Transformational phase [5G-Advanced R20]

The collaborative efforts of industry technology advancement currently focus on evolution of the 5G-Advanced Releases 18, 19 and 20. In 2022, 3GPP finalized Release 17 and initiated the work on Release 18 expected to be completed until March 2024 for various study items to improve network capacity, latency, coverage, power efficiency and mobility. At the same time that 3GPP is technically working on Release 18, new topics are emerging in parallel. Release 19 is the second release of 5G-Advanced, it’s a continuation of Release 18, also the bridge towards 6G technology leap for new capabilities and efficiency. The first workshop June 2023 provide clarity on work items and schedule with further fine tuning of the content until December 2023. The Release 19 specifications are expected to be finalized and frozen in March 2025. Release 20 workshop in July 2024 will define scope of technology foundation for the next generation innovation platform towards finalization in September 2026. Current expectations are that official specifications work on 6G standards will start around 2025. Anticipating to support use cases requirements in 2030 and beyond, the first 6G standard Release 21 will need to be completed and ratified by early 2028. 
  • 5G-Advanced Release 18 [2022 -  2024]
  • 5G-Advanced Release 19 [Workshop June 2023 - March 2025]
  • 5G-Advanced Release 20 [Workshop includes 6G Study Items July2024 - Sept. 2026]
  • 6G Release 21 [Workshop includes 6G Work Items 2025 - 2028]
  • 6G Release 21 submission for IMT-2030 with self-evaluation [2029]
The best way to predict the future is to create it. Technology innovation connects societies and becomes a part of everyday life!
6G refers to communications and services at the time of convergence of service·terminal evolution and mobile communication evolution, which will arrive around 2030, based on the lessons learned from the world's first 5G commercialization.
  •  6G requires setting achievable goals and continuous communication with the market and consumers.
  •  Efforts of all participants in the new 6G ecosystem are required, such as expanding of 6G usage scenarios, selecting candidate spectrums, vitalizing open interfaces, e.g., Open RAN, and simple architecture options, etc.
6G is in its early stage, but major countries and companies have already started 6G R&D, presenting 6G visions and research results through technical forums and white papers.
  •  6G Framework Recommendation includes and proposes usage scenarios and capabilities, and some KPIs such as peak data rate are to be discussed in detail in the technical performance requirements (TPR) phase.
  •  It is essential to identify 6G products and services, to define simple architecture options, and to develop technologies for coverage expansion and for UE heat and power consumption to improve user experience.
6G Timeline:
  •  ITU completed the 6G Framework Recommendation in 2023 and plans to approve the 6G standard specification in 2030. June 2023, ITU-R Working Party (WP) 5D finalized the Framework Recommendation of IMT-20303 (a.k.a. 6G Vision, hereinafter 6G Framework). This will now undergo the approval process within the ITU, with the final publication within 2023. 
  •  3GPP is expected to submit 6G standard specifications to ITU that meet 6G technical performance requirements in 2028, and 6G commercialization is expected around 2030.
  • There is a rich roadmap of 5G technologies coming with 5G-Advanced
  • 6G will be the future of wireless innovation platform for 2030 and beyond
  • 6G will expand the role of communication, AI, sensing in the connected intelligent edge

Part 1.   Introduction

6G dimensions and fundamental analyses

Part 2.   Next-generation broadband connectivity:  Terabit/s goal

2D OTFS (Orthogonal Time Frequency Space) modulation in DD (Delay-Doppler) domain

3D channel standard model framework

Antenna holography and intelligent reflecting surface (IRS) placement 

Part 3   Integrated communication:  3D services

Part 3.   Hybrid intelligent networks:  AI empowered wireless networks

Driving technology evolution

Artificial intelligence (AI) is not only an interesting technology for improving accuracy and prediction on a variety of problems, but it is ultimately required to be used to extract intelligence from the enormous amount of data produced on modern-day networks.The development of 6G networks will be largescale, multi-layered, highly complex, dynamic, and heterogeneous.AI techniques with powerful analysis ability, learning ability, optimizing ability and intelligent recognition ability, which can be employed into 6G networks to intelligently carry out performance optimization, knowledge discovery, sophisticated learning, structure organization and complicated decision making.
  • Wireless network architecture evolution
  • Data demand driven by video
  • Device growth driven by IoT

B5G Recent advances and future challenges

5G wireless communication networks are currently being deployed, and B5G networks are expected to be developed over the next decade. AI technologies and, in particular, ML have the potential to efficiently solve the unstructured and seemingly intractable problems by involving large amounts of data that need to be dealt with in B5G.
  • AI algorithms and applications
  • AI/ML for B5G networks in standards and study groups

 The Roadmap to 6G

6G will go beyond mobile Internet and will be required to support ubiquitous AI services from the core to the end devices of the network. Meanwhile, AI will play a critical role in designing and optimizing 6G architectures, protocols, and operations. 
  • AI-enabled technologies for 6G
  • Network management and optimization
  • 6G for AI applications
Artificial intelligence is rapidly becoming integrated into many aspects of communication, applications, content, and commerce to greatly enhance user experience, significantly improve productivity, as well as create new and profitable business opportunities. 

PART 1.

6G Wireless channel measurements and models

For 5G and previous generations, it is preferred that the standardized channel models use a general channel model framework with different parameter sets for different scenarios. A general 3D nonstationary 5G channel model was proposed to cover the four challenging scenarios, i.e., massive MIMO, HST, V2V, and mm-wave. All of the channel models are concentrated on only terrestrial communication networks and frequencies up to mm-wave bands. However, 6G channels exist over the space–air–ground–sea integrated networks with frequencies of up to the optical wireless bands, which makes it more challenging to derive a general channel model framework. As 6G wireless channels become heterogeneous and show different scales over the wavelengths, how to describe 6G wireless channels with a general standard channel model framework is an open issue that needs careful investigations. 
Physical-layer design of a communication systems conventionally relies on channel models and extensive mathematical analysis. This approach led to well-established methods for modulation, channel estimation, equalization, code design, etc. However, such models typically fail to describe all the complexity of the actual communication medium. Moreover, approximations are made when designing communication algorithms for tractability. Such issues lead to suboptimal performance. During the last decade, machine learning has led to breakthroughs within the field of communications, recently unlocked significant gains in terms of throughput and reliability. The goal is to apply deep learning to develop enhancend physical layer transceiver algorithms for emerging modulations and waveforms as well as channel estimation and detection. Upper layer applications.  Through learning features from the big data generated by wireless network’s infrastructure and sensor devices, network configurations can be optimized, resulting in better network performance. AI aided network traffic, and performance prediction and control have been studied for cellular networks. ML techniques can help optimize and manage the mobile networks and reduce the operational costs by performance prediction.
Certain scenarios may require multiple use cases to be met simultaneously (uRLLC and mMTC) as shown in (a) with intersecting circles. Specifically, 6G network will further enhance Ultra-Mobile Broadband (feUMBB), ultra-High Sensing Low Latency Communications (uHSLLC), ultra-High Density Data (uHDD) services, ultra-High Energy Efciency (uHEE), ultra-High Reliability and Sensing (uHRS), ultra-High Reliability and User experience (uHRUx), ultra-Low Latency Reliability and Secure (uLLRS), ultra-High Security (uHS), ultra-High Sensing and Localization (uHSLo) and several other combinations of these Key Performance Indicators (KPIs) and use cases.

6G communication networks will be the first generation of networks with native AI. This means that AI will not merely be an application but an inherent part of the infrastructure, and of the network management and operations.