A Delay-Optimal Packet Scheduler for M2M Uplink

In this paper, we present a delay-optimal packet scheduler for processing the M2M uplink traffic at the M2M application server (AS). Due to the delay-heterogeneity in uplink traffic, we classify it broadly into delay-tolerant and delay-sensitive traffic. We then map the diverse delay requirements of each class to sigmoidal functions of packet delay and formulate a utility-maximization problem that results in a proportionally fair delay-optimal scheduler. We note that solving this optimization problem is equivalent to solving for the optimal fraction of time each class is served with (preemptive) priority such that it maximizes the system utility. Using Monte-Carlo simulations for the queuing process at AS, we verify the correctness of the analytical result for optimal scheduler and show that it outperforms other state-of-the-art packet schedulers such as weighted round robin, max-weight scheduler, fair scheduler and priority scheduling. We also note that at higher traffic arrival rate, the proposed scheduler results in a near-minimal delay variance for the delay-sensitive traffic which is highly desirable. This comes at the expense of somewhat higher delay variance for delay-tolerant traffic which is usually acceptable due to its delay-tolerant nature.Comment: Accepted for publication in IEEE MILCOM 2016 (6 pages, 7 figures

Predictive Pre-allocation for Low-latency Uplink Access in Industrial Wireless Networks

Driven by mission-critical applications in modern industrial systems, the 5th generation (5G) communication system is expected to provide ultra-reliable low-latency communications (URLLC) services to meet the quality of service (QoS) demands of industrial applications. However, these stringent requirements cannot be guaranteed by its conventional dynamic access scheme due to the complex signaling procedure. A promising solution to reduce the access delay is the pre-allocation scheme based on the semi-persistent scheduling (SPS) technique, which however may lead to low spectrum utilization if the allocated resource blocks (RBs) are not used. In this paper, we aim to address this issue by developing DPre, a predictive pre-allocation framework for uplink access scheduling of delay-sensitive applications in industrial process automation. The basic idea of DPre is to explore and exploit the correlation of data acquisition and access behavior between nodes through static and dynamic learning mechanisms in order to make judicious resource per-allocation decisions. We evaluate the effectiveness of DPre based on several monitoring applications in a steel rolling production process. Simulation results demonstrate that DPre achieves better performance in terms of the prediction accuracy, which can effectively increase the rewards of those reserved resources.Comment: Full version (accepted by INFOCOM 2018

5G 이후 무선 네트워크를 위한 무선 접속 기술 향상 연구

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2020. 8. 박세웅.Recently, operators are creating services using 5G systems in various fields, e.g., manufacturing, automotive, health care, etc. 5G use cases include transmission of small packets using IoT devices to high data rate transmission such as high-definition video streaming. When a large-scale IoT device transmits a small packet, power saving is important, so it is necessary to disconnect from the base station and then establish a connection through random access to transmit data. However, existing random access procedures are difficult to satisfy various latency requirements. It is attractive to use a wide bandwidth of the millimeter wave spectrum for high data rate transmission. In order to overcome the channel characteristics, beamforming technology is applied. However, when determining a beam pair between a transmitter and a receiver, interference is not considered. In this dissertation, we consider the following three enhancements to enable 5G and beyond use cases: (i) Two-step random access procedure for delay-sensitive devices, (ii) self-uplink synchronization framework for solving preamble collision problem, and (iii) interference-aware beam adjustment for interference coordination. First, RAPID, two-step random access for delay-sensitive devices, is proposed to reduce latency requirement value for satisfying specific reliability. When devices, performing RAPID and contention-based random access, coexist, it is important to determine a value that is the number of preambles for RAPID to reduce random access load. Simulation results show that RAPID achieves 99.999% reliability with 80.8% shorter uplink latency, and also decreases random access load by 30.5% compared with state-of-the-art techniques. Second, in order to solve preamble collision problem, we develop self-uplink synchronization framework called EsTA. Preamble collision occurs when multiple devices transmit the same preamble. Specifically, we propose a framework that helps the UE to estimate the timing advance command using a deep neural network model and to determine the TA value. Estimation accuracy can achieve 98–99% when subcarrier spacing is 30 and 60 kHz. Finally, we propose IBA, which is interference-aware beam adjustment method to reduce interference in millimeter wave networks. Unlike existing methods of reducing interference by scheduling time and frequency resources differently, interference is controlled through beam adjustment. In IBA, it is important to reduce search space of finding new beam pair to reduce interference. In practical, it is impossible to search beam pair of all combinations. Therefore, through Monte Carlo method, we can reduce search space to achieve local optimum. IBA achieve enhancement of lower 50%throughput up to 50% compared with only applying beam adjustment. In summary, we propose a two-step random access, a self-uplink synchronization framework, and interference-aware beam adjustment for 5G and beyond use cases. Through these researches, we achieve enhancements of network performance such as latency and throughput compared with state-of-the-art techniques.최근 사업자는 제조, 자동차, 헬스 케어 등 다양한 분야에서 5G 시스템을 사용하여 서비스를 만들고 있다. 5G 사용 사례에는 IoT 장치를 이용한 작은 패킷 전송에서고화질 비디오 스트리밍과 같은 고속 데이터 전송까지 포함된다. 대규모 IoT 장치가작은 패킷을 전송하는 경우 전력 소모 절약이 중요하므로 기지국과의 연결을 끊은다음 랜덤 액세스를 통해 다시 기지국과 연결하여 데이터를 전송해야한다. 그러나기존의 랜덤 액세스 절차는 다양한 지연시간 요건을 만족시키기 어렵다. 한편, 높은데이터 전송 속도를 위해 넓은 대역폭의 밀리미터파 대역을 사용한다. 이때, 밀리미터파 대역 채널 특성을 극복하기 위해 빔포밍 기술이 적용된다. 그러나 현재 5G표준에서 송신기와 수신기 사이의 빔 쌍을 결정할 때, 간섭은 고려되지 않는다. 이논문에서는 5G 및 그 이후의 네트워크에서 다양한 사용 사례를 지원하기 위해 다음세 가지 개선 사항을 고려한다. (i) 지연에 민감한 장치를 위한 2 단계 랜덤 액세스절차, (ii) 프리앰블 충돌 문제를 해결하기 위한 자체 상향링크 동기화 프레임 워크,그리고 (iii) 간섭을 줄이기 위한 간섭 인식 빔 조정이다. 첫째, 지연에 민감한 장치를 위한 2 단계 랜덤 액세스인 RAPID는 특정 신뢰도를 만족시키기 위한 지연시간을 줄이기 위해 제안되었다. RAPID와 경합 기반 랜덤 액세스를 수행하는 장치가 공존할 경우 RAPID가 랜덤 액세스 부하를 줄이기 위해 RAPID를 위해 할당되는 프리앰블 수를 결정하는 것이 중요하다. 시뮬레이션 결과에 따르면 RAPID는 99.999%의신뢰도를 만족시키는 지연시간을 최신 기술에 비해 80.8% 줄이면서, 랜덤 액세스부하를 30.5% 줄인다. 둘째, 프리앰블 충돌 문제를 해결하기 위해 자체 상향링크 동기화 프레임워크인 EsTA를 개발한다. 프리앰블 충돌은 여러 장치가 동일한 프리앰블을 전송할 때 발생한다. 구체적으로, 단말이 심층 신경망 모델을 사용하여 timing advance(TA) command를 추정하고 TA값을 결정하는 프레임 워크를 제안한다. 네트워크 시스템의 부반송파 간격이 30 및 60 kHz 일 때, TA command 추정 정확도는98–99%를 달성 할 수 있다. 마지막으로, 밀리미터파 네트워크에서 간섭을 줄이기 위한 간섭 인식 빔 조정 방법인 IBA를 제안한다. 시간과 주파수 자원을 다르게 예약하여 간섭을 줄이는 기존의 방법과 달리 IBA는 빔 조정을 통해 간섭을 제어한다.이 때, 간섭을 줄이기 위해 새로운 빔 쌍을 찾는 검색 공간을 줄이는 것이 중요하다.현실적으로 모든 빔 쌍의 조합을 검색하는 것은 불가능하다. 따라서 IBA는 Monte Carlo 방법을 통해 검색 공간을 축소하여 local optimum을 달성하도록 설계되어야한다. IBA는 5G 표준의 빔 조정 방법과 비교했을 때, 하위 50% throughput의 중간값이최대 50%까지 향상된다. 요약하면, 우리는 5G 및 그 이후의 다양한 사용 사례를 위해서 2 단계 랜덤 액세스, 자체 상향링크 동기화 프레임 워크, 그리고 간섭 인식 빔조정 방법을 제안한다. 이 연구를 통해 최신 기술에 비해 지연시간 및 처리량과 같은네트워크 성능이 향상된다.1 Introduction 1 1.1 5G Vision, Applications, and Keywords 1 1.2 Overview of Existing Approach 3 1.3 Main Contributions 4 1.3.1 RAPID: Two-Step Random Access 4 1.3.2 EsTA: Self-Uplink Synchronization 5 1.3.3 IBA: Interference-Aware Beam Adjustment 5 1.4 Organization of the Dissertation 6 2 RAPID: Contention Resolution-based Random Access Procedure using Context ID for IoT 7 2.1 Introduction 7 2.2 Background 10 2.2.1 RRC State 10 2.2.2 Random Access Procedure 11 2.2.3 Uplink Latency in RRC INACTIVE State 13 2.2.4 Related Work 14 2.3 RAPID: Proposed Random Access Procedure 15 2.3.1 Overview 15 2.3.2 Criterion of Applying RAPID 16 2.3.3 Preamble Set and RACH Period Allocation 17 2.3.4 Preamble Transmission 18 2.3.5 RAR Transmission 19 2.3.6 AS Context ID Allocation 21 2.3.7 Number of Preambles for RAPID 22 2.4 Access Pattern Analyzer 22 2.4.1 Overview 22 2.4.2 APA Operation 23 2.4.3 Margin Value 26 2.4.4 Offset Index Decision 26 2.5 Random Access Load Analysis 27 2.5.1 System Model 28 2.5.2 Markov Chain Model for 4-Step RA 29 2.5.3 Average Random Access Load for 4-Step RA 34 2.5.4 Markov Chain Model for RAPID 34 2.5.5 Average Random Access Load for RAPID 37 2.5.6 Validation of Analysis 38 2.5.7 Optimization Problem 41 2.6 Performance Evaluation 42 2.6.1 Simulation Setup 42 2.6.2 Number of Preambles for RAPID 43 2.6.3 Performance of RAPID 43 2.6.4 Performance of APA 48 2.7 Summary 48 3 EsTA: Self-Uplink Synchronization in 2-Step Random Access 49 3.1 Introduction 49 3.2 Background 51 3.2.1 Overview of 2-Step CBRA 51 3.2.2 Channel Structure for msgA 52 3.2.3 TA Handling for the Payload 54 3.2.4 2-Step Random Access in Recent Literature 56 3.3 Challenges of 2-Step Random Access 57 3.3.1 Preamble Allocation 57 3.3.2 Resource Mapping for msgA 58 3.3.3 DFT Operation in gNB 58 3.3.4 Detected Collision Problem 58 3.4 EsTA: Proposed Self-UL Synchronization Procedure 59 3.4.1 Overview 60 3.4.2 Overall Procedures 60 3.4.3 Performance Evaluation 61 3.4.4 Future Research Perspectives 65 3.5 Summary 65 4 IBA: Interference-Aware Beam Adjustment for 5G mmWave Networks 67 4.1 Introduction 67 4.2 Background 68 4.2.1 Beam Management in 5G NR 68 4.2.2 System-Level Simulation and 3D Beamforming for 5G NR 70 4.3 Motivation 70 4.3.1 Throughput Degradation by Interference 70 4.4 IBA: Proposed Interference Management Scheme 72 4.4.1 Overall Procedure 72 4.4.2 Reduction of Search Space 72 4.4.3 Algorithm for IBA 75 4.5 Performance Evaluation 76 4.6 Summary 78 5 Concluding Remarks 79 5.1 Research Contributions 79 5.2 Future Work 80 Abstract (In Korean) 89 감사의 글 92Docto

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

Redução de sinalização e agendador de recursos periódicos para redes industriais M2M

Devido à introdução de novas funcionalidades e aplicações M2M (Machine-to-Machine) na indústria, novos dispositivos precisarão ser conectados às redes de comunicação existentes, coexistindo com os atuais. As novas tecnologias de comunicação móvel, que ainda estão em processo de padronização, prometem cumprir com os requisitos de comunicação exigidos pelos sistemas de automação industrial. Portanto, esta tese tem como principal contribuição analisar a comunicação industrial M2M, sua viabilidade, implantação, características, limitações e se é adequada para os cenários, requisitos e exigências industriais. Além disso, também é realizado o desenvolvimento de um algoritmo de agendamento para dispositivos que necessitam de recursos periódicos de rede. Esse algoritmo tem o objetivo de reduzir a sinalização de rede, aumentar a capacidade de transmissão de dados, ou ainda, aumentar o número de dispositivos operantes na rede industrial. Os métodos propostos são validados usando uma estrutura de simulação LTE-A e métricas de rede tais como: atraso e jitter as quais são usadas para comparar o desempenho da abordagem proposta com os atuais agendadores de última geração. Os resultados mostram que a aplicação do agendador de recursos cíclicos e o esquema de redução de sinalização juntos podem melhorar a função de utilização do sistema bem como a satisfação dos usuários.Due to the introduction of new M2M (Machine-to-Machine) functionalities and applications in the industry, new devices will need to be connected to existing communication networks, coexisting with current ones. The new mobile communication technologies, which are still in the standardization process, promise to comply with the communication requirements demanded by industrial automation systems. Therefore, this thesis has as its main contribution to analyze the M2M communication, its feasibility, implantation, characteristics, limitations and if it is adequate for the scenarios, requirements and industrial needs. In addition, it is also developed a scheduling algorithm for devices that use periodic network resources. This algorithm aims to reduce network signaling, increase data transmission capacity, or increase the number of devices operating in the industrial network. The proposed methods are validated using a LTE-A simulation framework and network metrics such as delay and jitter, which are used to compare the performance of the proposed approach with the current state-of-the-art schedulers. The results show that the application of the cyclic resource scheduler and the signaling reduction scheme together can improve the system’s utilization function as well as user satisfaction