• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4453-4468
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• 2015

This paper investigates optimization-based base station (BS) placement. An optimization model is defined and the BS placement problem is transformed to a lexicographical stratified programming (LSP) model for a given trajectory, according to different accuracy requirements. The feasible region for BS deployment is obtained from the positioning system requirement, which is also solved with signal coverage problem in BS placement. The LSP mathematical model is formulated with the average geometric dilution of precision (GDOP) as the criterion. To achieve an optimization solution, a tolerant factor based complete stratified series approach and grid searching method are utilized to obtain the possible optimal BS placement. Because of the LSP model utilization, the proposed algorithm has wider application scenarios with different accuracy requirements over different trajectory segments. Simulation results demonstrate that the proposed algorithm has better BS placement result than existing approaches for a given trajectory.

• ETRI Journal
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• v.45 no.5
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• pp.887-898
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• 2023

Aerial base stations (ABSs) seem promising to enhance the coverage and capacity of fifth-generation and upcoming networks. With the flexible mobility of ABSs, they can be positioned in air to maximize the number of users served with a guaranteed quality of service (QoS). However, ABSs may be overloaded or underutilized given inefficient placement, and user association has not been well addressed. Hence, we propose a three-dimensional ABS placement scheme with a delay-QoS-driven user association to balance loading among ABSs. First, a load balancing utility function is designed based on proportional fairness. Then, an optimization problem for joint ABS placement and user association is formulated to maximize the utility function subject to statistical delay QoS requirements and ABS collision avoidance constraints. To solve this problem, we introduce an efficient modified gray wolf optimizer for ABS placement with a greedy user association strategy. Simulation results demonstrate that the proposed scheme outperforms baselines in terms of load balancing and delay QoS provisioning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2B
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• pp.137-144
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• 2002

In this paper, we optimize the base station placement and transmission power using genetic approach. A new representation describing base station placement and transmit power with real number is proposed, and new genetic operators are introduced. This new representation can describe the locations, powers, and number of base stations, Considering coverage, power and economy efficiency, we also suggest a weighted objective function. Our algorithm is applied to an obvious optimization problem, and then it is verified. Moreover, our approach is tried in inhomogeneous traffic distribution. Simulation result proves that the algorithm enables to fad near optimal solution according to the weighted objective function.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.761-765
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• 2009

This research aims an optimal placement of Mobile Base Station (MBS) under HAP based network configurations with the restrictions of HAP capabilities. With clustering algorithm based on BIRCH, mobile ground nodes are clustered and the centroid of the clusters will be the location of MBS. The hierarchical structure of BIRCH enables mobile node management by CF tree and the restrictions of maximum nodes per MBS and maximum radio coverage are accomplished by splitting and merging clusters. Mobility models based on Jeju island are used for simulations and such restrictions are met with proper placement of MBS.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1525-1535
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• 2008

High Altitude Platform (HAP) based networks deploy network infrastructures of Mobile Base Station (MBS) in a form of Unmanned Aerial Vehicle (UAV) at stratosphere in order to build network configuration. The ultimate goal of HAP based network is a wireless network service for wide area by deploying multiple MBS for such area. In this paper we assume multiple UAVs over designated area and solve the MBS placement and coverage problem by clustering the mobile ground nodes. For this study we assumed area around Cheju island and nearby naval area where multiple mobile and fixed nodes are deployed and requires HAP based networking service. By simulation, visual results of stratospheric MBS placement have been presented. These results include clustering, MBS placement and coverage as well as dynamic reclustering according to the movement of mobile ground nodes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.321-333
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• 2005

With the limited frequency spectrum and an increasing demand for cellular communication services, the problem of channel assignment becomes increasingly important. However, finding a conflict free channel assignment with the minimum channel span is NP hard. As demand for services has expanded in the cellular segment, sever innovations have been made in order to increase the utilization of bandwidth. The innovations are cellular concept, dynamic channel assignment and hierarchical network design. Hierarchical network design holds the public eye because of increasing demand and quality of service to mobile users. We consider the frequency assignment problem and the base station placement simultaneously. Our model takes the candidate locations emanating from this process and the cost of assigning a frequency, operating and maintaining equipment as an input. In addition, we know the avenue and demand as an assumption. We propose the network about the profit maximization. This study can apply to GSM(Global System for Mobile Communication) which has 70% portion in the world. Hierarchical network design using GA(Genetic Algorithm) is the first three-tier (Macro, Micro, Pico) model, We increase the reality through applying to EMC (Electromagnetic Compatibility Constraints). Computational experiments on 72 problem instances which have 15${\sim}$40 candidate locations demonstrate the computational viability of our procedure. The result of experiments increases the reality and covers more than 90% of the demand.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3892-3912
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• 2021

The recent rapid growth of mobile network traffic places multi-access edge computing in an important position to reduce network load and improve network capacity and service quality. Contrasting with traditional mobile cloud computing, multi-access edge computing includes a base station cooperative cache layer and user cooperative cache layer. Selecting the most appropriate cache content according to actual needs and determining the most appropriate location to optimize the cache performance have emerged as serious issues in multi-access edge computing that must be solved urgently. For this reason, a cache placement algorithm based on comprehensive utility in big data multi-access edge computing (CPBCU) is proposed in this work. Firstly, the cache value generated by cache placement is calculated using the cache capacity, data popularity, and node replacement rate. Secondly, the cache placement problem is then modeled according to the cache value, data object acquisition, and replacement cost. The cache placement model is then transformed into a combinatorial optimization problem and the cache objects are placed on the appropriate data nodes using tabu search algorithm. Finally, to verify the feasibility and effectiveness of the algorithm, a multi-access edge computing experimental environment is built. Experimental results show that CPBCU provides a significant improvement in cache service rate, data response time, and replacement number compared with other cache placement algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.183-189
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• 2018

This paper proposes distributed file placement and coverage expansion techniques for mitigating the traffic bottleneck in backhaul for small-cell networks. In order to minimize the backhaul load with limited memory space, the proposed scheme controls the coverage and file placement of base station according to file popularity distribution and memory space of base stations. In other words, since the cache hit ratio is low when there is small memory capacity or widespread file popularity distribution, the base stations expand its coverage and cache different set of files for the user located in overlapped area to exploit multiple cached file sets of base stations. Our simulation results show that the proposed scheme outperforms the conventional cache strategy in terms of network throughput when there is small memory capacity or widespread file popularity distribution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1549-1555
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• 2009

The Relay node placement problem is one of the most important requirements for many wireless sensor networks because the lifetime of sensor networks is closely related with the placement of relay nodes which receive sensed data from sensor nodes and forward them to the base station. Relay node placement problem has focused at minimization of dissipated total energy of the sensor nodes in whole networks. However, minimum total energy causes the unbalance of consumed energy in sensor nodes due to different distances between relay nodes and sensor nodes. This paper proposes the concept of energy balance ratio and finds the locations of relay nodes using objective functions which maximize the energy balance ratio. Maximizing this ratio results in maximizing the network lifetime by minimizing the energy consumption of large-scale sensor networks. However, finding a solution to relay node placement problem is NP-hard and it is very difficult to get exact solutions. Therefore, we get approximate solutions to EBR-RNP problem which considers both energy balance ratio and relay node placement using constraint programming.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.181-189
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• 2010

HAP(High Altitude Platform) is a stationary aerial platform positioned in the stratosphere between 17Km and 22Km height and it could act as an MBS (Mobile Base Station). HAP based Network has advantages of both satellite system and terrestrial communication system. In this paper we study the deploy of multiple HAP MBS that can provides efficient communication for users. For this study, EM(Expectation Maximization) clustering algorithm is used to cluster terrestrial mobile nodes. The object of this paper is improving EM algorithm into the clustering algorithm for efficiency in variety aspects considering distance between mobile terminal units and speed of mobile terminal units, and estimating performance of HAP MBS deploy technique with use of improved EM algorithm using RWP (Random Waypoint) node mobility.