Survey of Spectrum Sharing for Inter-Technology Coexistence

Increasing capacity demands in emerging wireless technologies are expected to be met by network densification and spectrum bands open to multiple technologies. These will, in turn, increase the level of interference and also result in more complex inter-technology interactions, which will need to be managed through spectrum sharing mechanisms. Consequently, novel spectrum sharing mechanisms should be designed to allow spectrum access for multiple technologies, while efficiently utilizing the spectrum resources overall. Importantly, it is not trivial to design such efficient mechanisms, not only due to technical aspects, but also due to regulatory and business model constraints. In this survey we address spectrum sharing mechanisms for wireless inter-technology coexistence by means of a technology circle that incorporates in a unified, system-level view the technical and non-technical aspects. We thus systematically explore the spectrum sharing design space consisting of parameters at different layers. Using this framework, we present a literature review on inter-technology coexistence with a focus on wireless technologies with equal spectrum access rights, i.e. (i) primary/primary, (ii) secondary/secondary, and (iii) technologies operating in a spectrum commons. Moreover, we reflect on our literature review to identify possible spectrum sharing design solutions and performance evaluation approaches useful for future coexistence cases. Finally, we discuss spectrum sharing design challenges and suggest future research directions

비면허대역 셀룰라 통신의 성능 분석 및 성능 향상 기법 연구

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2021. 2. 박세웅.3GPP는 LAA (licensed-assisted access)라고하는 5GHz 비면허 대역 LTE를 개발했습니다. LAA는 충돌 방지 기능을 사용하기 위해 Wi-Fi의 CSMA / CA (Carrier Sense Multiple Access with Collision avoidance)와 유사한 LBT (Listen Before Talk) 작업을 채택하여 각 LAA 다운 링크 버스트의 프레임 구조 오버 헤드는 각각의 종료 시간에 따라 달라집니다. 이전 LBT 작업. 이 논문에서는 비면허 대역 셀룰러 통신을 분석하기위한 수치 모델을 제안한다. 다음으로, 비면허 대역 셀룰러 통신의 다음 두 가지 향상된 기능을 고려합니다. 대역 독립형 셀룰러 통신. 기존 WiFi 분석 모델로는 LAA의 성능을 평가할 수 없다는 점을 감안하여 본 서신에서는 여러 경합 진화 된 NodeB로 구성된 LAA 네트워크의 성능을 분석하기위한 새로운 Markov 체인 기반 분석 모델을 제안합니다. LAA 프레임 구조 오버 헤드의 변형. LTE-LAA는 LTE에서 상속 된 속도 적응 알고리즘을 위해 적응 변조 및 코딩 (AMC) 을 채택합니다. AMC는 진화 된 nodeB (eNB)가 현재 전송의 채널 품질 표시기 피드 백을 사용하여 다음 전송을위한 변조 및 코딩 방식 (MCS)을 선택하도록 돕습니다. 라이선스 대역에서 동작하는 기존 LTE의 경우 노드 경합 문제가 없으며 AMC 성능 에 대한 연구가 잘 진행되고 있습니다. 그러나 비면허 대역에서 동작하는 LTE-LAA 의 경우 충돌 문제로 인해 AMC 성능이 제대로 처리되지 않았습니다. 이 편지에서는 AMC 운영을 고려한 현실적인 채널 모델에서 LTELAA 성능을 분석하기위한 새로 운 Markov 체인 기반 분석 모델을 제안합니다. 무선 네트워크 분석에 널리 사용되는 Rayleigh 페이딩 채널 모델을 채택하고 분석 결과를 ns-3 시뮬레이터에서 얻은 결과 와 비교합니다. 비교 결과는 평균 정확도가 99.5%로 분석 모델의 정확도를 보여줍니다. 높은 데이터 속도에 대한 요구 사항으로 인해 3GPP는 LTE-LAA를위한 다중 반송파 운영을 제공했습니다. 그러나 다중 반송파 동작은 OOBE에 취약하고 제한된 전송 전력을 사용하여 비효율적 인 채널 사용을 초래합니다. 본 논문은 채널 효율을 높이기위한 새로운 다중 반송파 접근 방식을 제안한다. 우리가 제안한 방식은 전송 버스트를 여러 개로 분할하고 전송 전력 제한을 충족하면서 짧은 서브 프레임 전송 을 사용합니다. 또한 채널 상태를 정확하게 판단하여 OOBE 문제를 극복 할 수있는 에너지 감지 알고리즘을 제안합니다. 소프트웨어 정의 라디오를 사용하는 프로토 타입은 99% 이상의 정확도로 채널 상태를 결정하는 에너지 감지 알고리즘의 실행 가능성과 성능을 보여줍니다. ns-3 시뮬레이션을 통해 제안 된 다중 반송파 액세스 방식이 기존 LBT 유형 A 및 유형 B에 비해 사용자인지 처리량에서 각각 최대 59% 및 21.5%의 성능 향상을 달성 함을 확인했습니다. 레거시 LAA에는 배포 문제가 있기 때문에 3GPP와 MulteFire 얼라이언스는 비면허 대역 독립형 셀룰러 통신 시스 템을 제안했습니다. 그러나, 종래의 비면허 대역 독립형 셀룰러 통신 시스템은 상향 링크 제어 메시지의 전송 확률이 낮다. 이 논문은 Wi-Fi 블록 ACK 프레임에 업 링크 제어 메시지를 넣는 W ARQ : Wi-Fi 지원 HARQ를 제안합니다. 또한 W-ARQ의 처 리 성능을 향상시키기 위해 병렬 HARQ 및 클러스터링 된 Minstrel을 제안합니다. 우리가 제안한 알고리즘은 기존 MulteFire가 거의 제로 처리량 성능을 보이는 경우 높은 처리량 성능을 보여줍니다. 요약하면 비면허 대역 셀룰러 통신의 성능을 분석 합니다. 제안 된 모델을 사용함으로써 우리는 레거시 다중 반송파 동작을 주장하며 비면허 셀룰러 통신의 HARQ는 효율적이지 않다. 이러한 이유로, 우리는 최첨단 기 술에 비해 UPT 및 처리량과 같은 네트워크 성능 향상을 달성하는 OOBE 인식 추가 액세스 및 W-ARQ를 제안합니다.3GPP has developed 5 GHz unlicensed band LTE, referred to as licensed-assisted access (LAA). LAA adopts listen before talk (LBT) operation, resembling Wi-Fis carrier sense multiple access with collision avoidance (CSMA/CA), to enable collision avoidance capability, while the frame structure overhead of each LAA downlink burst varies with the ending time of each preceding LBT operation. In this dissertation, we propose numerical model to analyze unlicensed band cellular communication. Next, we consider the following two enhancements of unlicensed band cellular communication: (i) out-of-band emission (OOBE) aware additional carrier access, and (ii) Wi-Fi assisted hybrid automatic repeat request (H-ARQ) for unlicensed-band stand-alone cellular communication. Given that, existing analytic models of Wi-Fi cannot be used to evaluate the performance of LAA, in this letter, we propose a novel Markov chain-based analytic model to analyze the performance of LAA network composed of multiple contending evolved NodeBs by considering the variation of the LAA frame structure overhead. LTE-LAA adopts adaptive modulation and coding (AMC) for the rate adaptation algorithm inherited from LTE. AMC helps the evolved nodeB (eNB) to select a modulation and coding scheme (MCS) for the next transmission using the channel quality indicator feedback of the current transmission. For the conventional LTE operating in the licensed band, there is no node contention problem and AMC performance has been well studied. However, in the case of LTE-LAA operating in the unlicensed band, AMC performance has not been properly addressed due to the collision problem. In this letter, we propose a novel Markov chain-based analysis model for analyzing LTELAA performance under a realistic channel model considering AMC operation. We adopt Rayleigh fading channel model widely used in wireless network analysis, and compare our analysis results with the results obtained from ns-3 simulator. Comparison results show an average accuracy of 99.5%, which demonstrates the accuracy of our analysis model. Due to the requirement for a high data rate, the 3GPP has provided multi-carrier operation for LTE-LAA. However, multi-carrier operation is susceptible to OOBE and uses limited transmission power, resulting in inefficient channel usage. This paper proposes a novel multi-carrier access scheme to enhance channel efficiency. Our proposed scheme divides a transmission burst into multiple ones and uses short subframe transmission while meeting the transmission power limitation. In addition, we propose an energy detection algorithm to overcome the OOBE problem by deciding the channel status accurately. Our prototype using software-defined radio shows the feasibility and performance of the energy detection algorithm that determines the channel status with over 99% accuracy. Through ns-3 simulation, we confirm that the proposed multi-carrier access scheme achieves up to 59% and 21.5% performance gain in userperceived throughput compared with the conventional LBT type A and type B, respectively. Since the legacy LAA has deployment problem, 3GPP and MulteFire alliance proposed unlicensed band stand-alone cellular communication system. However, conventional unlicensed band stand-alone cellular communication system has low transmission probability of uplink control messages. This disertation proposes W-ARQ: Wi-Fi assisted HARQ which put uplink control messages into Wi-Fi block ACK frame. In addition we propose parallel HARQ and clustered Minstrel to enhance throughput performance of W-ARQ. Our proposed algorithm shows high throughput performance where conventional MulteFire shows almost zero throughput performance. In summary, we analyze the performance of unlicensed-band cellular communication. By using the proposed model, we insist the legacy multi-carrier operation and HARQ of unlicensed cellular communication is not efficient. By this reason, we propose OOBE aware additional access and W-ARQ which achievee enhancements of network performance such as UPT and throughput compared with state-of-the-art techniques.Abstract i Contents iv List of Tables vii List of Figures viii 1 Introduction 1 1.1 Unlicensed Band Communication System . . . . . . . . . . . . . . . 1 1.2 Overview of Existing Approaches . . . . . . . . . . . . . . . . . . . 2 1.2.1 License-assisted access . . . . . . . . . . . . . . . . . . . . . 2 1.2.2 Further LAA . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.3 Non-3GPP Unlicensed Band Cellular Communication . . . . 6 1.3 Main Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3.1 Performance Analysis of LTE-LAA . . . . . . . . . . . . . . 6 1.3.2 Out-of-Band Emission Aware Additional Carrier Access for LTE-LAA Network . . . . . . . . . . . . . . . . . . . . . . . 7 1.3.3 W-ARQ: Wi-Fi Assisted HARQ for Unlicensed Band StandAlone Cellular Communication System . . . . . . . . . . . . 8 1.4 Organization of the Dissertation . . . . . . . . . . . . . . . . . . . . 8 2 Performance Analysis of LTE-LAA network 10 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.3 Proposed Markov-Chain Model . . . . . . . . . . . . . . . . . . . . . 14 2.3.1 Markov Property . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3.2 Markov Chain Model for EPS Type Variation . . . . . . . . . 16 2.3.3 LAA Network Throughput Estimation . . . . . . . . . . . . . 18 2.4 Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3 Out-of-Band Emission Aware Additional Carrier Access for LTE-LAA Network 35 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2 Related work and Background . . . . . . . . . . . . . . . . . . . . . 37 3.2.1 Related work . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.2.2 Listen Before Talk . . . . . . . . . . . . . . . . . . . . . . . 38 3.2.3 Out-of-Band Emission . . . . . . . . . . . . . . . . . . . . . 39 3.3 Multi-carrier Operation of LTE-LAA . . . . . . . . . . . . . . . . . . 39 3.4 Carrier Sensing considering Out-of-Band Emission . . . . . . . . . . 47 3.4.1 Energy Detection Algorithm . . . . . . . . . . . . . . . . . . 49 3.4.2 Nominal Band Energy Detection . . . . . . . . . . . . . . . . 50 3.4.3 OOBE-Free Region Energy Detection . . . . . . . . . . . . . 51 3.5 Additional Carrier Access Scheme . . . . . . . . . . . . . . . . . . . 52 3.5.1 Basic Operation . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.5.2 Transmission Power Limitation . . . . . . . . . . . . . . . . 53 3.5.3 Dividing Transmission Burst . . . . . . . . . . . . . . . . . . 54 3.5.4 Short Subframe Decision . . . . . . . . . . . . . . . . . . . . 54 3.6 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.6.1 Performance of Energy Detection considering OOBE . . . . . 57 3.6.2 Simulation Environments . . . . . . . . . . . . . . . . . . . . 57 3.6.3 Performance of Proposed Carrier Access Scheme . . . . . . . 58 3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4 W-ARQ: Wi-Fi Assisted HARQ for Unlicensed Band Stand-Alone Cellular Communication System 66 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 4.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.3 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.4 W-ARQ: Wi-Fi assisted HARQ for Unlicensed Band Stand-Alone Cellular Communication System . . . . . . . . . . . . . . . . . . . . . . 69 4.4.1 Parallel HARQ . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.4.2 Clustered Minstrel . . . . . . . . . . . . . . . . . . . . . . . 72 4.5 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 75 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5 Concluding Remarks 80 5.1 Research Contributions . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Abstract (In Korean) 90 감사의 글 93Docto

Cooperation techniques between LTE in unlicensed spectrum and Wi-Fi towards fair spectral efficiency

On the road towards 5G, a proliferation of Heterogeneous Networks (HetNets) is expected. Sensor networks are of great importance in this new wireless era, as they allow interaction with the environment. Additionally, the establishment of the Internet of Things (IoT) has incredibly increased the number of interconnected devices and consequently the already massive wirelessly transmitted traffic. The exponential growth of wireless traffic is pushing the wireless community to investigate solutions that maximally exploit the available spectrum. Recently, 3rd Generation Partnership Project (3GPP) announced standards that permit the operation of Long Term Evolution (LTE) in the unlicensed spectrum in addition to the exclusive use of the licensed spectrum owned by a mobile operator. Alternatively, leading wireless technology developers examine standalone LTE operation in the unlicensed spectrum without any involvement of a mobile operator. In this article, we present a classification of different techniques that can be applied on co-located LTE and Wi-Fi networks. Up to today, Wi-Fi is the most widely-used wireless technology in the unlicensed spectrum. A review of the current state of the art further reveals the lack of cooperation schemes among co-located networks that can lead to more optimal usage of the available spectrum. This article fills this gap in the literature by conceptually describing different classes of cooperation between LTE and Wi-Fi. For each class, we provide a detailed presentation of possible cooperation techniques that can provide spectral efficiency in a fair manner

LTE-LAA 성능 향상을 위한 MAC 계층 기법

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2019. 2. 최성현.3GPP long term evolution (LTE) operation in unlicensed spectrum is emerging as a promising technology in achieving higher data rate with LTE since ultra-wide unlicensed spectrum, e.g., about 500 MHz at 5–6 GHz range, is available in most countries. Recently, 3GPP has finalized standardization of licensed-assisted access (LAA) for LTE operation in 5 GHz unlicensed spectrum, which has been a playground only for Wi-Fi. In this dissertation, we propose the following three strategies to enhance the performance of LAA: (1) Receiver-aware COT adaptation, (2) Collision-aware link adaptation, and (3) Power and energy detection threshold adaptation. First, LAA has a fixed maximum channel occupancy time (MCOT), which is the maximum continuous transmission time after channel sensing, while Wi-Fi may transmit for much shorter time duration. As a result, when Wi-Fi coexists with LAA, Wi-Fi airtime and throughput can be much less than those achieved when Wi-Fi coexists with another Wi-Fi. To guarantee fair airtime and improve throughput of Wi-Fi, we propose a receiver-aware channel occupancy time (COT) adaptation ( RACOTA ) algorithm, which observes Wi-Fi aggregate MAC protocol data unit (A-MPDU) frames and matches LAAs COT to the duration of A-MPDU frames when any Wi-Fi receiver has more data to receive. Moreover, RACOTA detects saturation of Wi-Fi traffic and adjusts COT only if Wi-Fi traffic is saturated. We prototype saturation detection algorithm of RACOTA with commercial off-the-shelf Wi-Fi device and show that RACOTA detects saturation of Wi-Fi networks accurately. Through ns-3 simulations, we demonstrate that RACOTA provides airtime fairness between LAA and Wi-Fi while achieves up to 334% Wi-Fi throughput gain. Second, the link adaptation scheme of the conventional LTE, adaptive modulation and coding (AMC), cannot operate well in the unlicensed band due to intermittent collisions. Intermittent collisions make LAA eNB lower modulation and coding scheme (MCS) for the subsequent transmission and such unnecessarily lowered MCS significantly degrades spectral efficiency. To address this problem, we propose a collision-aware link adaptation algorithm ( COALA ). COALA exploits k-means unsupervised clustering algorithm to discriminate channel quality indicator (CQI) reports which are measured with collision interference and selects the most suitable MCS for the next transmission. By prototype-based experiments, we demonstrate that COALA detects collisions accurately, and by conducting ns-3 simulations in various scenarios, we also show that COALA achieves up to 74.9% higher user perceived throughput than AMC. Finally, we propose PETAL to mitigate the negative impact of spatial reuse (SR) operation. We first design the baseline algorithm, which operates SR aggressively, and show that the baseline algorithm degrades the throughput performance severely when the UE is close to an interferer. Our proposed algorithm PETAL estimates and compares the spectral efficiency for the SR operation and non-SR operation. Then, PETAL operates SR only if the spectral efficiency of SR operation is expected to be higher than the case of non-SR operation. Our simulation verifies the performance of PETAL in various scenarios. When two pair of an eNB and a UE coexists, PETAL improves the throughput by up to 329% over the baseline algorithm. In summary, we identify interesting problems that appeared with LAA and shows the impact of the problems through the extensive simulations and propose compelling algorithms to solve the problems. The airtime fairness between Wi-Fi and LAA is improved with COT adaptation. Furthermore, link adaptation accuracy and SR operation are improved by exploiting CQI reports history. The performance of the proposed schemes is verified by system level simulation.비면허 대역에서의 LTE 동작은 더 높은 데이터 전송률을 달성하는 유망한 기술로 부각되고 있다. 최근 3GPP는 기존 Wi-Fi 기술이 사용하던 5 GHz 비면허 대역에서 LTE를 사용하는 licensed-assisted access (LAA) 기술의 표준화를 완료하였다. 본 논문에서 우리는 LAA의 성능을 향상시키기 위해 다음과 같은 세 가지 전략을 제안한다: (1) 수신기 인식 채널 점유 시간 적응, (2) 충돌 인식 링크 적응, (3) 전력 및 에너지 검출 역치 적응. 첫째, LAA는 고정된 최대 채널 점유 시간을 가지고 있고 그 시간 만큼 연속적으로 전송할 수 있는 반면, Wi-Fi는 비교적 짧은 시간 동안만 연속적으로 전송할 수 있다. 그 결과 Wi-Fi가 LAA와 공존할 때 Wi-Fi의 airtime과 수율 성능은 Wi-Fi가 또 다른 Wi-Fi와 공존할 때에 비하여 저하되게된다. 따라서 우리는 Wi-Fi의 airtime과 수율 성능을 향상시키기 위하여 Wi-Fi의 A-MPDU 프레임 전송 시간에 맞추어 LAA의 채널 점유 시간을 조절하는 수신기 인식 채널 점유 시간 적응 기법인 RACOTA를 제안한다. RACOTA 는 포화 감지 결과 Wi-Fi 수신기가 더 받을 데이터가 있다고 판단될 때에만 채널 점유 시간을 조절한다. 우리는 RACOTA 의 포화 감지 알고리즘을 상용 Wi-Fi 장비에 구현하여 이를 바탕으로 실측을 통해 RACOTA 가 공존하는 Wi-Fi의 포화 여부를 정확하게 감지해냄을 보인다. 또한 우리는 ns-3 시뮬레이션을 통하여 RACOTA 를 사용하는 LAA가 공존하는 Wi-Fi에게 공정한 airtime을 제공하고 기존 LAA와 공존하는 Wi-Fi 대비 최대 334%의 Wi-Fi 수율 성능 향상을 가져옴을 보인다. 둘째, 간헐적인 충돌이 발생할 수 있는 비면허 대역에서는 기존 LTE의 링크 적응 기법인 adaptive modulation and coding (AMC)이 잘 동작하지 않을 수 있다. 간헐적인 충돌은 LAA 기지국으로 하여금 modulation and coding scheme (MCS)을 낮추어서 다음 전송을 하도록 하는데 다음 전송 시에 충돌이 발생하지 않는다면 불필요하게 낮춘 MCS로 인해 주파수 효율이 크게 저하된다. 이러한 문제를 해결하기위해 우리는 충돌 인식 링크 적응 기법인 COALA 를 제안한다. COALA 는 k-means 무감독 클러스터링 알고리즘을 사용하여 channel quality indicator (CQI) 리포트 중 충돌 간섭에 영향을 받은 CQI 리포트들을 구별해내고 이를 통해 다음 전송을 위한 최적의 MCS를 선택한다. 우리는 실측을 통하여 COALA 가 정확하게 충돌을 감지해냄을 보인다. 또한 우리는 다양한 환경에서의 ns-3 시뮬레이션을 통하여 COALA 가 AMC 대비 최대 74.9%의 사용자 인식 수율 성능 향상을 가져옴을 보인다. 셋째, 우리는 공간 재사용 동작의 부작용을 최소화하기 위하여 수신 단말을 고려하여 전송 파워 및 에너지 검출 역치를 적응적으로 조절하는 PETAL 알고리즘을 제안한다. 우리는 먼저 수신 단말을 고려하지 않고 공격적으로 공간 재사용 동작을 하는 baseline 알고리즘을 설계하고 다양한 환경에서의 시뮬레이션을 통하여 수신 단말이 간섭원에 가까운 경우 baseline 알고리즘의 성능이 심각하게 열화됨을 보인다. 제안하는 알고리즘인 PETAL 은 수신 단말로부터 받은 CQI 리포트 정보와 채널 점유 시점까지의 평균 대기 시간을 이용하여 공간 재사용 동작을 할 때 예상되는 주파수 효율과 공간 재사용 동작을 하지 않을 때 예상되는 주파수 효율을 비교하여 공간 재사용 동작을 할 때 예상되는 주파수 효율이 더 클 때에만 공간 재사용 동작을 한다. 우리는 다양한 환경에서의 ns-3 시뮬레이션을 통하여 PETAL 이 baseline 알고리즘 대비 최대 329%의 수율 성능 향상을 가져옴을 보인다. 요약하자면, 우리는 LAA의 등장과 함께 새롭게 대두되는 흥미로운 문제들을 확인하고 문제들의 심각성을 다양한 환경에서의 시뮬레이션을 통하여 살펴보고 이 러한 문제들을 해결할 수 있는 알고리즘들을 제안한다. Wi-Fi와 LAA 사이의 airtime 공정성은 LAA의 연속 전송 시간을 적응적으로 조절하여 개선할 수 있다. 또한 링크 적응 정확도와 공간 재사용 동작의 효율성은 CQI 리포트들의 분포를 이용하여 개선할 수 있다. 제안하는 알고리즘들의 성능은 시스템 레벨 시뮬레이션을 통하여 검증되었다.1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Overview of Existing Approaches . . . . . . . . . . . . . . . . . . . 2 1.3 Main Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3.1 RACOTA: Receiver-Aware Channel Occupancy Time Adaptation for LTE-LAA . . . . . . . 2 1.3.2 COALA: Collision-Aware Link Adaptation for LTE-LAA . . 3 1.3.3 PETAL: Power and Energy Detection Threshold Adaptation for LAA . . . . . . . . . . . . . . 4 1.4 Organization of the Dissertation . . . . . . . . . . . . . . . . . . . . 5 2 RACOTA:Receiver-AwareChannelOccupancyTimeAdaptationforLTE- LAA 6 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 MAC Mechanisms of Wi-Fi and LAA . . . . . . . . . . . . . . . . . 10 2.3.1 Wi-Fi MAC Operation . . . . . . . . . . . . . . . . . . . . . 10 2.3.2 LAA Listen-Before-Talk (LBT) Mechanism . . . . . . . . . . 11 2.3.3 Wide Bandwidth Operation . . . . . . . . . . . . . . . . . . 13 2.4 Coexistence performance of LAA and Wi-Fi . . . . . . . . . . . . . . 14 2.4.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . 14 2.4.2 Unfairness between LAA and Wi-Fi . . . . . . . . . . . . . . 15 2.5 Receiver-Aware COT Adaptation Algorithm . . . . . . . . . . . . . . 17 2.5.1 Saturation Detection (SD) . . . . . . . . . . . . . . . . . . . 20 2.5.2 Receiver-Aware COT Decision . . . . . . . . . . . . . . . . . 22 2.6 Performance Evaluation of SD Algorithm . . . . . . . . . . . . . . . 22 2.6.1 Measurement Setup . . . . . . . . . . . . . . . . . . . . . . . 22 2.6.2 PPDUMaxTime Detection . . . . . . . . . . . . . . . . . . . 24 2.6.3 Saturation Detection Performance . . . . . . . . . . . . . . . 26 2.7 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.7.1 Saturated Traffic Scenario . . . . . . . . . . . . . . . . . . . 28 2.7.2 Unsaturated Traffic Scenario . . . . . . . . . . . . . . . . . . 30 2.7.3 Bursty Traffic Scenario . . . . . . . . . . . . . . . . . . . . . 30 2.7.4 Heterogeneous Wi-Fi Traffic Generation Scenario . . . . . . 31 2.7.5 Multiple Node Scenario . . . . . . . . . . . . . . . . . . . . 34 2.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3 COALA: Collision-Aware Link Adaptation for LTE-LAA 36 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.2 Backgound and Related Work . . . . . . . . . . . . . . . . . . . . . 38 3.2.1 LAA and LBT . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.2.2 AMC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.2.3 Inter-Cell Interference Cancellation . . . . . . . . . . . . . . 39 3.2.4 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.3 Impact of Collision to Link Adaptation . . . . . . . . . . . . . . . . . 41 3.4 COALA: Collision-aware Link Adaptation . . . . . . . . . . . . . . . 47 3.4.1 CQI Clustering Algorithm . . . . . . . . . . . . . . . . . . . 48 3.4.2 Collision Detection and Collision Probability Estimation . . . 48 3.4.3 Suitable MCS Selection . . . . . . . . . . . . . . . . . . . . 49 3.5 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.5.1 Prototype-based Feasibility Study . . . . . . . . . . . . . . . 51 3.5.2 Contention Collision with LAA eNBs . . . . . . . . . . . . . 53 3.5.3 Hidden Collision . . . . . . . . . . . . . . . . . . . . . . . . 57 3.5.4 Bursty Hidden Collision . . . . . . . . . . . . . . . . . . . . 58 3.5.5 Contention Collision with Wi-Fi Transmitters . . . . . . . . . 58 3.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 4 PETAL: Power and Energy Detection Threshold Adaptation for LAA 62 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.2 Backgound and Related Work . . . . . . . . . . . . . . . . . . . . . 64 4.2.1 Energy Detection Threshold . . . . . . . . . . . . . . . . . . 64 4.2.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.3 Baseline Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 4.3.1 Design of the Baseline Algorithm . . . . . . . . . . . . . . . 65 4.3.2 Performance of the Baseline Algorithm . . . . . . . . . . . . 66 4.4 PETAL: Power and Energy Detection Threshold Adaptation . . . . . 68 4.4.1 CQI Management . . . . . . . . . . . . . . . . . . . . . . . . 69 4.4.2 Success Probability and Airtime Ratio Estimation . . . . . . . 69 4.4.3 CQI Clustering Algorithm . . . . . . . . . . . . . . . . . . . 71 4.4.4 SR Decision . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.5 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.5.1 Two Cell Scenario . . . . . . . . . . . . . . . . . . . . . . . 73 4.5.2 Coexistence with Standard LAA . . . . . . . . . . . . . . . . 75 4.5.3 Four Cell Scenario . . . . . . . . . . . . . . . . . . . . . . . 76 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5 Concluding Remarks 79 5.1 Research Contributions . . . . . . . . . . . . . . . . . . . . . . . . . 79 Abstract (In Korean) 88 감사의 글 92Docto

Measurement and Optimization of LTE Performance

4G Long Term Evolution (LTE) mobile system is the fourth generation communication system adopted worldwide to provide high-speed data connections and high-quality voice calls. Given the recent deployment by mobile service providers, unlike GSM and UMTS, LTE can be still considered to be in its early stages and therefore many topics still raise great interest among the international scientific research community: network performance assessment, network optimization, selective scheduling, interference management and coexistence with other communication systems in the unlicensed band, methods to evaluate human exposure to electromagnetic radiation are, as a matter of fact, still open issues. In this work techniques adopted to increase LTE radio performances are investigated. One of the most wide-spread solutions proposed by the standard is to implement MIMO techniques and within a few years, to overcome the scarcity of spectrum, LTE network operators will offload data traffic by accessing the unlicensed 5 GHz frequency. Our Research deals with an evaluation of 3GPP standard in a real test best scenario to evaluate network behavior and performance