• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.1
• /
• pp.58-73
• /
• 2014

As is well known, cooperative sensing can significantly improve the sensing accuracy as compared to local sensing in cognitive radio networks (CRNs). However, a large number of cooperative secondary users (SUs) reporting their local detection results to the fusion center (FC) would cause much overhead, such as sensing delay and energy consumption. In this paper, we propose a fast cooperative sensing scheme, called double threshold fusion (DTF), to reduce the sensing overhead while satisfying a given sensing accuracy requirement. In DTF, FC respectively compares the number of successfully received local decisions and that of failed receptions with two different thresholds to make a final decision in each reporting sub-slot during a sensing process, where cooperative SUs sequentially report their local decisions in a selective fashion to reduce the reporting overhead. By jointly considering sequential detection and selective reporting techniques in DTF, the overhead of cooperative sensing can be significantly reduced. Besides, we study the performance optimization problems with different objectives for DTF and develop three optimum fusion rules accordingly. Simulation results reveal that DTF shows evident performance gains over an existing scheme.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.3
• /
• pp.102-109
• /
• 1998

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment.For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental codintion changes, a robot select an appropriate beharior stategy. And its behavior stategy is stimulated and suppressed by other robot using communiation. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idotopic network hypothesis. And it is used for decision making of optimal swarm stragegy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.03a
• /
• pp.127-130
• /
• 1998

In this paper, we propose a method of cooperative control(T-cell modeling) and selection of group behavior strategy(B-cell modeling) based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-call respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based of clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.1
• /
• pp.287-304
• /
• 2012

Spectrum sensing is an important functionality for cognitive users to look for spectrum holes before taking transmission in dynamic spectrum access model. Unlike previous works that assume perfect knowledge of the SNR of the signal received from the primary user, in this paper we consider a realistic case where the SNR of the primary user's signal is unknown to both fusion center and cognitive radio terminals. A Kalman filter based adaptive Takagi and Sugeno's fuzzy system is designed to make the global spectrum sensing decision based on the observed energies from cognitive users. With the capacity of adapting system parameters, the fusion center can make a global sensing decision reliably without any requirement of channel state information, prior knowledge and prior probabilities of the primary user's signal. Numerical results prove that the sensing performance of the proposed scheme outperforms the performance of the equal gain combination based scheme, and matches the performance of the optimal soft combination scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.9 no.1
• /
• pp.19-26
• /
• 2010

In this paper, we propose an efficient decision rule in order to get better chance to detect the unused spectrum assigned to a licensed user and improve reliability of spectrum sensing performance. Each secondary user receives the signals from the licensed user. And the resulting signals input to an energy detector. Then, each sensing result is combined and used to make a decision whether the primary user is present at the licensed spectrum band or not. In order to make the reliable decision, we apply an efficient decision rule that is called as a majority rule in this paper. The simulation results show that spectrum sensing performance with the proposed decision rule is more reasonable and efficient than that with conventional decision rules.

• Industrial Engineering and Management Systems
• /
• v.12 no.4
• /
• pp.317-329
• /
• 2013

In recent years, for the purpose of solving the problem regarding environment protection and resource saving, certain measures and policies have been promoted to establish a green supply chains (GSC) with material flows from collection of used products to reuse of recycled parts in production of products. In this study, we propose an optimal operation of the GSC while considering the collection incentive of the used products and quality for recycling of used products. Two types of decision-making approaches are used for product quantity, collection incentive of used products and lower limit of quality level of reusable parts in the used products for recycling in the GSC. One is the decision-making under an independent policy in decentralized supply chains where a retailer and a manufacturer make decisions so as to maximize profits individually. The other is the decision-making under a cooperative policy in centralized supply chains where a retailer and a manufacturer make decisions cooperatively so as to maximize the whole system's profit. Additionally, we also discuss supply chain coordination as a manufacturer-retailer partnership based on profit sharing. Furthermore, we show the effect of the quality of the reusable parts on the optimal decisions. The collection incentive of the used products was found to bring more profitability to the GSC activity.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.315-318
• /
• 2003

In Korea construction project case, architectural construction project is curtailed production because information network process within multidisciplinary isn't smooth. Particularly, the construction is not insufficient about performance, cost and material, construction process, etc. in result various question arises because of design error in construction step. And various mistake is made because communication path within multidisciplinary isn't smooth in architectural design and design change process. Therefore The final object of this study is to propose the establishment method of decision support process for the cooperative design in order to provides improved design coordination and optimize the building system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.1A
• /
• pp.87-94
• /
• 2010

It is widely known that cooperative spectrum sensing in which secondary users scattered in some region collaborate to detect primary users can significantly reduce the performance degradation due to the fading phenomenon. Most of previous works on cooperative spectrum sensing are based on the assumption that the local spectrum sensing decisions of secondary users are statistically independent. However, there can be practically some statistical correlation between the local decisions of any two secondary users in close proximity, which is caused by shadowing effect. In order to evaluate the effect of this correlation on the performance of collaborative spectrum sensing, we assumed that, for the case that a primary user are active in the spectrum of interest, any two local decisions are statistically correlated to each other with some level of constant correlation and independent otherwise, and analyzed the achievable throughput with the degree of correlation varying. The results showed that, as the degree of correlation gets higher, the throughput increases for the case of the AND fusion rule and decreases for the OR fusion rule.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7A
• /
• pp.560-568
• /
• 2012

Spectrum sensing and spectrum decision are the main functions that cognitive radios (CRs) have to perform in order to get the best available spectrum band for the establishment of a wireless communication. These problems are worsened in the presence of users with different demands and spectrum channels with different properties in a heterogeneous network. The primary objective in this work is to design and simulate a new spectrum decision algorithm for heterogeneous cognitive radio system. To this end, first, we consider all cognitive users are separated into different traffic classes according to their Quality of Service (QoS). The cognitive users within one traffic class perform spectrum sensing in centralized group-based cooperative spectrum sensing system and the users of different traffic classes share the sensing results. Second, we propose a novel use of the Analytic Hierarchy Process (AHP) to optimally select available bands according to user requirements and detected spectrum channel characteristics (SCC). In this paper, utility function is used as spectrum decision algorithm. Simulation results demonstrate that the proposed method shows can effectively select the best available spectrum channels with a low complexity.

• Journal of Auto-vehicle Safety Association
• /
• v.11 no.3
• /
• pp.19-29
• /
• 2019

Recently, autonomous vehicles have been studied actively. Autonomous vehicles can detect objects around them using their on board sensors, estimate collision probability and maneuver to avoid colliding with objects. Many algorithms are suggested to prevent collision avoidance. However there are limitations of complex and diverse environments because algorithm uses only the information of attached environmental sensors and mainly depends on TTC (time-to-Collision) parameter. In this paper, autonomous driving algorithm using I2V communication-based cooperative sensing information is developed to cope with complex and diverse environments through sensor fusion of objects information from infrastructure camera and object information from equipped sensors. The cooperative sensing based autonomous driving algorithm is implemented in autonomous shuttle bus and the proposed algorithm proved to be able to improve the autonomous navigation technology effectively.