Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Optimización de problemas de varios objetivos desde un enfoque de eficiencia energética aplicado a redes celulares heterogéneas 5G usando un marco de conmutación de celdas pequeñas

This Ph.D. dissertation addresses the Many-Objective Optimization Problem (MaOP) study to reduce the inter-cell interference and the power consumption for realistic Centralized, Collaborative, Cloud, and Clean Radio Access Networks (C-RANs). It uses the Cell Switch-Off (CSO) scheme to switch-off/on Remote Radio Units (RRUs) and the Coordinated Scheduling (CS) technique to allocate resource blocks smartly. The EF1-NSGA-III (It is a variation of the NSGA-III algorithm that uses the front 1 to find extreme points at the normalization procedure extended in this thesis) algorithm is employed to solve a proposed Many-Objective Optimization Problem (MaOP). It is composed of four objective functions, four constraints, and two decision variables. However, the above problem is redefined to have three objective functions to see the performance comparison between the NSGA-II and EF1-NSGA-III algorithms. The OpenAirInterface (OAI) platform is used to evaluate and validate the performance of an indoor coverage system because most of the user-end equipment of next-generation cellular networks will be in an indoor environment. It constitutes the fastest growing 5G open-source platform that implements 3GPP technology on general-purpose computers, fast Ethernet transport ports, and Commercial-Off-The-Shelf (COTS) software-defined radio hardware. This document is composed of five contributions. The first one is a survey about testbed, emulators, and simulators for 4G/5G cellular networks. The second one is the extension of the KanGAL's NSGA-II code to implement the EF1-NSGA-III, adaptive EF1-NSGA-III (A-EF1-NSGA-III), and efficient adaptive EF1-NSGA-III (A$^2$-EF1-NSGA-III). They support up to 10 objective functions, manage real, integer, and binary decision variables, and many constraints. The above algorithms outperform other works in terms of the Inverted Generational Distance (IGD) metric. The third contribution is the implementation of real-time emulation methodologies for C-RANs using a frequency domain representation in OAI. It improves the average computation time 10-fold compared to the time domain without using Radio Frequency hardware and avoids their uncertainties. The fourth one is the implementation of the Coordination Scheduling (CS) technique as a proof-of-concept to validate the advantages of frequency domain methodologies and to allocate resource blocks dynamically among RRUs. Finally, a many-objective optimization problem is defined and solved with evolutionary algorithms where diversity is managed based on crowded-distance and reference points to reduce the power consumption for C-RANs. The solutions obtained are considered to control the scheduling task at the Radio Cloud Center (RCC) and to switch RRUs.Este disertación aborda el estudio del problema de optimización de varios objetivos (MaOP) para reducir la interferencia entre células y el consumo de energía para redes de acceso de radio en tiempo real, colaborativas, en la nube y limpias (C-RAN). Utiliza el esquema de conmutacion de celdas (CSO) para apagar / encender unidades de radio remotas (RRU) y la técnica de programación coordinada (CS) para asignar bloques de recursos de manera inteligente. El algoritmo EF1-NSGA-III (es una variación del algoritmo NSGA-III que usa el primer frente de pareto para encontrar puntos extremos en el procedimiento de normalización extendido en esta tesis) se utiliza para resolver un problema de optimización de varios objetivos (MaOP) propuesto. Se compone de cuatro funciones objetivos, cuatro restricciones y dos variables de decisión. Sin embargo, el problema anterior se redefine para tener tres funciones objetivas para ver la comparación de rendimiento entre los algoritmos NSGA-II y EF1-NSGA-III. La plataforma OpenAirInterface (OAI) se utiliza para evaluar y validar el rendimiento de un sistema de cobertura en interiores porque la mayoría del equipos móviles de las redes celulares de próxima generación estarán en un entorno interior. Ella constituye la plataforma de código abierto 5G de más rápido crecimiento que implementa la tecnología 3GPP en computadoras de uso general, puertos de transporte Ethernet rápidos y hardware de radio definido por software comercial (COTS). Este documento se compone de cinco contribuciones. La primera es una estudio sobre banco de pruebas, emuladores y simuladores para redes celulares 4G / 5G. El segundo es la extensión del código NSGA-II de KanGAL para implementar EF1-NSGA-III, EF1-NSGA-III adaptativo (A-EF1-NSGA-III) y EF1-NSGA-III adaptativo eficiente (A $^ 2$ -EF1-NSGA-III). Admiten hasta 10 funciones objetivas, gestionan variables de decisión reales, enteras y binarias, y muchas restricciones. Los algoritmos anteriores superan a otros trabajos en términos de la métrica de distancia generacional invertida (IGD). La tercera contribución es la implementación de metodologías de emulación en tiempo real para C-RAN utilizando una representación de dominio de frecuencia en OAI. Mejora el tiempo de cálculo promedio 10 veces en comparación con el dominio del tiempo sin usar hardware de radiofrecuencia y evita sus incertidumbres. El cuarto es la implementación de la técnica de Programación de Coordinación (CS) como prueba de concepto para validar las ventajas de las metodologías de dominio de frecuencia y asignar bloques de recursos dinámicamente entre las RRU. Finalmente, un problema de optimización de muchos objetivos se define y resuelve con algoritmos evolutivos en los que la diversidad se gestiona en función de la distancia de crouding y los puntos de referencia para reducir el consumo de energía de las C-RAN. Las soluciones obtenidas controlan la tarea de programación en Radio Cloud Center (RCC) y conmutan las RRU.Proyecto personal: Redes celulares de próxima generaciónDoctorad

Implementation and automation of beam management test system

Abstract. The mobile network technologies nowadays have come to a point where transferring data as much as possible, as fast as possible and as reliable as possible has become to the main requirement and this has led to the development of the capacity to become one of the main aspects in mobile technology. The 5G mobile technology with millimetre-wave frequency range combined with beamforming technology is currently answer to the capacity question of the networks. Beamforming in millimetre-waves requires a beam management technology, which basically handles the controlling of the beams. As a new feature the beam management requires testing and verification. In this thesis the environment which is capable to test beam management technology with the MediaTek the prototype UE was created. The beam management was tested with the help of a linear actuator which can traverse UE sideways in front of 5G NR millimetre-wave antenna. The main task in this thesis was to create controlling solutions for the linear actuator so that it can be controlled manually and to integrate the test system to the test automation later. The test automation was implemented in python programming language, so the controlling solution was created using python making the integration easier. After the completing the controlling solution, the beam management tests were executed. There were two test scenarios completed in this thesis, the first one tested beam management while prototype UE was connected to test network and sending ping requests. The second scenario tested the UE while connected to test network and data was transferred to UE from the network. Both scenarios completed successfully resulting the beams to be switched while the UE traversed back and forth with the linear actuator. The manual testing of beam management was successful according to the results. Finally, the existing automation, beam management environment integration to the automation and possible test scenarios to run with the automation were introduced.Keilanhallintatestijärjestelmän toteutus ja automatisointi. Tiivistelmä. Nykypäivän mobiiliverkkoteknologiat ovat tulleet siihen pisteeseen, että datan siirtäminen nopeasti, luotettavasti ja paljon kerralla on tullut pääkehityksen kohteeksi ja johtanut kehitystyön kohdistumisen mobiiliverkon kapasiteettiin. 5G mobiiliteknologia ja millimetriaaltoihin pohjautuva taajuusalue yhdessä keilanhallintateknologian kanssa ovat vastaus verkkojen kapasiteettikysymykseen. Keilanmuodostus millimetriaalloilla vaatii avukseen keilanhallintateknologiaa, joka käytännössä hallitsee keilojen kontrolloinnin. Uutena ominaisuutena keilanhallinta vaatii paljon testausta ja todentamista. Tässä työssä luotiin ympäristö, joka kykenee testaamaan keilanhallintateknologiaa käyttäen MediaTekin prototyyppipuhelinta. Keilanhallintaa testattiin lineaarisen toimilaitteen avulla, joka kykenee kuljettamaan prototyyppipuhelinta sivuttaissuunnassa 5G NR antennin edessä, joka toimii millimetriaaltoalueella. Työn päätehtävänä oli luoda ohjausratkaisu lineaariselle toimilaitteelle, jotta sitä voitaisiin ohjata manuaalisesti ja myöhemmin integroida testijärjestelmä automaatioon. Testiautomaatio oli luotu käyttämällä python ohjelmointikieltä, niinpä ohjausratkaisu luotiin käyttäen pythonia, tehden näin integraation testiautomaatioon helpommaksi. Kun ohjausratkaisu oli saatu valmiiksi, suoritettiin keilanhallintatestit. Tässä työssä ajettiin kahta erilaista testiskenaariota, ensimmäisessä skenaariossa testattiin keilanhallintaa, kun prototyyppipuhelin oli yhdistettynä testiverkkoon ja lähetti verkolle ping -paketteja. Toisessa skenaariossa testattiin keilanhallintaa, kun puhelin oli yhdistettynä testiverkkoon ja datansiirto testiverkolta puhelimelle oli aktiivisena. Molemmat skenaariot suoritettiin onnistuneesti tuloksena keilojen vaihtuminen, kun puhelinta liikutettiin edestakaisin lineaarisen toimilaitteen avulla. Tulosten perusteella keilanhallinnan manuaalinen testaaminen suoritettiin onnistuneesti. Lopuksi esiteltiin olemassa oleva automaatio, keilanhallintaympäristön integroiminen automaatioon ja mahdolliset testiskenaariot, joita automaatiolla voidaan ajaa

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