• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.398-405
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• 2005

The multiuser detection (MUD) based wireless receiver requires more accurate channel estimation than the single user detection (SUD) schemes such as Rake receiver, and hence the post processing is required for MUD to clean up the estimated channel coefficients by eliminating the noise only coefficients. The adaptive post processing method is proposed in order to provide more accurate channel responses and the power level of the background noise and interferences at the cost of the negligible processing delay compared to the conventional method based on the threshold test with the threshold value relative to the noise variance. The simulations are performed in 3GPP-TDD mode environment. The results show that the noise estimation error of the proposed method is maximum $10\%$, which is much smaller than $50\%$ maximum error of the conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.577-594
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• 2020

Service Function Chaining (SFC) supports services through linking an ordered list of functions. There may be multiple instances of the same function, which provides a challenge to select available instances for all the functions in an SFC and generate a specific Service Function Path (SFP). Aiming to solve the problem of SFP selection, we propose an architecture consisting of distributed SFP algorithm and central control mechanism. Nodes generate distributed routings based on the first function and destination node in each service request. Controller supervises all of the distributed routing tables and modifies paths as required. The architecture is scalable, robust and quickly reacts to failures because of distributed routings. Besides, it enables centralized and direct control of the forwarding behavior with the help of central control mechanism. Simulation results show that distributed routing tables can generate efficient SFP and the average cost is acceptable. Compared with other algorithms, our design has a good performance on average cost of paths and load balancing, and the response delay to service requests is much lower.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1220-1225
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• 2010

This paper proposes a novel active noise control (ANC) approach that uses an IIR filter and neural network techniques to effectively reduce interior noise. We construct a multiple-channel IIR filter module which is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimization based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Lastly, we present the results of a numerical study to test our ANC methodology with realistic interior noise measurement obtained from Korean railway trains.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1281-1286
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• 2010

Ant-based routing methods belong to a class of ant colony optimization algorithms which apply the behavior of ants in nature to routing mechanism. Since the topology of mobile ad-hoc network(MANET) changes dynamically, it is needed to establish paths based on the local information. Subsequently, it is known that routing in MANET is one of applications of ant colony optimization. In this paper, we propose a routing method, namely EPMAR, which enhances SIR in terms of route selection method and the process upon link failure. The performance of the proposed method is compared with those of AntHocNet and SIR. Based on he analysis, it is proved that the proposed method provided higher packet delivery ratio and less critical link failure than AntHocNet and SIR.

• Current Optics and Photonics
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• v.7 no.5
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• pp.518-528
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• 2023

As an effective means of remotely detecting the spectral information of the object, the spectral calibration for the Savart polarization interference imaging spectrometer (SPIIS) is a basis and prerequisite of information quantification, and its experimental calibration scheme is firstly proposed in this paper. In order to evaluate the accuracy of the spectral information acquisition, the linear interpolation, cubic spline interpolation, and piecewise cubic interpolation algorithms are adopted, and the precision of the quadratic polynomial fitting is the highest, whose fitting error is better than 5.8642 nm in the wavelength range of [500 nm, 820 nm]. Besides, the inversed value of the spectral resolution for the monochromatic light is greater than the theoretical value, and the deviation between them becomes larger with the wavelength increasing, which is mainly caused by the structural design of the SPIIS, together with the rationality of the spectral restoration algorithm and the selection of the maximum optical path difference (OPD). This work demonstrates that the SPIIS has achieved high performance assuring the feasibility of its practical use in various fields.

• Proceedings of the IEEK Conference
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• summer
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• pp.330-333
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• 2004

Microsensor nodes is energy limited in sensor networks. If nodes had been stop in working, sensor network can't acquire sensing data in that area as well as routing path though the sensor can't be available. So, it's important to maximize the life of network in sensor network. In this paper, we look at communication protocol, which is modified by LEACH(Low-Energy Adaptive Clustering Hierarchy). We extend LEACH's stochastic cluster-head selection algorithm by a Position-based Selection (PB-Leach). This method is that the sink divides the topology into several areas and cluster head is only one in an area. PB-Leach can prevent that the variance of the number of Cluster-Head is large and Cluster-Heads are concentrated in specific area. Simulation results show that PB-Leach performs better than leach by about 100 to $250\%.$

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.131-137
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• 2007

Recently, Ant Colony Optimization (ACO) is emerged as a simple yet powerful optimization algorithm for routing and load-balancing of both wired and wireless networks. However, there are few researches trying to adopt ACO to enhance routing performance in WSN owing to difficulties in applying ACO to WSN because of stagnation effect. In this paper, we propose an energy-efficient path selection algorithm based on ACO for WSN. The algorithm is not by simply applying ACO to routing algorithm but by introducing a mechanism to alleviate the influence of stagnation. By the simulation result, the proposed algorithm shows better performance in data propagation delay and energy efficiency over Directed Diffusion which is one of the outstanding schemes in multi-hop flat routing protocols for WSN. Moreover, we checked that the proposed algorithm is able to mitigate stagnation effect than simple ACO adoption to WSN.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.30-45
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• 2014

Recently, multimedia application users who demand for ubiquitous computing environment are rapidly increasing, and wireless mesh network is receiving attention as a cost-effective key technology for next generation wireless networking. When multiple flows are transmitting data at the same time in the network, routing for path selection of each flow and link resource allocation for data transmission of each flow are one of the key factors that influence to the effectiveness of the network directly. In this paper, we consider problems for path discovery and resource allocation of links at the same time and we propose an algorithm based on mathematical modeling using a technique for cross-layer optimization design in STDMA-based wireless mesh networks that can enhance transfer performance for each flow. We show by performance analysis that the proposed algorithm can enhance the throughput performance by maximally utilizing given bandwidth resources when the number of flows increase in multi-hop wireless mesh networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.951-958
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• 2000

In wavelength-routed all-optical networks, signals are transmitted on a direct optical path, or a lightpath, in a single-hop manner without opto-electronic/electro-optic(OE/EO) conversion at intermediate nodes. However, due to the physical constraints of optical elements such as ASE noise and crosstalk signals can be degraded un a long path. To establish a connection under such impairments, the optical signal may need to be regenerated at intermediate nodes, dividing a lightpath into two or more fragments. However, since signal regeneration at intermediate nodes requires additional network resources, the selection of these nodes should be made carefully to minimize blocking of other lightpaths. In this paper, we deal with the problem of establishing a lightpath in a multihop manner under physical constraints. We provide both minimal-cost and heuristic algorithms for locating signal regeneration nodes(SRNs). For a minimal-cost algorithm, we formulate the problem using dynamic programming(DP) such that blocking of other lightpaths due to the lack of transmitters/receivers(TXs/RXs) and wavelengths is minimized throughout the network.

• ETRI Journal
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• v.38 no.4
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• pp.714-723
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• 2016

Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.