Juhyeon Lee

Channel prediction-based channel allocation scheme for multichannel cognitive radio networks

Cognitive radio (CR) has been proposed to solve the spectrum utilization problem by dynamically exploiting the unused spectrum. In CR networks, a spectrum selection scheme is an important process to efficiently exploit the spectrum holes, and an efficient channel allocation scheme must be designed to minimize interference to the primary network as well as to achieve better spectrum utilization. In this paper, we propose a multichannel selection algorithm that uses spectrum hole prediction to limit the interference to the primary network and to exploit channel characteristics in order to enhance channel utilization. The proposed scheme considers both the interference length and the channel capacity to limit the interference to primary users and to enhance system performance. By using the proposed scheme, channel utilization is improved whereas the system limits the collision rate of the CR packets.

A Method to Identify the Identification Eye Status for Drowsiness Monitoring System

This paper describes a method for detecting the pupil region and identification of the eye status for driver drowsiness detection system. This program detects a driver’s face and eyes using viola-jones face detection algorithm and extracts the pupil area by utilizing mean values of each row and column on the eye area. The proposed method uses binary images and the number of black pixels to identify the eye status. Experimental results showed that the accuracy of classification eye status(open/close) was above 90%.

Modified proportional fair scheduling for Cognitive Radio networks

Channel selection is one of important issues in Cognitive Radio (CR) networks and it is closely related to the channel characteristics and primary users behavior. In this paper, we proposed a modified proportional fairness scheduling which not only consider the fairness and the throughput but also take the primary user characteristics of each channel into account.

Routing algorithm using channel based hop counting for wireless ad-hoc networks

A wireless ad-hoc network is a decentralized wireless network and a routing protocol is important to support efficient data transmission in wireless ad-hoc network. Conventional routing schemes considered the number of hops to determine the routing path. However, channel condition is an important factor to determine successful data transmission. In this paper, we propose a routing algorithm that consider successful transmission rate of each link. The advantage of the proposed algorithm is that it can be easily applied to conventional routing algorithms by using channel-based hop count.

Channel Capacity-Based Multi-Channel Allocation in Cognitive Radio Networks

Dynamically exploiting unused-spectrum, cognitive radio has been proposed to solve spectrum utilization problem. In cognitive radio, it is important to minimize the interference to primary service as well as to provide efficient channel allocation. In this paper, we propose a multi-channel allocation scheme based on spectrum hole prediction. Proposed scheme considered both interference length and channel capacity to limit the interference to primary user as well as to enhance system performance. Simulation results show the proposed scheme improves the system throughput.

Chaotic Prediction Based Channel Sensing in CR System

Cognitive radio (CR) has been recently proposed to dynamically access unused-spectrum. Since the spectrum availability for opportunistic access is determined by spectrum sensing, sensing control is identified as one of the most crucial issues of cognitive radio networks. Out-of-band sensing to find an available channels to sense. Sensing is also required in case of spectrum hand-off. Sensing process needs to be done very fast in order to enhance the quality of service (QoS) of the CR nodes, and transmission not to be cut for longer time. During the sensing, the PU(primary user) detection probability condition should be satisfied. We adopt a channel prediction method to find target channels. Proposed prediction method combines chaotic global method and chaotic local method for channel idle probability prediction. Global method focus on channel history information length and order number of prediction model. Local method focus on local prediction trend. Through making simulation, Proposed method can find an available channel with very high probability, total sensing time is minimized, detection probability of PU`s are satisfied.

Channel Scheduling for Cognitive Radio Networks

In Cognitive Radio network, spectrum selection scheme is one of a important part to manage idle spectrums efficiently. However, in CR networks, they have to adopt time-varying channel availability to minimize the interference to primary users (PU), and be able to manage spectrum resources efficiently. In this paper, we proposed a modified PF scheduler which can be appropriate to schedule downlink CR users and channels, by considering the fairness and the throughput as well as the primary user characteristics of each channel.