• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.103-109
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• 2010

Total performance is improved by minimizing the channel interference between links in wireless mesh networks (WMNs). The paper refines on the CB-CA [1] to be suitable for multi-radio multi-channel (MRMC) WMNs. The CB-CA is the cluster-based channel assignment algorithm for one radio three channel WMN based on IEEE 802.11b/g. The CB-CA does not perform the channel scanning and the channel switching between the cluster heads (CHs) and the edge gateway nodes (EGs). However, the use of co-channel for links between CHs and EGs brings the problem of channel interference among many nodes. We propose and evaluate an improved CB-CA algorithm to solve this problem in MRMC WMNs. The proposed algorithm discriminates between transmission channel and receive channel and assigns channels to each interface randomly and advertises this information to neighbor clusters in order to be assigned no-interference channel between clusters. Therefore, the proposed algorithm can minimize the interference between clusters and also improve QoS, since it can use multiple interfaces and multiple channels.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.99-105
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• 2009

This paper suggests novel signal processing methods for optimal beamforming of smart antenna system in CDMA2000 mobile communication environments. This method utilize characteristics of the reverse pilot channel of CDMA2000 mobile communication systems, and applies them to improve the performance of an adaptive algorithm, which is used to a smart antenna system for beamforming. To perform the best beamforming, it is important to get an exact beamforming algorithm. This paper proposed an algorithm based on Laglange multiplier which has such an adaptive process, and also proposed the method to demodulate the received signal through array antenna using pilot channel in CDMA2000 environment. This paper analysed the enhanced performance of proposed algorithm in various signal environment through signal modeling of physical layer in CDMA2000 reverse link.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.318-330
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• 2015

In wearable sensor systems (WSSs), sensor nodes are deployed around human body parts such as the arms, the legs, the stomach, and the back. These sensors have limited lifetimes because they are battery-operated. Thus, transmission power control (TPC) is needed to save the energy of sensor nodes. The TPC should control the transmission power level (TPL) of sensor nodes based on current channel conditions. However, previous TPC algorithms did not precisely estimate the channel conditions. Therefore, we propose a new TPC algorithm that uses an accelerometer to directly measure the current channel condition. Based on the directly measured channel condition, the proposed algorithm adaptively adjusts the transmission interval of control packets for updating TPL. The proposed algorithm is efficient because the power consumption of the accelerometer is much lower than that of control packet transmissions. To evaluate the effectiveness of our approach, we implemented the proposed algorithm in real sensor devices and compared its performance against diverse TPC algorithms. Through the experimental results, we proved that the proposed TPC algorithm outperformed other TPC algorithms in all channel environments.

• 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 Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.75-81
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• 2017

This paper estimate a desired signal in a correlation wireless communication. The transmitted signal is mixed with the information signal, interference, and noise in wireless channel, and it is incident on the receiver. In this paper, we apply MUSIC algorithm and sub-array method to recover the total rank of the correlation matrix in order to estimation a desired signal among receiving signals. Through simulation, we analyze to compare the proposed method with the classical MUSIC algorithm. As a result of the simulation, the proposed method improved the resolution about 10degrees compared to the conventional MUSIC algorithm. We prove the superiority of the proposed method for the desired signal estimation in correlation channel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3771-3788
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• 2015

This paper studies the distributed energy efficient resource management in the Internet of Things (IoT). Wireless communication networks support the IoT without limitation of distance and location, which significantly impels its development. We study the communication channel and energy management in the wireless communication network supported IoT to improve the ability of connection, communication, share and collaboration, by using the game theory and distributed learning algorithm. First, we formulate an energy efficient neighbor collaborative game model and prove that the proposed game is an exact potential game. Second, we design a distributed energy efficient channel selection learning algorithm to obtain the global optimum in a distributed manner. We prove that the proposed algorithm will asymptotically converge to the global optimum with geometric speed. Finally, we make the simulations to verify the theoretic analysis and the performance of proposed algorithm.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.99-105
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• 2012

Recently, there are many user selection algorithms in multi user multiple-input multiple-output (MU-MIMO) systems. One of well-known user selection methods is Semi orthogonal user selection (SUS). It is an algorithm maximizing channel capacity. However, it is applicable only when user's antenna is one. We propose a generalized user selection algorithm regardless of the number of user's antennas. In the proposed scheme, Base station (Bs) selects the first user who has the highest determinant of channel and generates a user group that correlation with first user's channel is less than allowance of correlation. Then, each determinant of channels made up of first user's channel and a user's channel in the generated group is calculated and BS selects the next user who has the highest determinant of that. BS selects following users by repeating above procedure. In this paper, we get better performance because of selecting users who have the highest determinant of channel as well as allowance of correlation optimally calculated through matrix operations.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.13-21
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• 2022

Recently, in wireless video sensor networks(WVSN), various schemes for efficient video data transmission have been studied. In this paper, a layer based cooperative relaying(LCR) algorithm is proposed for minimizing scalable video transmission distortion from packet loss in WVSN. The proposed LCR algorithm consists of two modules. In the first step, a parameter based error propagation metric is proposed to predict the effect of each scalable layer on video quality degradation at low complexity. In the second step, a layer-based cooperative relay algorithm is proposed to minimize distortion due to packet loss using the proposed error propagation metric and channel information of the video sensor node and relay node. In the experiment, the proposed algorithm showed that the improvement of peak signal-to-noise ratio (PSNR) in various channel environments, compared to the previous algorithm(Energy based Cooperative Relaying, ECR) without considering the metric of error propagation.The proposed LCR algorithm minimizes video quality degradation from packet loss using both the channel information of relaying node and the amount of layer based error propagation in scalable video.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.