• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1716-1721
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• 2008

Currently, Wireless Networks have some nice characteristics such as multi-hop, multi-channel, multi-radio, etc but these kinds of resources are not fully used. The most difficulty to solve this issue is to solve mixed integer optimization. This paper proposes a method to solve a class of mixed integer optimization for wireless networks by using AMPL modeling language with CPLEX solver. The result of method is scheduling and congestion control in multi-channel multi-radio wireless networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8B
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• pp.681-688
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• 2008

In this paper, we propose a new price-based call admission control algorithm for multi-class communication networks. When a call arrives at the network, it informs the network of the number of requested circuits and the minimum amount of time that it will require. The network provides the optimal price for the arrived call with which it tries to maximize its expected revenue. The optimal price is dynamically adjusted based on the information of the arrived call, and the present and the estimated future congestion level of the network during the reservation time of the call. If the call accepts the price, it is admitted. Otherwise, it is rejected. We compare the performance of our dynamic pricing algorithm with that of the static pricing algorithm by Courcoubetis and Reiman [1], and Paschalidis and Tsitsiklis [2]. By the comparison, we show that our dynamic pricing algorithm has better performance aspects such as higher call admission ratio and lower price than the static pricing algorithm, although these two algorithms result in almost the same revenue as shown in [2]. This implies that, in the competitive situation, the dynamic pricing algorithm can attract more users than the static pricing algorithm, generating more revenue. Moreover, we show that if a certain fixed connection fee is introduced to the price for a call, our dynamic pricing algorithm yields more revenue.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7B
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• pp.771-779
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• 2011

It is expected that many heterogeneous wireless systems, such as 3GPP LTE systems, WiMAX systems and WLAN systems, will coexist in the next generation wireless communication environments. Integrated radio resource management and seamless vertical handoff (VHO) should be supported to provide integrated communication services over multi-radio access networks. A new class of adaptive VHO system that views the handoff problem as a pattern recognition problem is proposed. In this paper, we propose a unified radio resource management (URRM) architecture and Support Vector Machine (SVM) based vertical handoff decision system. Extensive simulation studies show the proposed VHO algorithm outperforms RSS based VHO algorithms in terms of throughput and service cost.

• ETRI Journal
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• v.38 no.6
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• pp.1153-1162
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• 2016

This paper addresses the resource allocation (RA) problem in multi-cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered-such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP-hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub-gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

• Journal of Communications and Networks
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• v.7 no.2
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• pp.157-170
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• 2005

The combination of multiple antennas and multi-carrier code division multiple-access (MC-CDMA) is a strong candidate for the downlink of the next generation mobile communications. The study of such systems in scenarios that model real-life trans-missions is an additional step towards an optimized achievement. We consider a realistic MIMO channel with two or four transmit antennas and up to two receive antennas, and channel state information (CSI) mismatches. Depending on the mobile terminal (MT) class, its number of antennas or complexity allowed, different data-rates are proposed with turbo-coding and asymptotic spectral efficiencies from 1 to 4.5 bit/s/Hz, using three algorithms developed within the European IST-MATRICE project. These algorithms can be classified according to the degree of CSI at base-station (BS): i) Transmit space-frequency prefiltering based on constrained zero-forcing algorithm with complete CSI at BS; ii) transmit beamforming based on spatial correlation matrix estimation from partial CSI at BS; iii) orthogonal space-time block coding based on Alamouti scheme without CSI at BS. All presented schemes require a reasonable complexity at MT, and are compatible with a single-antenna receiver. A choice between these algorithms is proposed in order to significantly improve the performance of MC-CDMA and to cover the different environments considered for the next generation cellular systems. For beyond-3G, we propose prefiltering for indoor and pedestrian microcell environments, beamforming for suburban macrocells including high-speed train, and space-time coding for urban conditions with moderate to high speeds.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.144-150
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• 2017

Recently, deep learning is used for intelligent processing and accuracy improvement of data. It is formed calculation model composed of multi data processing layer that train the data representation through an abstraction of the various levels. A category of deep learning, convolution neural network is utilized in various research fields, which are human pose estimation, face recognition, image classification, speech recognition. When using the deep layer and lots of class, CNN that show a good performance on image classification obtain higher classification rate but occur the overfitting problem, when using a few data. So, we design the training network based on convolution neural network and trained our image data set for object classification in few class problem. The experiment show the higher classification rate of 7.06% in average than the previous networks designed to classify the object in 1000 class problem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2233-2248
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• 1999

The TMN that appears to operate the various communication networks generally and efficiently is developed under the different platform environment such as the different hardware and the different operating system. One of the main problems is that all the agents of the TMN system must be duplicated and maintain the software and the data blocks that perform the identical function. Therefore, the standard of the Q3 interface development cannot be defined and the multi-platform cannot be supported in the development of the TMN agent. In order to overcome these problems, the Farming methodology that is based on the Farmer model has been suggested. With the Farming methodology, the software and the data components which are duplicated and stored in each distributed object are saved in the platform independent class repository(PICR) by converting into the format of the independent componentware in the platform, so that the componentwares that are essential for the execution can be loaded and used statically or dynamically from PICR as described in the framework of each distributed object. The distributed TMN agent of the personal communication network is designed and developed by using the Farmer model.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.225-232
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• 2020

The underlaying communication scheme in 5G cellular network is a very promising resource sharing scheme, and it is an effective scheme for improving service performance of 5G and reducing communication load between a cellular link and a device to device (D2D) link. This paper proposes the algorithm to minimize the resource interference that occurs when performing 5G-based multi-class service on gNB(gNodeB) and the cooperative priority-based resource allocation scheduling scheme (CPRAS) to maximize 5G communication service according to the analyzed control conditions of interference. The proposed CPRAS optimizes communication resources for each device, and it optimizes resource allocation according to the service request required for 5G communication and the current state of the network. In addition, the proposed scheme provides a function to guarantee giga-class service by minimizing resource interference between a cellular link and a D2D link in gNB. The simulation results show that the proposed scheme is better system performance than the Pure cellular and Force cellular schemes. In particular, the higher the priority and the higher the cooperative relationship between UE(User Equipment), the proposed scheme shows the more effective control of the resource interference.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.123-134
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• 2002

The requirement for QoS (Quality of Service) has become an important Issue as real-time or high bandwidth services are increasing, such as Internet Telephony, Internet broadcasting, and multimedia service etc. In order to guarantee the QoS of Internet application services, several approaches are being sought including IntServ (Integrated Service) DiffServ(Differentiated Srvices), and MPLS(Multi-Protocol Label Switching). In this paper, we describe the performance analysis of QoS guarantee mechanism using the DiffServ. To analyze how the DiffServ performance was affected by diverse input traffic models and the weight value in WFQ(Weighted Fair Queueing), we simulated and performed performance evaluation under a random, bursty, and self-similar input traffic models and for diverse input parameters. leased on the results of performance analysis, it was confirmed that significant difference exist in packet delay and loss depending on the input traffic models used. However, it was revealed that QoS guarantee is possible to the EF (expedited Forwarding) class and the service separation between RF and BE (Best Effort) classes may also be achieved. Next, we discussed the performance synthesis problem. (i. e. derived the conservation laws for a DiffServ networks, and analysed the performance variation and dynamic behavior based on the resource allocation (i.e., weight value) in WFQ.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2493-2503
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• 1999

The TMN that appears to operate the various communication networks generally and efficiently is developed under the different platform environment such as the different hardware and the different operating system. One of the main problems is that all the agents of the TMN system must be duplicated and maintain the software and the data blocks that perform the identical function. Therefore, the multi-platform cannot be supported in the development of the TMN agent. In order to overcome these problems, the Farming methodology that is based on the Farmer model has been suggested. With the Farming methodology, the software and the data components which are duplicated and stored in each distributed object are saved in the platform independent class repository (PICR) by converting into the format of the independent componentware in the platform, so that the componentwares that are essential for the execution can be loaded and used statically or dynamically from PICR as described in the framework of each distributed object. The distributed TMN agent of the personal communication network is designed and developed by using the Farmer model.