김효일 교수
Hyoil Kim
UNIST 전기전자공학과 · 컴퓨터과학
연구실 소개
김효일 교수의 연구실은 인공지능 기반의 스마트 무선 통신 및 에너지 효율적 모바일 컴퓨팅을 핵심으로 하며, 인텔리전트 스펙트럼 공유, 컴퓨팅 오프로딩, Wi-Fi 2.0 기반의 고성능 무선 접근 기술을 연구하고 있습니다. 특히, 사용자 경험을 고려한 에너지-지연-비용 트레이드오��� 최적화 및 실시간 스펙트럼 기회 탐색 기반의 서비스 연속성 확보 기술에 초점을 맞추고 있습니다. 동적으로 변화하는 무선 환경에서의 효율적 자원 할당과 실시간 의사결정 기반의 네트워크 최적화가 핵심 연구 과제입니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15We address the problem of rapidly discovering spectrum opportunities for seamless service provisioning for secondary users (SUs) in cognitive radio networks (CRNs). Specifically, we propose an efficient sensing-sequence that incurs a small opportunity-discovery delay by considering (1) the probability that a spectrum band (or a channel) may be available at the time of sensing, (2) the duration of sensing on a channel, and (3) the channel capacity. We derive the optimal sensing-sequence for chann
Wi-Fi has become an essential wireless technology in our daily lives, although the original intention of its introduction was to replace Ethernet cable. In this article, we outline the most remarkable features introduced during its ongoing technological evolution in terms of three major directions: throughput enhancement, longrange extension, and greater ease of use. By stitching these advanced features together, we also envision a promising future that Wi-Fi technology will bring us in terms of
Computation offloading is a promising application of mobile clouds that can save energy of mobile devices via optimal transmission scheduling of mobile-to-cloud task offloading. Existing approaches to computation offloading have addressed various aspects of the tradeoff between energy consumption and application latency, but none of them explicitly considered the dependency in optimization on the mobile user''s context, e.g., user tendency, the remaining battery level. This paper captures such a
Computation offloading in mobile clouds helps mobile users save energy and enhance performance via mobile-to-cloud migration of processing. Although there exist many approaches to computation offloading, they have not explicitly considered the energy-latency-pricing tradeoff from the viewpoint of mobile users' context, e.g., user tendency, the remaining battery level. This paper tries to capture the user-centric perspective via quality-of-experience (QoE), and formulates two important problems:
The whitespaces (WS) in the legacy spectrum provide new opportunities for the future Wi-Fi-like Internet access, often called Wi-Fi 2.0, since service quality can be greatly enhanced thanks to the better propagation characteristics of the WS than the ISM bands. In the Wi-Fi 2.0 networks, each wireless service provider (WSP) temporarily leases a licensed spectrum band from the licensees and opportunistically utilizes it during the absence of the legacy users. The WSPs in Wi-Fi 2.0 thus face uniqu
We address the problem of rapidly discovering spectrum opportunities for seamless service provisioning in cognitive radio networks (CRNs). In particular, we focus on multichannel communications via channel-bonding with heterogeneous channel characteristics of ON/OFF patterns, sensing time, and channel capacity. Using dynamic programming (DP), we derive an optimal online sensing sequence incurring a minimal opportunity-discovery delay, and propose a suboptimal sequence that presents a near-optima
License Assisted Access (LAA) LTE (LAA-LTE) is a new type of LTE that aggregates the licensed LTE bands with the unlicensed bands via carrier aggregation. To operate in unlicensed bands, LAA-LTE adopts the listen-before-talk policy and designs its channel access mechanism similar to WLAN's DCF. This paper considers an LAA-LTE eNB coexisting with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">asymmetric hidden</i> Wi-Fi APs where the eNB can dete
We consider the problem of opportunistically scheduling low-priority tasks onto underutilized computation resources in the cloud left by high-priority tasks. To avoid conflicts with high-priority tasks, the scheduler must suspend the low-priority tasks (causing waiting), or move them to other underutilized servers (causing migration), if the high-priority tasks resume. The goal of opportunistic scheduling is to schedule the low-priority tasks onto intermittently available server resources while
Millimeter-wave (mmWave) networks are conventionally considered to bear a fundamental coverage limitation, due to the directional beams and limited field-of-view (FoV) of the phased array antennas. In this paper, we explore an array of phased arrays (APA) architecture, which aggregates co-located phased arrays with complementary FoVs to approximate WiFi-like omni-directional coverage. We found that straightforwardly activating all the arrays may even hamper network performance. To fully exploit
Spectrum sensing is essential to the realization of spectrum agility in cognitive radio (CR) networks. Although fundamental tradeoffs and theoretical limits associated with spectrum sensing have been studied extensively, there have been very few experimental studies focused on building a spectrum &quot;sensor&quot; with commercial off-the-shelf devices. We have therefore built a prototype of CR-based sensor implementation with off-the-shelf IEEE 802.11 devices. 1 In particular, we have e
The prosperity of IEEE 802.11-based Wi-Fi networks aggravates cross-technology interference to IEEE 802.15.4-enabled ZigBee networks widely deployed to enable various Internet-of-Things applications. To make ZigBee communication reliable and robust even in a dense Wi-Fi environment, taming Wi-Fi interference in ZigBee networks especially from the perspective of physical layer is of paramount importance. In this context, this work takes aim to design a novel Wi-Fi interference-resilient ZigBee de
Femtocell base station (BS) is a low-power, low-price BS based on the cellular communication technology. It is expected to become a cost-effective solution for improving the communication performance of indoor users, whose traffic demands are large in general. We propose long-term parameter optimization schemes for open and hybrid femtocells, which maximize the average throughput of macrocell users by offloading the macro users' downlink traffic to femtocells. To achieve this goal, load balancin
Smart vehicles require constantly running heavy vehicular computations with their limited computation/energy resources. 5G vehicular networks have potential to resolve the issue, by letting the vehicular tasks offloaded to 5G mobile edge computing (MEC) servers. To better support vehicular computation offloading, this paper proposes a road-side 5G infrastructure consisting of multiple millimeter-wave (mmWave) small-cell base stations (BSs) and a cellular mid-band based macro-cell BS where each B
Low latency networking is gaining attention to support futuristic network applications like the Tactile Internet with stringent end-to-end latency requirements. In realizing the vision, cut-through (CT) switching is believed to be a promising solution to significantly reduce the latency of today's store-and-forward switching, by splitting a packet into smaller chunks called flits and forwarding them concurrently through input and output ports of a switch. Nevertheless, the end-to-end latency per
Cognitive radio (CR)-based Wi-Fi 2.0 hotspots are introduced as an attractive application of dynamic spectrum access (DSA), at which a wireless service provider (WSP) leases licensed channels via secondary market and offers Internet access to CR-enabled customers by opportunistically utilizing the leased spectrum. The CR users access the channels only when they are temporarily unoccupied by their legacy users, and pay a usage charge according to the WSP's pricing policy. In this paper, we study
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