arXiv subjects

Xingqin Lin

Publications and source records attributed to Xingqin Lin.

At least 37 records · Page 2Linked to original sources

arXiv2023

Hardware Acceleration for Open Radio Access Networks: A Contemporary Overview

Radio access networks (RAN) are going through a paradigm shift towards interoperable, intelligent, software-defined, and cloud-native open RAN solutions. A key challenge towards the adoption and deployment of open RAN at scale is performance. Hence, it is critical to leverage the power of hardware acceleration to offload compute-heavy RAN workloads to specialized hardware devices to enable accelerated compute for open RAN deployments. In this article, we provide a state-of-the-art overview of hardware acceleration for open RAN in the fifth generation (5G) wireless networks. We also present a practical implementation of inline hardware acceleration for open RAN layer 1 processing and identify several areas for future exploration towards the sixth generation (6G) wireless networks.

eess.SP↗

arXiv2023

Deep Reinforcement Learning for Interference Management in UAV-based 3D Networks: Potentials and Challenges

Modern cellular networks are multi-cell and use universal frequency reuse to maximize spectral efficiency. This results in high inter-cell interference. This problem is growing as cellular networks become three-dimensional with the adoption of unmanned aerial vehicles (UAVs). This is because the strength and number of interference links rapidly increase due to the line-of-sight channels in UAV communications. Existing interference management solutions need each transmitter to know the channel information of interfering signals, rendering them impractical due to excessive signaling overhead. In this paper, we propose leveraging deep reinforcement learning for interference management to tackle this shortcoming. In particular, we show that interference can still be effectively mitigated even without knowing its channel information. We then discuss novel approaches to scale the algorithms with linear/sublinear complexity and decentralize them using multi-agent reinforcement learning. By harnessing interference, the proposed solutions enable the continued growth of civilian UAVs.

cs.IT↗

arXiv2023

Artificial Intelligence in 3GPP 5G-Advanced: A Survey

Industries worldwide are being transformed by artificial intelligence (AI), and the telecom industry is no different. Standardization is critical for industry alignment to achieve widespread adoption of AI in telecom. The 3rd generation partnership project (3GPP) Release 18 is the first release of 5G-Advanced, which includes a diverse set of study and work items dedicated to AI. This article provides a holistic overview of the state of the art in the 3GPP work on AI in 5G-Advanced, by presenting the various 3GPP Release-18 activities on AI as an organic whole, explaining in detail the design aspects, and sharing various design rationales influencing standardization.

cs.NI↗

arXiv2023

5G-Advanced Towards 6G: Past, Present, and Future

Since the start of 5G work in 3GPP in early 2016, tremendous progress has been made in both standardization and commercial deployments. 3GPP is now entering the second phase of 5G standardization, known as 5G-Advanced, built on the 5G baseline in 3GPP Releases 15, 16, and 17. 3GPP Release 18, the start of 5G-Advanced, includes a diverse set of features that cover both device and network evolutions, providing balanced mobile broadband evolution and further vertical domain expansion and accommodating both immediate and long-term commercial needs. 5G-Advanced will significantly expand 5G capabilities, address many new use cases, transform connectivity experiences, and serve as an essential step in developing mobile communications towards 6G. This paper provides a comprehensive overview of the 3GPP 5G-Advanced development, introducing the prominent state-of-the-art technologies investigated in 3GPP and identifying key evolution directions for future research and standardization.

cs.IT↗

arXiv2023

Technology Trends for Massive MIMO towards 6G

At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) has been envisioned as one of the enabling technologies. With the continued success of being applied in the 5G and beyond, the massive MIMO technology has demonstrated its advantageousness, integrability, and extendibility. Moreover, several evolutionary features and revolutionizing trends for massive MIMO have gradually emerged in recent years, which are expected to reshape the future 6G wireless systems and networks. Specifically, the functions and performance of future massive MIMO systems will be enabled and enhanced via combining other innovative technologies, architectures, and strategies such as intelligent omni-surfaces (IOSs)/intelligent reflecting surfaces (IRSs), artificial intelligence (AI), THz communications, cell free architecture. Also, more diverse vertical applications based on massive MIMO will emerge and prosper, such as wireless localization and sensing, vehicular communications, non-terrestrial communications, remote sensing, inter-planetary communications.

cs.IT↗

arXiv2022

6G Digital Twin Networks: From Theory to Practice

Digital twin networks (DTNs) are real-time replicas of physical networks. They are emerging as a powerful technology for design, diagnosis, simulation, what-if-analysis, and artificial intelligence (AI)/machine learning (ML) driven real-time optimization and control of the sixth-generation (6G) wireless networks. Despite the great potential of what digital twins can offer for 6G, realizing the desired capabilities of 6G DTNs requires tackling many design aspects including data, models, and interfaces. In this article, we provide an overview of 6G DTNs by presenting prominent use cases and their service requirements, describing a reference architecture, and discussing fundamental design aspects. We also present a real-world example to illustrate how DTNs can be built upon and operated in a real-time reference development platform - Omniverse.

cs.NI↗

arXiv2022

Towards Providing Connectivity When and Where It Counts: An Overview of Deployable 5G Networks

Public safety operations require fast and reliable mission critical communications under various scenarios, in which the availability of wireless connectivity can be a question of life or death. To provide connectivity when and where it counts, we have witnessed a growing demand for deployable networks for public safety in natural disasters or emergency situations. This article investigates the opportunities of using the 5th generation (5G) new radio (NR) standard for designing flexible and reliable deployable networks. We describe use cases and provide an overview of deployable 5G network concepts, including architecture options, system performance analysis, and coexistence aspects. We also identify technical challenges that can be considered in the evolution of 5G NR to unlock the full potential of deployable 5G networks.

cs.NI↗

arXiv2022

A Primer on HIBS -- High Altitude Platform Stations as IMT Base Stations

Mobile communication via high-altitude platforms operating in the stratosphere is an idea that has been on the table for decades. In the past few years, however, with recent advances in technology and parallel progress in standardization and regulatory bodies like 3GPP and ITU, these ideas have gained considerable momentum. In this article, we present a comprehensive overview of HIBS - High Altitude Platform Stations as IMT Base Stations. We lay out possible use cases and summarize the current status of the development, from a technological point of view as well as from standardization in 3GPP, and regarding spectrum aspects. We then present preliminary system level simulation results to shed light on the performance of HIBS. We conclude with pointing out several directions for future research.

cs.NI↗

arXiv2022

Embracing AI in 5G-Advanced Towards 6G: A Joint 3GPP and O-RAN Perspective

Artificial intelligence (AI) has emerged as a powerful technology that improves system performance and enables new features in 5G and beyond. Standardization, defining functionality and interfaces, is essential for driving the industry alignment required to deliver the mass adoption of AI in 5G-Advanced and 6G. However, fragmented efforts in different standards bodies, such as the third generation partnership project (3GPP) and the open radio access network (O-RAN) Alliance, can lead to confusion and uncertainty about which standards to follow and which aspects of the standards to embrace. This article provides a joint 3GPP and O-RAN perspective on the state of the art in AI adoption in mobile communication systems, including the fundamentals of 5G architecture and its evolution towards openness and intelligence, AI for 5G-Advanced evolution, and a case study on AI-enabled traffic steering. We also identify several areas for future exploration to accelerate AI adoption on the path towards 6G.

cs.NI↗

arXiv2022

Autonomous Navigation and Configuration of Integrated Access Backhauling for UAV Base Station Using Reinforcement Learning

Fast and reliable connectivity is essential to enhancing situational awareness and operational efficiency for public safety mission-critical (MC) users. In emergency or disaster circumstances, where existing cellular network coverage and capacity may not be available to meet MC communication demands, deployable-network-based solutions such as cells-on-wheels/wings can be utilized swiftly to ensure reliable connection for MC users. In this paper, we consider a scenario where a macro base station (BS) is destroyed due to a natural disaster and an unmanned aerial vehicle carrying BS (UAV-BS) is set up to provide temporary coverage for users in the disaster area. The UAV-BS is integrated into the mobile network using the 5G integrated access and backhaul (IAB) technology. We propose a framework and signalling procedure for applying machine learning to this use case. A deep reinforcement learning algorithm is designed to jointly optimize the access and backhaul antenna tilt as well as the three-dimensional location of the UAV-BS in order to best serve the on-ground MC users while maintaining a good backhaul connection. Our result shows that the proposed algorithm can autonomously navigate and configure the UAV-BS to improve the throughput and reduce the drop rate of MC users.

cs.LG↗

arXiv2022

An Overview of 5G Advanced Evolution in 3GPP Release 18

The 3rd generation partnership project (3GPP) radio access network (RAN) plenary recently approved a work package for its Release 18, representing a major evolution and branded as the first release of 5G Advanced. The work package includes diverse study or work items that will significantly boost 5G performance and address a wide variety of new use cases. In particular, 3GPP Release 18 will embrace artificial intelligence and machine learning technologies to provide data-driven, intelligent network solutions. This article provides an overview of the 5G Advanced evolution in 3GPP Release 18, which is anticipated to trigger a paradigm shift and have a profound impact on future wireless networks.

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arXiv2021

Fueling the Next Quantum Leap in Cellular Networks: Embracing AI in 5G Evolution towards 6G

Cellular networks, such as 5G systems, are becoming increasingly complex for supporting various deployment scenarios and applications. Embracing artificial intelligence (AI) in 5G evolution is critical to managing the complexity and fueling the next quantum leap in 6G cellular networks. In this article, we share our experience and best practices in applying AI in cellular networks. We first present a primer on the state of the art of AI in cellular networks, including basic concepts and recent key advances. Then we discuss 3GPP standardization aspects and share various design rationales influencing standardization. We also present case studies with real network data to showcase how AI can improve network performance and enable network automation.

cs.NI↗

arXiv2021

On the Path to 6G: Embracing the Next Wave of Low Earth Orbit Satellite Access

Offering space-based Internet services with mega-constellations of low Earth orbit (LEO) satellites is a promising solution to connecting the unconnected. It can complement the coverage of terrestrial networks to help bridge the digital divide. However, there are challenges from operational obstacles to technical hurdles facing the development of LEO satellite access. This article provides an overview of state of the art in LEO satellite access, including the evolution of LEO satellite constellations and capabilities, critical technical challenges and solutions, standardization aspects from 5G evolution to 6G, and business considerations. We also identify several areas for future exploration to realize a tight integration of LEO satellite access with terrestrial networks in 6G.

cs.NI↗

arXiv2021

Doppler Shift Estimation in 5G New Radio Non-Terrestrial Networks

Evolving 5G New Radio (NR) to support non-terrestrial networks (NTNs), particularly satellite communication networks, is under exploration in 3GPP. The movement of the spaceborne platforms in NTNs may result in large timing varying Doppler shift that differs for devices in different locations. Using orthogonal frequency-division multiple access (OFDMA) in the uplink, each device will need to apply a different frequency adjustment value to compensate for the Doppler shift. To this end, the 3GPP Release-17 work on NTNs assumes that an NTN device is equipped with a global navigation satellite system (GNSS) chipset and thereby can determine its position and calculate the needed frequency adjustment value using its position information and satellite ephemeris data. This makes GNSS support essential for the NTN operation. However, GNSS signals are weak, not ubiquitous, and susceptible to interference and spoofing. We show that devices without access to GNSS signals can utilize reference signals in more than one frequency position in an OFDM carrier to estimate the Doppler shift and thereby determine the needed frequency adjustment value for pre-compensating the Doppler shift in the uplink. We analyze the performance, elaborate on how to utilize the NR reference signals, and present simulation results. The solution can reduce the dependency of NTN operation on GNSS with reasonable complexity and performance trade-off.

cs.NI↗

arXiv2021

5G from Space: An Overview of 3GPP Non-Terrestrial Networks

We provide an overview of the 3rd generation partnership project (3GPP) work on evolving the 5G wireless technology to support non-terrestrial satellite networks. Adapting 5G to support non-terrestrial networks entails a holistic design spanning across multiple areas from radio access network to services and system aspects to core and terminals. In this article, we describe the main topics of non-terrestrial networks, explain in detail the design aspects, and share various design rationales influencing standardization.

cs.NI↗

arXiv2021

Towards 6G with Connected Sky: UAVs and Beyond

The large-scale and ever-growing use of unmanned aerial vehicles (UAVs) in a wide range of applications is foreseen to be a major part of beyond 5G and 6G wireless networks in the next decade. The effective support of such massive deployment of UAVs requires offering reliable, secure, and cost-effective wireless connectivity. In this regard, cellular networks play essential roles in serving UAVs acting as flying user equipments. While the cellular networks provide promising connectivity solutions for UAVs, enabling robust UAV operations faces several challenges. In this paper, an overview of key barriers and design considerations of widespread commercial use of flying UAVs are presented along with their potential solutions. In addition, we discuss how cellular networks can support UAVs by relying on their advanced features, network intelligence, key enabling technologies for beyond 5G and 6G, and exploiting new tools from machine learning. Finally, we shed light on offering wireless services to high altitudes and the integration of non-terrestrial networks with terrestrial networks towards limitless connectivity in 6G.

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arXiv2021

Narrowband Internet of Things for Non-terrestrial Networks

The Narrowband Internet of Things (NB-IoT) is a cellular access technology developed by the Third Generation Partnership Project (3GPP) to provide wide area connectivity for the Internet of Things. Since its introduction in 3GPP Release 13, NB-IoT has in a few years achieved a remarkable market presence and is currently providing coverage in close to 100 countries. To further extend the reach of NB-IoT and to connect the unconnected, 3GPP Release 17 will study the feasibility of adapting NB-IoT to support non-terrestrial networks (NTNs). In this article, we review the fundamentals of NB-IoT and NTN and explain how NB-IoT can be adapted to support satellite communication through a minimal set of modifications.

cs.NI↗

arXiv2021

Internet of Things from Space: Transforming LTE Machine Type Communications for Non-terrestrial Networks

Satellite communication is experiencing a new dawn thanks to low earth orbit mega constellations being deployed at an unprecedented speed. Fueled by the renewed interest in non-terrestrial networks (NTN), the Third Generation Partnership Project (3GPP) is preparing 5G NR, NB-IoT and LTE-M for NTN operation. This article is focused on LTE-M and the essential adaptations needed for supporting satellite communication. Specifically, the major challenges facing LTE-M NTN at the physical and higher layers are discussed and potential solutions are outlined.

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