networks. It allows short range communication in a limited area with the advantages of power saving, high data rate and traffic offloading. However, D2D communications may reuse the licensed channels with cellular communications and potentially result in critical interferences to nearby devices. To control the interference and improve network throughput in overlaid D2D cellular networks, a novel channel assignment approach is proposed in this paper. First, we characterize the performance of devices by using Poisson point process model. Then, we convert the throughput maximization problem into an optimal spectrum allocation problem with signal to interference plus noise ratio constraints and solve it, i.e., assigning appropriate fractions of channels to cellular communications and D2D communications. In order to mitigate the interferences between D2D devices, a cluster-based multi-channel assignment algorithm is proposed. The algorithm first cluster D2D communications into clusters to reduce the problem scale. After that, a multi-channel assignment algorithm is proposed to mitigate critical interferences among nearby devices for each D2D cluster individually. The simulation analysis conforms that the proposed algorithm can greatly increase system throughput.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.12
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• pp.856-864
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• 2019

The weapon-target assignment (WTA) problem is a matter of effectively allocating weapons to a number of threats. The WTA in a rapidly changing dynamic environment of engagement must take into account both of properties of the threat and the weapon and the effect of the previous decision. We propose a method of applying the Greedy Randomized Adaptive Search Procedure (GRASP) algorithm, a kind of meta-heuristic method, to derive optimal solution for a dynamic WTA problem. Firstly, we define a dynamic WTA problem and formulate a mathematical model for applying the algorithm. For the purpose of the assignment strategy, the objective function is defined and time-varying constraints are considered. The dynamic WTA problem is then solved by applying the GRASP algorithm. The optimal solution characteristics of the formalized dynamic WTA problem are analyzed through the simulation, and the algorithm performance is verified via the Monte-Carlo simulation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.143-150
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• 2019

We focus on the weapon target assignment and fire scheduling problem (WTAFSP) with the objective of minimizing the makespan, i.e., the latest completion time of a given set of firing operations. In this study, we assume that there are m available weapons to fire at n targets (> m). The artillery attack operation consists of two steps of sequential procedure : assignment of weapons to the targets; and scheduling firing operations against the targets that are assigned to each weapon. This problem is a combination of weapon target assignment problem (WTAP) and fire scheduling problem (FSP). To solve this problem, we define the problem with a mixed integer programming model. Then, we develop exact algorithms based on a dynamic programming technique. Also, we suggest how to find lower bounds and upper bounds to a given problem. To evaluate the performance of developed exact algorithms, computational experiments are performed on randomly generated problems. From the results, we can see suggested exact algorithm solves problems of a medium size within a reasonable amount of computation time. Also, the results show that the computation time required for suggested exact algorithm can be seen to increase rapidly as the problem size grows. We report the result with analysis and give directions for future research for this study. This study is meaningful in that it suggests an exact algorithm for a more realistic problem than existing researches. Also, this study can provide a basis for developing algorithms that can solve larger size problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.52-58
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• 2005

In this paper, we address a real-world periodic vehicle routing problem with time windows (PVRPTW). In addition to the general requirements of single-day vehicle routing problem, each stop has required number of visits within a cycle period in PVRPTW. Thus, we need to determine optimized days of visit for each stop with consideration of the cycle-period days together. The problem also requires consistent vehicle assignment to the stops. We developed a clustering based 3-phase approach for this problem: 1) stop-route assignment, 2) stop-day assignment, and 3) stop sequencing within a single-day route. Using the approach, we could reduce the number of routes and improve the routing efficiency for several real-world problems.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.300-302
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• 2012

In this paper, we investigate the performance of multi-channel cognitive radio networks (CRNs) by taking into consideration the problem of channel assignment and link scheduling. We assume that secondary nodes are equipped with multiple radios and can switch among multiple channels. How to allocate channels to links and how much power used on each channel to avoid mutual interference among secondary links are the key problem for such CRNs. We formulate the problem of channel assignment and link scheduling as a combinatorial optimization problem. Then, we propose a the optimal solution and show that it converges to maximum optimum in some iterations by using numerical results.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.169-176
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• 1992

In parts assignment problem for FMS, both the parts and the tools required to process the parts are assigned to the machine tools for a specified planning period. This is an important decision-making problem for a short-term production planning of FMS. In this paper, parts assignment problem for FMS was analyzed to determine the optimal plan which has the adaptability to production fluctuation. A mathematical model was developed for determing the parts and the tools required for the machine tools which compose FMS, and the model was analyzed to obtain optimal solution. In addition, the vality and feasibility of the computational algorithm was examined by solving a numerical example.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.79-88
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• 2008

In this paper, we propose efficient peer assignment algorithms for low-latency transmission of scalable coded images in peer-to-peer networks, in which peers may dynamically join and leave the networks. The objective of our algorithm is to minimize the transmission time of a requested image that is scalable coded. When an image is scalable coded in different bit rates, the bit stream encoded in a lower bit rate is a prefix subset of the one encoded in a higher bit rate. Therefore, a peer with the same requested image coded in any bit rate, even when it is different from the requested rate, may work as a supplying peer. As a result, when a scalable coded image is requested, more supplying peers can be found in peer-to-peer networks to help with the transfer. However, the set of supplying peers is not static during transmission, as the peers in this set may leave the network or finish their transmission at different times. The proposed peer assignment algorithms have taken into account the above constraints. In this paper, we first prove the existence of an optimal peer assignment solution for a simple identity permutation function, and then formulate peer assignment with this identity permutation as a mixed-integer programming problem. Next, we discuss how to address the problem of dynamic peer departures during image transmission. Finally, we carry out experiments to evaluate the performance of proposed peer assignment algorithms.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.4
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• pp.441-450
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• 2015

The tactical communications network has to be deployed rapidly at military operation area and support the communications between the military command systems and the weapon systems. For that, the frequency assignment is required for backbone wireless links of tactical communications network without frequency interferences. In this paper, we propose a frequency assignment method using net filter discrimination (NFD) and graph coloring to avoid frequency interferences. The proposed method presents frequency assignment problem of tactical communications network as vertex graph coloring problem of a weighted graph. And it makes frequency assignment sequences and assigns center frequencies to communication links according to the priority of communication links and graph coloring. The evaluation shows that this method can assign center frequencies to backbone communication links without frequency interferences. It also shows that the method can improve the frequency utilization in comparison with HTZ-warfare that is currently used by Korean Army.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.237-253
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• 2019

For massive multiple-input multiple-output (MIMO) circumstances with time division duplex (TDD) protocol, pilot contamination becomes one of main system performance bottlenecks. This paper proposes an uplink pilot sequence assignment to alleviate this problem for spatially correlated massive MIMO circumstances. Firstly, a single-cell TDD massive MIMO model with multiple terminals in the cell is established. Then a spatial correlation between two channel response vectors is established by the large-scale fading variables and the angle of arrival (AOA) span with an infinite number of base station (BS) antennas. With this spatially correlated channel model, the expression for the achievable system capacity is derived. To optimize the achievable system capacity, a problem regarding uplink pilot assignment is proposed. In view of the exponential complexity of the exhaustive search approach, a pilot assignment algorithm corresponding to the distinct channel AOA intervals is proposed to approach the optimization solution. In addition, simulation results prove that the main pilot assignment algorithm in this paper can obtain a noticeable performance gain with limited BS antennas.