Exploitation of wireless control link in the software-defined LEO satellite network

software-defined satellite network, control link, cross layer optimization, power-efficient control link algorithmThe low earth orbit (LEO) satellite network can benefit from software-defined networking (SDN) by lightening forwarding devices and improving service diversity. In order to apply SDN into the network, however, reliable SDN control links should be associated from satellite gateways to satellites, with the wireless and mobile properties of the network taken into account. Since these characteristics affect both control link association and gateway power allocation, we define this new cross layer problem as an SDN control link problem. The problem is discussed from the viewpoint of multilayers such as automatic repeat request (ARQ) and gateway power allocation at the Link layer, and split transmit control protocol (TCP) and link scheduling at the Transport layer. A centralized SDN control framework constrained by maximum total power is introduced to enhance gateway power efficiency for control link setup. Based on the power control analysis of the problem, a power-efficient control link algorithm is developed, which establishes low latency control links with reduced power consumption. Along with the sensitivity analysis of the proposed control link algorithm, numerical results demonstrate low latency and high reliability of control links established by the algorithm, ultimately suggesting the feasibility, both technical and economical, of the software-defined LEO satellite network.open1. INTRODUCTION 1 1.1 Software-Defined Satellite Network 1 1.2 Wireless SDN Control Link Problem Statement 4 1.3 Contributions and Overview of Theses 5 1.4 Related Works 6 2. MODELING AND FORMULATION 8 2.1 Control Link Association 8 2.1.1 Graph Model 8 2.1.2 ARQ and Split TCP 9 2.1.3 Link Association Variable 10 2.2 Control Link Reliability and Expected Latency Formulation 12 2.2.1 Control Link Reliability and Gateway Power 12 2.2.2 Expected Latency Formulation 13 2.3 SDN Control Link Problem 16 2.3.1 Expected Latency Minimization Problem 16 2.3.2 Power-Efficient SDN Control Link Problem 17 3. SDN CONTROL LINK ALGORITHM 22 4. NUMERICAL RESULTS AND ANALYSIS 25 4.1 Latency Analysis and Feasibility of the Software-Defined Satellite Network 27 4.2 Sensitivity Analysis and Selection of the Maximum Total Power 33 5. CONCLUSION 37 APPENDIX 38 REFERENCES 40저궤도(LEO) 위성 네트워크는 데이터 전달 장치를 간소화하고 서비스 다양성을 향상시키는 등, 소프트웨어 정의 네트워킹(SDN)로부터 다양한 이점을 얻을 수 있다. 그러나 SDN을 위성 네트워크에 적용하기 위해서는, 신뢰성 있는 SDN 제어 링크가 위성 게이트웨이로부터 위성까지 연결되어야 하며, 위성 네트워크의 무선 특성과 이동성이 동시에 고려되어야 한다. 이러한 특성들은 제어 링크 연결과 게이트웨이 전력 할당 모두에 영향을 미치기 때문에, 우리는 이러한 교차 계층 문제를 SDN 제어 링크 문제로 새롭게 정의한다. 이 문제는 전송 계층의 자동 재전송 요구(ARQ) 및 전송 제어 프로토콜(TCP), 네트워크 계층의 라우팅, 물리 계층의 전력 할당과 같은 다중 계층의 관점에서 논의된다. 본 논문에서는 제어 링크 설정에 필요한 게이트웨이 전력 효율을 높이기 위해 최대 총 전력을 제한하는 중앙집권화 SDN 제어 프레임워크를 도입한다. 제안된 문제에 대한 전력 할당 분석을 기반으로, 전력 소비가 적으면서도 지연이 적은 제어 링크를 연결하는 전력 효율적인 제어 링크 알고리즘이 제안된다. 제안된 제어 링크 알고리즘의 민감도 분석과 함께, 시뮬레이션 결과는 알고리즘에 의해 설정되는 제어 링크의 낮은 지연과 높은 신뢰성을 보여주며, 궁극적으로 소프트웨어 정의 LEO 위성 네트워크의 기술적 및 경제적 타당성을 제시한다.MasterdCollectio

Non-Terrestrial Networks in the 6G Era: Challenges and Opportunities

Many organizations recognize non-terrestrial networks (NTNs) as a key component to provide cost-effective and high-capacity connectivity in future 6th generation (6G) wireless networks. Despite this premise, there are still many questions to be answered for proper network design, including those associated to latency and coverage constraints. In this paper, after reviewing research activities on NTNs, we present the characteristics and enabling technologies of NTNs in the 6G landscape and shed light on the challenges in the field that are still open for future research. As a case study, we evaluate the performance of an NTN scenario in which satellites use millimeter wave (mmWave) frequencies to provide access connectivity to on-the-ground mobile terminals as a function of different networking configurations.Comment: 8 pages, 4 figures, 2 tables, submitted for publication to the IEE

Satellite-5G integration: a network perspective

Future 5G mobile communication systems are expected to integrate different radio access technologies, including the satellite component. Within the 5G framework, the terrestrial services can be augmented with the development of HTS systems and new mega-constellations meeting 5G requirements, such as high bandwidth, low latency, and increased coverage including rural areas, air, and seas. This article provides an overview of the current 5G initiatives and projects followed by a proposed architecture for 5G satellite networks where the SDN/NFV approach facilitates the integration with the 5G terrestrial system. In addition, a novel technique based on network coding is analyzed for the joint exploitation of multiple paths in such an integrated satellite-terrestrial system. For TCP-based applications, an analytical model is presented to achieve an optimal traffic split between terrestrial and satellite paths and optimal redundancy levels

Reliable Packet Streams with Multipath Network Coding

With increasing computational capabilities and advances in robotics, technology is at the verge of the next industrial revolution. An growing number of tasks can be performed by artificial intelligence and agile robots. This impacts almost every part of the economy, including agriculture, transportation, industrial manufacturing and even social interactions. In all applications of automated machines, communication is a critical component to enable cooperation between machines and exchange of sensor and control signals. The mobility and scale at which these automated machines are deployed also challenges todays communication systems. These complex cyber-physical systems consisting of up to hundreds of mobile machines require highly reliable connectivity to operate safely and efficiently. Current automation systems use wired communication to guarantee low latency connectivity. But wired connections cannot be used to connect mobile robots and are also problematic to deploy at scale. Therefore, wireless connectivity is a necessity. On the other hand, it is subject to many external influences and cannot reach the same level of reliability as the wired communication systems. This thesis aims to address this problem by proposing methods to combine multiple unreliable wireless connections to a stable channel. The foundation for this work is Caterpillar Random Linear Network Coding (CRLNC), a new variant of network code designed to achieve low latency. CRLNC performs similar to block codes in recovery of lost packets, but with a significantly decreased latency. CRLNC with Feedback (CRLNC-FB) integrates a Selective-Repeat ARQ (SR-ARQ) to optimize the tradeoff between delay and throughput of reliable communication. The proposed protocol allows to slightly increase the overhead to reduce the packet delay at the receiver. With CRLNC, delay can be reduced by more than 50 % with only a 10 % reduction in throughput. Finally, CRLNC is combined with a statistical multipath scheduler to optimize the reliability and service availability in wireless network with multiple unreliable paths. This multipath CRLNC scheme improves the reliability of a fixed-rate packet stream by 10 % in a system model based on real-world measurements of LTE and WiFi. All the proposed protocols have been implemented in the software library NCKernel. With NCKernel, these protocols could be evaluated in simulated and emulated networks, and were also deployed in several real-world testbeds and demonstrators.:Abstract 2 Acknowledgements 6 1 Introduction 7 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2 Use Cases and Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3 Opportunities of Multipath . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.4 Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2 State of the Art of Multipath Communication 19 2.1 Physical Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2 Data Link Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.3 Network Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.4 Transport Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.5 Application Layer and Session Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.6 Research Gap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3 NCKernel: Network Coding Protocol Framework 27 3.1 Theory that matters! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.2 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.3 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.3.1 Socket Buffers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.3.2 En-/Re-/Decoder API . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.3.3 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.3.4 Timers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.3.5 Tracing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.4 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.5 Protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 4 Low-Latency Network Coding 35 4.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 4.2 Random Linear Network Coding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 4.3 Low Latency Network Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.4 CRLNC: Caterpillar Random Linear Network Coding . . . . . . . . . . . . . . . . . . 38 4.4.1 Encoding and Packet Format . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4.4.2 Decoding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.4.3 Computational Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.5 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.5.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.5.2 Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.5.3 Packet Loss Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.5.4 Delay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.5.5 Window Size Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 5 Delay-Throughput Tradeoff 55 5.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5.2 Network Coding with ARQ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5.3 CRLNC-FB: CRLNC with Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 5.3.1 Encoding and Packet Format . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3.2 Decoding and Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3.3 Retransmissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.4.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.4.2 Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5.4.3 Systematic Retransmissions . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5.4.4 Coded Packet Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 5.4.5 Comparison with other Protocols . . . . . . . . . . . . . . . . . . . . . . . . 67 5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 6 Multipath for Reliable Low-Latency Packet Streams 73 6.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 6.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 6.3 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.3.1 Traffic Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.3.2 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.3.3 Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 6.3.4 Reliability Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 6.4 Multipath CRLNC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 6.4.1 Window Size for Heterogeneous Paths . . . . . . . . . . . . . . . . . . . . . 77 6.4.2 Packet Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.5 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.5.1 Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.5.2 Preliminary Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6.5.3 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 6.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 7 Conclusion 94 7.1 Results and Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 7.2 Future Research Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Acronyms 99 Publications 101 Bibliography 10

An ns-3 Module for Non-Terrestrial Network (NTN) Simulation: Implementation, Design and Performance Evaluation

While the 5th generation (5G) of mobile networks has landed in the commercial area, with features such as millimeter waves already being deployed, there still are other functionalities to be investigated, for example non-terrestrial networks (NTN). In this context, satellite-based communications offer new opportunities for future research and applications, such as providing connectivity to remote or otherwise unconnected areas, complementing terrestrial networks to reduce connection downtime, as well as increasing traffic efficiency in hot spot areas. This thesis implements the 3rd generation partnership project (3GPP) channel model for NTNs, which introduces an ad-hoc characterization of the attenuation of the signal in the space scenario, as well as new challenges for the whole protocol stack, including those associated with latency and coverage constraints, compared to terrestrial network. In such regard, we extend the ns-3 simulator with new modules to implement the attenuation of the signal due to atmospheric gases and scintillation and a new mobility model to account for the Geocentric Cartesian coordinate system of spaceborne vehicles. We evaluate the performance of the system based on full-stack end-to-end simulations, and provide guidelines on possible future developments.While the 5th generation (5G) of mobile networks has landed in the commercial area, with features such as millimeter waves already being deployed, there still are other functionalities to be investigated, for example non-terrestrial networks (NTN). In this context, satellite-based communications offer new opportunities for future research and applications, such as providing connectivity to remote or otherwise unconnected areas, complementing terrestrial networks to reduce connection downtime, as well as increasing traffic efficiency in hot spot areas. This thesis implements the 3rd generation partnership project (3GPP) channel model for NTNs, which introduces an ad-hoc characterization of the attenuation of the signal in the space scenario, as well as new challenges for the whole protocol stack, including those associated with latency and coverage constraints, compared to terrestrial network. In such regard, we extend the ns-3 simulator with new modules to implement the attenuation of the signal due to atmospheric gases and scintillation and a new mobility model to account for the Geocentric Cartesian coordinate system of spaceborne vehicles. We evaluate the performance of the system based on full-stack end-to-end simulations, and provide guidelines on possible future developments

Evolution of Non-Terrestrial Networks From 5G to 6G: A Survey

Non-terrestrial networks (NTNs) traditionally have certain limited applications. However, the recent technological advancements and manufacturing cost reduction opened up myriad applications of NTNs for 5G and beyond networks, especially when integrated into terrestrial networks (TNs). This article comprehensively surveys the evolution of NTNs highlighting their relevance to 5G networks and essentially, how it will play a pivotal role in the development of 6G ecosystem. We discuss important features of NTNs integration into TNs and the synergies by delving into the new range of services and use cases, various architectures, technological enablers, and higher layer aspects pertinent to NTNs integration. Moreover, we review the corresponding challenges arising from the technical peculiarities and the new approaches being adopted to develop efficient integrated ground-air-space (GAS) networks. Our survey further includes the major progress and outcomes from academic research as well as industrial efforts representing the main industrial trends, field trials, and prototyping towards the 6G networks

Evolution of Non-Terrestrial Networks From 5G to 6G: A Survey

Non-terrestrial networks (NTNs) traditionally have certain limited applications. However, the recent technological advancements and manufacturing cost reduction opened up myriad applications of NTNs for 5G and beyond networks, especially when integrated into terrestrial networks (TNs). This article comprehensively surveys the evolution of NTNs highlighting their relevance to 5G networks and essentially, how it will play a pivotal role in the development of 6G ecosystem. We discuss important features of NTNs integration into TNs and the synergies by delving into the new range of services and use cases, various architectures, technological enablers, and higher layer aspects pertinent to NTNs integration. Moreover, we review the corresponding challenges arising from the technical peculiarities and the new approaches being adopted to develop efficient integrated ground-air-space (GAS) networks. Our survey further includes the major progress and outcomes from academic research as well as industrial efforts representing the main industrial trends, field trials, and prototyping towards the 6G networks