• International journal of advanced smart convergence
• /
• v.13 no.1
• /
• pp.1-11
• /
• 2024

Cognitive small cell networks, consisting of macro-cells and small cells, are foreseen as a promising candidate solution to address 5G spectrum scarcity. Recently, many technological issues (such as spectrum sensing, spectrum sharing) related to cognitive small cell networks have been studied, but the common control channel (CCC) establishment problem has been ignored. CCC is an indispensable medium for control message exchange that could have a huge significant on transmitter-receiver handshake, channel access negotiation, topology change, and routing information updates, etc. Therefore, establishing CCC in cognitive small cell networks is a challenging problem. In this paper, we propose a potential game theory-based approach for CCC establishment in cognitive radio networks. We design a utility function and demonstrate that it is an exact potential game with a pure Nash equilibrium. To maintain the common control channel list (CCL), we develop a CCC update algorithm. The simulation results demonstrate that the proposed approach has good convergence. On the other hand, it exhibits good delay and overhead of all networks.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.8
• /
• pp.629-637
• /
• 2000

Unbalance between user requirements and insufficient network resources makes a congestion. In the future since the communication networks will have very heavy traffic congestion will be more serious. The ATM networks was recommended to support the B-ISDN service for the future multimedia communication. In thie sense of congestion avoidance and recovery the ABR service category in ATM networks allows the feedback flow control mechanism to dynamically allocate the idle bandwidth of the network to users fairly and to control the network congestion rapidly In this paper we introduce a congestion control scheme using systematical approach to confirm robust stability with respect to unknown round trip delay for the network which has both unicast and multicast connections.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.9A
• /
• pp.916-922
• /
• 2007

Wireless networks (WNs) are developed and applied widely in a lot of areas. Now, a new generation of wireless networks is coming, and that is Wireless Mesh Network (WMN). At present, there are not so many researches which deal on this area. Most researches are derived from Mobile Ad hoc Networks (MANET) and WNs. In WMNs, there are some applications that require real-time delivery. To guarantee this, rate control and congestion control are needed. This problem leads to optimization issue in transport layer. In this paper, we propose a mathematical model which is applied in rate and congestion control in WNMs. From this model, we optimize rate and congestion control in WMNs by maximizing network utility. The proposed algorithm is implemented in distributed way both in links and sources.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.11
• /
• pp.5218-5233
• /
• 2018

The coexisting wireless body area networks (WBAN) is a very challenging issue because of strong inter-networks interference, which seriously affects energy consumption and spectrum utilization ratio. In this paper, we study a power control strategy with nearest neighbor nodes distribution for coexisting WBAN based on stochastic geometry. Using homogeneous Poisson point processes (PPP) model, the relationship between the transmission power and the networks distribution is analytically derived to reduce interference to other devices. The goal of this paper is to increase the transmission success probability and throughput through power control strategy. In addition, we evaluate the area spectral efficiency simultaneously active WBAN in the same channel. Finally, extensive simulations are conducted to evaluate the power control algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.411-415
• /
• 1994

An adaptive learning control scheme by use of multilayer neural networks for compensating for uncertainties in nonlinear dynamic system is examined. Multilayer neural networks are introduced to map the uncertainties in nonlinear dynamics and perform nonlinear state feedback. Parameters of neural networks are adjusted by conventional back-propagation algorithms modified with the projection operation. Effectiveness of the proposed scheme for tracking control are demonstrated through computer simulations.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.8
• /
• pp.219-226
• /
• 1994

Sinusoidal current tracking inverters have substantial advantages in high performance acdrive systems and various control strategies for the inverter have been proposed by several researchers. This paper develops a sinusoidal current tracking inverter with neural networks. The neural network are trained to follow a set of reference current waveforms by erro back propagation algorithm and the trained neural networks are applied to the current control. We compare neural networks method with conventional current control methods (fixed band and sinusiidal band hystersis methods) and simulation results are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.4
• /
• pp.1076-1089
• /
• 2012

Home automation networks are good environments for merging sensor networks and consumer electronics technologies. It is very important to reduce the energy consumption of each sensor node because sensor nodes operate with limited power based on a battery that cannot be easily replaced. One of the primary mechanisms for achieving low energy operation in energy-constrained wireless sensor networks is the duty-cycle operation, but this operation has several problems. For example, unnecessary energy consumption occurs during synchronization between transmission schedules and sleep schedules. In addition, a low duty-cycle usually causes more performance degradation, if the network becomes congested. Therefore, an appropriate control scheme is required to solve these problems. In this paper, we propose UDC (Unsynchronized Duty-cycle Control), which prevents energy waste caused by unnecessary preamble transmission and avoids congestion using duty-cycle adjustment. In addition, the scheme adjusts the starting point of the duty-cycle in order to reduce sleep delay. Our simulation results show that UDC improves the reliability and energy efficiency while reducing the end-to-end delay of the unsynchronized duty-cycled MAC (Media Access Control) protocol in sensor-based home automation networks.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.6
• /
• pp.991-1000
• /
• 1994

To control nonlinear systems adaptively, we improve learning speed of neural networks and present a novel control algorithm characterized by compensation of control inputs. In an error-backpropagation algorithm for tranining multilayer neural networks(MLNN's) the effect of the slope of activation functions on learning performance is investigated and the learning speed of neural networks is improved by auto-adjusting the slope of activation functions. The control system is composed of two MLNN's, one for control and the other for identification, with the weights initialized by off-line training. The control algoritm is modified by a control strategy which compensates the control error induced by the indentification error. Computer simulations show that the proposed control algorithm is efficient in controlling a nonlinear system with abruptly changing parameters.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.9
• /
• pp.1199-1206
• /
• 2002

This study is to verify the application characteristics of PI control and to simulate the applicability of Neural Networks control HVAC TRNSYS program. Each performance of HVAC by PI control and by Neural Networks is compared. According to the result of simulation, Neural Networks control is favorably applicable than previous PI control for the variation of weather condition and systematic changes.

• Journal of Communications and Networks
• /
• v.7 no.4
• /
• pp.408-416
• /
• 2005

Quality of service (QoS) provision is an important and indispensable function for multi-service wireless networks. In this paper, we present a new scheduling/admission control frame­work, including an efficient rate-guaranteed opportunistic scheduling (ROS) scheme and a coordinated admission control (ROS­CAC) policy to support statistic QoS guarantee in multi-service wireless networks. Based on our proposed mathematical model, we derive the probability distribution function (PDF) of queue length under ROS and deduce the packet loss rate (PLR) for individual flows. The new admission control policy makes admission decision for a new incoming flow to ensure that the PLR requirements of all flows (including the new flow) are satisfied. The numerical results based on ns-2 simulations demonstrate the effectiveness of the new joint packet scheduling/admission control framework.