• 한국HCI학회논문지
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• 제14권2호
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• pp.31-39
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• 2019

본 연구는 빠르게 발전하는 음성 기반의 디바이스가 스크린 중심의 미디어 멀티태스킹 환경에 어떤 변화를 가져올 수 있을지 확인하고자 했다. 서로 다른 자원 구조를 가진 과업을 동시에 수행할 때 정보 처리 효율이 높아진다는 이론적 근거를 토대로, 시각 주의가 필요한 과제와 음성 또는 스크린 기반의 디바이스를 활용해 정보를 검색하는 과업을 동시에 수행하는 실험이 진행되었다. 실험 결과, 과업수행 환경과 인터페이스 감각양식은 모두 인지부하에 유의미한 영향을 미쳤다. 음성 인터페이스 그룹에서 전반적으로 인지부하 수준이 높게 나타났는데, 단독으로 사용된 단일 과업 조건보다 시각 과제를 동시에 수행한 다중 과업 조건에서 시각 인터페이스 그룹과의 차이가 줄어들었다. 과업 수행도의 경우 음성 인터페이스 그룹에서 시각 과제에 대한 수행능력이 시각 인터페이스 그룹보다 더 높게 측정되었다. 이러한 결과는 멀티태스킹 환경에서 음성 인터페이스를 사용했을 때 동시적 과업을 청각 경로와 시각 경로로 나누어 처리함으로써 인지부하와 과업수행에 이점이 나타났음을 의미한다. 이는 시각 자원의 충돌이 발생하기 쉬운 스크린 중심의 미디어 멀티태스킹 환경에서 음성 기반의 디바이스가 효율적 정보 처리를 촉진시키는 잠재적 역할을 할 수 있다는 함의점을 제공한다. 본 연구는 다중 자원 이론을 통해 자원의 분산처리에 대한 이론적 증거를 제시하고, 스레드 인지 모델을 기반으로 음성 인터페이스를 활용했을 때의 이점을 더욱 구체적으로 규명하고자 했다.

• 전기학회논문지
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• 제61권4호
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• pp.629-631
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• 2012

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.

• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4748-4765
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• 2016

We consider a virtualized cognitive radio (CR) network, where multiple virtual network operators (VNOs) who own different virtual cognitive base stations (VCBSs) share the same physical CBS (PCBS) which is owned by an infrastructure provider (InP), sharing the spectrum with the primary user (PU). The uplink scenario is considered where the secondary users (SUs) transmit to the VCBSs. The PU is protected by constraining the interference power from the SUs. Such constraint is applied by the InP through pricing the interference. A Stackelberg game is formulated to jointly maximize the revenue of the InP and the individual utilities of the VNOs, and then the Stackelberg equilibrium is investigated. Specifically, the optimal interference price and channel allocation for the VNOs to maximize the revenue of the InP and the optimal power allocation for the SUs to maximize the individual utilities of the VNOs are derived. In addition, a low‐complexity ±‐optimal solution is also proposed for obtaining the interference price and channel allocation for the VNOs. Simulations are provided to verify the proposed strategies. It is shown that the proposed strategies are effective in resource allocation and the ±‐optimal strategy achieves practically the same performance as the optimal strategy can achieve. It is also shown that the InP will not benefit from a large interference power limit, and selecting VNOs with higher unit rate utility gain to share the resources of the InP is beneficial to both the InP and the VNOs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1845-1865
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• 2019

Current Internet is designed by lots of service providers with different objects and policies which make the direct deployment of radically new architecture and protocols on Internet nearly impossible without reaching a consensus among almost all of them. Network virtualization is proposed to fend off this ossification of Internet architecture and add diversity to the future Internet. As an important part of network virtualization, virtual network embedding (VNE) problem has received more and more attention. In order to solve the problems of large embedding cost, low acceptance ratio (AR) and environmental adaptability in VNE algorithms, cognitive method is introduced to improve the adaptability to the changing environment and a cognitive virtual network embedding algorithm based on weighted relative entropy (WRE-CVNE) is proposed in this paper. At first, the weighted relative entropy (WRE) method is proposed to select the suitable substrate nodes and paths in VNE. In WRE method, the ranking indicators and their weighting coefficients are selected to calculate the node importance and path importance. It is the basic of the WRE-CVNE. In virtual node embedding stage, the WRE method and breadth first search (BFS) algorithm are both used, and the node proximity is introduced into substrate node ranking to achieve the joint topology awareness. Finally, in virtual link embedding stage, the CPU resource balance degree, bandwidth resource balance degree and path hop counts are taken into account. The path importance is calculated based on the WRE method and the suitable substrate path is selected to reduce the resource fragmentation. Simulation results show that the proposed algorithm can significantly improve AR and the long-term average revenue to cost ratio (LTAR/CR) by adjusting the weighting coefficients in VNE stage according to the network environment. We also analyze the impact of weighting coefficient on the performance of the WRE-CVNE. In addition, the adaptability of the WRE-CVNE is researched in three different scenarios and the effectiveness and efficiency of the WRE-CVNE are demonstrated.

• 전자공학회지
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• 제36권6호
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• pp.64-73
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• 2009

• Journal of Communications and Networks
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• 제18권5호
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• pp.744-761
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• 2016

For about the past decade and a half research efforts into cognitive radio networks (CRNs) have increased dramatically. This is because CRN is recognized as a technology that has the potential to squeeze the most out of the existing spectrum and hence virtually increase the effective capacity of a wireless communication system. The resulting increased capacity is still a limited resource and its optimal allocation is a critical requirement in order to realize its full benefits. Allocating these additional resources to the secondary users (SUs) in a CRN is an extremely challenging task and integer programming based optimization tools have to be employed to achieve the goals which include, among several aspects, increasing SUs throughput without interfering with the activities of primary users. The theory of the optimization tools that can be used for resource allocations (RA) in CRN have been well established in the literature; convex programming is one of them, in fact the major one. However when it comes to application and implementation, it is noticed that the practical problems do not fit exactly into the format of well established tools and researchers have to apply approximations of different forms to assist in the process. In this survey paper, the optimization tools that have been applied to RA in CRNs are reviewed. In some instances the limitations of techniques used are pointed out and creative tools developed by researchers to solve the problems are identified. Some ideas of tools to be considered by researchers are suggested, and direction for future research in this area in order to improve on the existing tools are presented.

• 대한전자공학회논문지TC
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• 제49권7호
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• pp.23-31
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• 2012

스케쥴링 및 데이터율의 결합 제어와 같은 자원할당 기술은 전파인지 네트워크에서는 매우 중요한 문제이다. 그러나 전파인지 네트워크에서는 주사용자 채널의 스토케스틱 특성으로 인하여 데이터율 및 스케쥴링을 결합하여 제어하는 것은 매우 어렵다. 본 논문에서는 전파인지 네트워크에서 신뢰성 제한 조건들을 고려한 비대칭 데이터율 및 스케쥴링 결합 제어 기법을 제안한다. 데이터율 및 스케쥴링 문제를 컨벡스 최적화 기법으로 공식화하고 쌍대성 분해 기법을 사용하여 부분 문제로 변환하여 분산화 하였다. 본 논문에서는 전체 시스템의 효용함수를 최대화 하도록 분산 노드들의 데이터율을 분산적으로 제어하는 알고리즘을 제안 하였다. 반면, 스케줄링은 기지국이 최적화하는 비대칭 기법을 제안하였다. 본 논문에서 제안한 비대칭 결합 제어 알고리즘은 전체 최적화 해로 수렴하는 것을 수치해석 기법으로 검증하였다.

• 한국인터넷방송통신학회논문지
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• 제10권1호
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• pp.145-150
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• 2010

본 논문은 무선인지시스템이 갖는 얼랑 용량을 분석하였다. 무선 인지 사용자들의 신규 호 및 스펙트럼 핸드오프를 요청하는 호들에 대해 버퍼를 사용하는 무선 자원 관리 기법을 고려하였으며, 성능 분석을 위해 마르코프(Markov) 모델을 사용하였다. 이를 기반으로 무선 인지 시스템에서 기사용자 및 무선 인지 사용자가 겪는 호 차단(call blocking) 확률, 강제 호 종료(forced call termination) 확률, 호 서비스 비완료(non-completion) 확률 등을 유도하였다. 시뮬레이션을 통해 버퍼의 크기가 증가함에 따라, 인지 무선 시스템에서 수용될 수 있는 얼랑 용량 또한 증가함을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권5호
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• pp.691-708
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• 2010

An important issue of supporting multi-users with diverse quality-of-service (QoS) requirements over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resource while, at the same time, to meet each communication service QoS requirement. In this work, we study the problem of a variety of communication services over multi-media heterogeneous cognitive OFDM system. We first divide the communication services into two parts. Multimedia applications such as broadband voice transmission and real-time video streaming are very delay-sensitive (DS) and need guaranteed throughput. On the other side, services like file transmission and email service are relatively delay tolerant (DT) so varying-rate transmission is acceptable. Then, we formulate the scheduling as a convex optimization problem, and propose low complexity distributed solutions by jointly considering channel assignment, bit allocation, and power allocation. Unlike prior works that do not care computational complexity. Furthermore, we propose the FAASA (Fairness Assured Adaptive Sub-carrier Allocation) algorithm for both DS and DT users, which is a dynamic sub-carrier allocation algorithm in order to maximize throughput while taking into account fairness. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes.