Wireless Communications in the Era of Big Data

The rapidly growing wave of wireless data service is pushing against the boundary of our communication network's processing power. The pervasive and exponentially increasing data traffic present imminent challenges to all the aspects of the wireless system design, such as spectrum efficiency, computing capabilities and fronthaul/backhaul link capacity. In this article, we discuss the challenges and opportunities in the design of scalable wireless systems to embrace such a "bigdata" era. On one hand, we review the state-of-the-art networking architectures and signal processing techniques adaptable for managing the bigdata traffic in wireless networks. On the other hand, instead of viewing mobile bigdata as a unwanted burden, we introduce methods to capitalize from the vast data traffic, for building a bigdata-aware wireless network with better wireless service quality and new mobile applications. We highlight several promising future research directions for wireless communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications Magazin

Stochastic geometry approach towards interference management and control in cognitive radio network : a survey

Interference management and control in the cognitive radio network (CRN) is a necessity if the activities of primary users must be protected from excessive interference resulting from the activities of neighboring users. Hence, interference experienced in wireless communication networks has earlier been characterized using the traditional grid model. Such models, however, lead to non-tractable analyses, which often require unrealistic assumptions, leading to inaccurate results. These limitations of the traditional grid models mean that the adoption of stochastic geometry (SG) continues to receive a lot of attention owing to its ability to capture the distribution of users properly, while producing scalable and tractable analyses for various performance metrics of interest. Despite the importance of CRN to next-generation networks, no survey of the existing literature has been done when it comes to SG-based interference management and control in the domain of CRN. Such a survey is, however, necessary to provide the current state of the art as well as future directions. This paper hence presents a comprehensive survey related to the use of SG to effect interference management and control in CRN. We show that most of the existing approaches in CRN failed to capture the relationship between the spatial location of users and temporal traffic dynamics and are only restricted to interference modeling among non-mobile users with full buffers. This survey hence encourages further research in this area. Finally, this paper provides open problems and future directions to aid in finding more solutions to achieve efficient and effective usage of the scarce spectral resources for wireless communications.The SENTECH Chair in Broadband Wireless Multimedia Communications (BWMC), Department of Electrical, Electronic and Computer Engineering, University of Pretoria, South Africa.http://www.elsevier.com/locate/comcomhj2022Electrical, Electronic and Computer Engineerin

Access Network Selection in Heterogeneous Networks

The future Heterogeneous Wireless Network (HWN) is composed of multiple Radio Access Technologies (RATs), therefore new Radio Resource Management (RRM) schemes and mechanisms are necessary to benefit from the individual characteristics of each RAT and to exploit the gain resulting from jointly considering the whole set of the available radio resources in each RAT. These new RRM schemes have to support mobile users who can access more than one RAT alternatively or simultaneously using a multi-mode terminal. An important RRM consideration for overall HWN stability, resource utilization, user satisfaction, and Quality of Service (QoS) provisioning is the selection of the most optimal and promising Access Network (AN) for a new service request. The RRM mechanism that is responsible for selecting the most optimal and promising AN for a new service request in the HWN is called the initial Access Network Selection (ANS). This thesis explores the issue of ANS in the HWN. Several ANS solutions that attempt to increase the user satisfaction, the operator benefits, and the QoS are designed, implemented, and evaluated. The thesis first presents a comprehensive foundation for the initial ANS in the H\VN. Then, the thesis analyses and develops a generic framework for solving the ANS problem and any other similar optimized selection problem. The advantages and strengths of the developed framework are discussed. Combined Fuzzy Logic (FL), Multiple Criteria Decision Making (MCDM) and Genetic Algorithms (GA) are used to give the developed framework the required scalability, flexibility, and simplicity. The developed framework is used to present and design several novel ANS algorithms that consider the user, the operator, and the QoS view points. Different numbers of RATs, MCDM tools, and FL inference system types are used in each algorithm. A suitable simulation models over the HWN with a new set of performance evolution metrics for the ANS solution are designed and implemented. The simulation results show that the new algorithms have better and more robust performance over the random, the service type, and the terminal speed based selection algorithms that are used as reference algorithms. Our novel algorithms outperform the reference algorithms in- terms of the percentage of the satisfied users who are assigned to the network of their preferences and the percentage of the users who are assigned to networks with stronger signal strength. The new algorithms maximize the operator benefits by saving the high cost network resources and utilizing the usage of the low cost network resources. Usually better results are achieved by assigning the weights using the GA optional component in the implemented algorithms

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

초고밀도밀리미터웨이브셀룰러네트워크에서이중연결기반핸드오버기법

학위논문 (석사)-- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2019. 2. 박세웅최성현심병효.밀리미터 웨이브를 사용하는 초고밀도 셀룰러 네트워크에서 이동하는 단말은 기존의 네트워크보다 더 많은 핸드 오버를 경험할 것이며, 이는 서비스 중단 시간의 증가와 그로 인한 성능저하를 야기할 것이다. 이런 문제점을 해결하기 위한 솔루 션으로서 다중연결성은 밀리미터 웨이브의 통신 범위를 향상시키고 링크를 보다 견고하게 할 수 있다는 점에서 현재 많이 각광 받고 있는 기법 중 하나이다. 본 논 문에서는 한 개의 단말이 기존의 LTE 셀과의 연결을 유지하면서 두 개의 밀리미터 웨이브 셀과 동시에 연결하는 새로운 네트워크 구조를 제안하며, 이러한 연결성에 의존하는 단말의 이동성을 보장하며 핸드오버의 수를 감소시키기 위하여 이중연결 기반 핸드오버 기법을 제시하였다. 또한 논문에서는 제시한 이중연결기법 기반의 핸드오버 기법과 기존의 단일 연결 기반의 핸드오버 기법을 ns-3 시뮬레이션을 통 해 구현하고 비교하였다. 시뮬레이션 결과는 제안 된 기법이 핸드 오버 비율, 전송 실패율 및 전송 지연 시간을 크게 감소시킨다는 것을 보여주었다. 따라서 본 논문은 이중 연결 기반 핸드 오버 기법이 네트워크의 부담을 줄여주고 더 안정적인 전송을 보장하며 보다 나은 서비스 품질을 제공 할 것이라고 주장한다.Mobile UEs in ultra-dense millimeter-wave cellular networks will experience handover events more frequently than in conventional networks, which will cause increased service interruption time and performance degradation. To resolve this, leveraging multi-connectivity becomes a promising solution in that it can improve the coverage of millimeter-wave communications and support link robustness. In this paper, we propose a dual-connection based handover scheme for mobile UEs in an environment where they are connected simultaneously with two millimeter-wave cells to overcome frequent handover problems, keeping a legacy LTE connection. We compare our dual-connection based scheme with a conventional single-connection based one through ns-3 simulation. The simulation results show that the proposed scheme significantly reduces handover rate, transmission failure ratio and delay. Therefore, we argue that the dual-connection based handover scheme will decrease network controlling overheads, guarantee more reliable transmission and provide better quality-of-service.1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Contributions and Outline . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Background and System Model 5 2.1 LTE-MmWave Dual Connectivity and Small Cell Handover . . . . . . 5 2.2 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Channel and Propagation Model . . . . . . . . . . . . . . . . . . . . 8 3 Secondary Cell Handover Design for Multi-Connectivity 9 3.1 MmWave-MmWave Dual Connectivity . . . . . . . . . . . . . . . . . 9 3.2 Secondary Cell Handover Scheme . . . . . . . . . . . . . . . . . . . 11 4 Implementation and Performance Evaluation 15 4.1 ns-3 Simulator Implementation . . . . . . . . . . . . . . . . . . . . . 15 4.2 Simulation Setting and Scenario . . . . . . . . . . . . . . . . . . . . 16 4.3 Simulation Results and Discussion . . . . . . . . . . . . . . . . . . . 18 4.3.1 File download completion time . . . . . . . . . . . . . . . . 18 4.3.2 Radio resource usage in user-plane . . . . . . . . . . . . . . . 20 4.3.3 Handover rate and file download failure ratio . . . . . . . . . 20 4.3.4 TCP performance . . . . . . . . . . . . . . . . . . . . . . . . 23 5 Conclusion 25Maste

사용자 중심의 밀리미터파 통신 시스템을 위한 이동성 인식 분석 프레임워크 및 네트워크 관리 기법

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2021. 2. 박세웅.Millimeter wave (mmWave) communication enables high rate transmission, but its network performance may be degraded significantly due to blockages between the transmitter and receiver. There have been two approaches to overcome the blockage effect and enhance link reliability: multi-connectivity and ultra-dense network (UDN). Particularly, multi-connectivity under a UDN environment facilitates user-centric communication. It requires dynamic configuration of serving base station groups so that each user experiences high quality services. This dissertation studies a mathematical framework and network manament schemes for user-centric mmWave communication systems. First, we models user mobility and mobility-aware performance in user-centric mmWave communication systems with multi-connectivity, and proposes a new analytical framework based on the stochastic geometry. To this end, we derive compact mathematical expressions for state transitions and probabilities of various events that each user experiences. Then we investigate mobility-aware performance in terms of network overhead and downlink throughput. This helps us to understand network operation in depth, and impacts of network density and multi-connection capability on the probability of handover related events. Numerical results verify the accuracy of our analysis and illustrate the correlation between mobility-aware performance and user speed. Next, we propose user-oriented configuration rules and price based association algorithms for user-centric mmWave networks with fully/partially wired backhauls. We develop a fair association algorithm by solving the optimization problem that we formulate for mmWave UDNs. The algorithm includes an access price based per-user request decision method and a price adjustment rule for load balancing. Based on insights from the algorithm, we develop path-aware access pricing policy for mmWave integrated access and backhaul networks. Numerical evaluations show that our proposed methods are superior to other comparative schemes. Our findings from analysis and optimization provide useful insights into the design of user-centric mmWave communication systems.밀리미터파 통신은 고속 전송을 가능하게 하지만 송신기와 수신기 사이의 장애물로 인해 네트워크 성능이 크게 저하될 수 있다. 장애물 효과를 극복하고 링크 안정성을 향상시키는 다중 연결 및 네트워크 초고밀화 두가지 접근법이 있다. 특히 각 사용자가 고품질의 서비스를 경험할 수 있도록 서빙 기지국 그룹의 동적 구성이 필요하므로 초고밀도 네트워크 환경에서 다중 연결은 사용자 중심 통신을 용이하게 한다. 본 논문은 사용자 중심의 밀리미터파 통신 시스템을 위한 수학적 프레임워크와 네트워크 관리 체계를 연구한다. 먼저 다중 연결을 사용하여 사용자 중심의 밀리미터파 통신 시스템에서 사용자 이동성과 이동성 인식 성능 지표를 모델링하고 확률기하분석을 기반으로 하는 새로운 분석 프레임워크를 제안한다. 이를 위해 각 사용자가 경험하는 다양한 이벤트의 상태 전이 확률에 대한 수학적 표현을 도출한다. 그런 다음 네트워크 오버헤드 및 다운 링크 수율 측면에서 이동성 인식 성능을 연구한다. 이를 통해 네트워크 운영에 대한 깊이있는 이해와 네트워크 밀도 및 다중 연결 기능이 핸드 오버와 관련된 이벤트의 확률에 미치는 영향을 이해할 수 있다. 시뮬레이션 결과는 분석의 정확성을 검증하고 이동성 인식 성능과 사용자 속도 간의 상관 관계를 보여준다. 다음으로 완전 또는 부분 유선 백홀이 있는 사용자 중심 밀리미터파 네트워크를 위한 사용자 중심 구성 규칙 및 접속 가격 기반 연결 알고리즘을 제안한다. 밀리미터파 초고밀도 네트워크에 대한 최적화 문제를 해결하여 공정한 연결 알고리즘을 개발한다. 이 알고리즘에는 접속 가격 기반 사용자 별 요청 결정 방법과 로드 밸런싱을 위한 가격 조정 규칙이 포함된다. 위 알고리즘 개발을 통해 얻은 통찰력을 기반으로 밀리미터파 통합 액세스 및 백홀 네트워크를 위한 경로 인식 접속 요금 정책을 개발한다. 수치 평가에 따르면 제안된 방법이 다른 비교 기법보다 우수하다. 분석 및 최적화 결과는 사용자 중심의 밀리미터파 통신 시스템 설계에 대한 유용한 통찰력을 제공할 것 이다.Abstract i Contents iii List of Tables vi List of Figures vii 1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Outline and Contributions . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Mobility-Aware Analysis of MillimeterWave Communication Systems with Blockages 5 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.2 Connectivity Model . . . . . . . . . . . . . . . . . . . . . . 10 2.2.3 Mobility Model . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.3 Mobility-Aware Analysis . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3.1 Analytical Framework . . . . . . . . . . . . . . . . . . . . . 13 2.3.2 Urban Scenario with Ultra-Densely Deployed BSs . . . . . . 18 2.3.3 Handover Analysis for Macrodiversity . . . . . . . . . . . . . 22 2.3.4 Normalized Network Overhead and Mobility-Aware Downlink Throughput with Greedy User Association . . . . . . . . 24 2.4 Numerical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3 Association Control for User-Centric Millimeter Wave Communication Systems 34 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.2.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.2.2 Channel Model and Achievable Rate . . . . . . . . . . . . . . 39 3.2.3 User Centric mmWave Communication Framework . . . . . . 39 3.3 Traffic Load Management . . . . . . . . . . . . . . . . . . . . . . . . 44 3.3.1 Optimal Association and Admission Control . . . . . . . . . 45 3.3.2 Outage Analysis . . . . . . . . . . . . . . . . . . . . . . . . 51 3.4 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.4.1 Evaluation Environments . . . . . . . . . . . . . . . . . . . . 53 3.4.2 Performance Comparison . . . . . . . . . . . . . . . . . . . . 55 3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4 Path Selection and Path-Aware Access Pricing Policy in Millimeter Wave IAB Networks 60 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 4.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.2.1 Geographic and Pathloss Models . . . . . . . . . . . . . . . . 62 4.2.2 IAB Network Model . . . . . . . . . . . . . . . . . . . . . . 63 4.3 Path Selection Strategies . . . . . . . . . . . . . . . . . . . . . . . . 66 4.4 Path-Aware Access Pricing Policy . . . . . . . . . . . . . . . . . . . 69 4.5 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 72 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 5 Conclusion 80 5.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.2 Limitations and Future Work . . . . . . . . . . . . . . . . . . . . . . 82 Abstract (In Korean) 90Docto