Enabling multi-service radio access networks with Massive MIMO

无线连接目前被认为是一种事实上的能力，使人和机器能够通信。这种无线接入网络（RAN）支持的应用范围包括语音和视频通话、内容流服务、银行、云数据存储、导航等等。据Ofcom称，为此类应用提供连接的蜂窝网络所承载的数据量每年增长约40%，这意味着数据流量大约每两年翻一番。工业界和学术界的研究和开发工作一直集中在能够满足这种不断增长的容量需求的技术上，在数字信号处理、计算机科学、光传输、电路和天线技术方面提供创新。频谱效率，即无线电信道中可以携带的信息量，一直是这种跨学科努力的关键焦点，因为无线电频谱是一种稀缺资源，必须有效利用。主动天线系统（AAS，也称为大规模MIMO）是最新一代移动网络基站技术，通过结合多学科的创新和经验，提高了频谱效率。AAS已经作为全球5G网络部署的一部分推出，并将继续在未来几代移动网络中发挥关键作用。然而，为了使对移动网络的投资可行，需要更多的服务能够有效地使用移动网络，这就要求支持在同一蜂窝基础设施上同时提供多种服务。AAS并发交付多个服务的实际潜力是原始FLF的重点。近年来，可持续发展已成为一个关键主题，旨在大量减少碳排放，以帮助扭转工业化对气候的负面影响。在移动网络中，这导致能源效率（EE）成为关键的设计目标。仅英国电信网络就消耗了英国总能耗的0.8%，因此找到应对这一挑战的短期和长期解决方案至关重要。RAN面临的具体挑战是尽量减少电力消耗，同时满足对各种连接服务日益增长的需求。该项目将重点关注对实际移动网络的雄心勃勃的增强。新的合作伙伴关系的目的是提高移动网络提供的各种连接服务的实际EE -从传统的通过无线接口传输比特到提供非数据承载服务（如定位）。为了实现这一目标，该项目将为当前移动网络中的数据和服务提供建立实用的EE基准，然后评估和开发短期和长期改善EE的方法。具体而言，发射机静音、将基站发送到不同的睡眠状态等技术将被视为短期可用的参考能力，而利用人工智能定制传输技术和使用节能波形将被视为旨在发展6G空中接口的长期研究目标。该项目的应用和收益将包括在实际操作条件和限制条件下通过关键技术选择获得的能效基准。这将有助于对可持续RAN的潜在贡献进行现实评估，并有助于为5G和6G RAN设计ee原生通信和网络部署策略。

Wireless connectivity is currently considered a de-facto capability, enabling people and machines to communicate. Range of applications supported by such Radio Access Networks (RAN) ranges from voice and video calling, content streaming services, banking, cloud data storage, navigation and many more. The volume of data carried by cellular networks delivering the connectivity for such applications grows approximately by 40% every year, which means the data traffic approximately doubles every two years, according to Ofcom. Research and development effort within industry and academia has been focussed on technologies capable of meeting this growing demand for capacity, delivering innovations in digital signal processing, computer science, optical transmission, circuitry, and antenna technology. Spectral efficiency, which is the amount of information that can be carried in a radio channel, has been the key focus for such inter-disciplinary effort since radio spectrum is a scarce resource and has to be used efficiently. Active Antenna Systems (AAS, also referred to as Massive MIMO) is the latest generation of base station technology for mobile networks delivering increased spectral efficiency by combining innovations and experience from multiple disciplines. AAS are already being rolled out as part of 5G network deployments globally and will continue to play a key role in future generations of mobile networks. However, in order for investment in mobile networks to be viable, more services need to be able to use mobile network efficiently, calling for support for multiple services to be concurrently delivered over the same cellular infrastructure. Practical potential of AAS to concurrently deliver multiple services is the focus of the original FLF.Sustainability has emerged as a key theme in recent years with a view to reduce carbon emissions by a substantial amount to help reverse the negative impact of industrialisation on the climate. In mobile networks this has resulted in energy efficiency (EE) becoming a key design objective. With 0.8% of the overall UK energy consumption falling on BT network alone, finding both short and long-term solutions to this challenge is of critical importance. The specific challenge for RAN is to minimise the consumption of electrical power while also meeting increasing demand for diverse connectivity services.This project will focus on ambitious enhancements to practical mobile network. The aim of the renewed fellowship is to increase the practical EE of diverse connectivity services provided by mobile networks - from traditional delivery of bits over the wireless interface, to provision of non-data bearing services such as positioning. To achieve this goal, the project will establish practical EE benchmarks for data and service provision in current mobile networks, and then assess and develop approaches to improve the EE, both in short and long term. Specifically, technologies such as muting of transmitters, sending base stations to varying states of sleep will be considered as reference capabilities available in short term, while the use of AI to tailor transmission technology and the use of energy-efficient waveforms with be considered as longer-term research objective aiming the development of 6G air interface.Applications and benefits from this project will include benchmarks for EE gains from key technology choices under practical operating conditions and constraints. This will enable a realistic assessment of potential contribution to sustainable RAN, and also help design EE-native communication and network deployment strategies for 5G and 6G RAN.