ECCS-EPSRC: NeuroComm: Brain-Inspired Wireless Communications -- From Theoretical Foundations to Implementation for 6G and Beyond

ECCS-EPSRC：NeuroComm：受大脑启发的无线通信——从理论基础到 6G 及更高版本的实施

• 批准号: EP/X011852/1
• 负责人: Osvaldo Simeone
• 金额: $ 126.16万
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX011852%2F1
• 关键词: ECCS; EPSRC; NeuroComm; Brain; Inspired

Current wireless systems, from Wi-Fi to 5G, have been designed by following principles that have not changed over the last 70 years. This approach has given us dependable, universal wireless connectivity solutions that can deliver any type of digital information. As computing systems substitute universal digital processors with specialised circuits for artificial intelligence (AI), and as wireless connectivity becomes an integral part of the sensing-compute-actuation fabric powered by AI, it is essential to rethink the fundamental principles underpinning the design of wireless systems. The global telecom market is estimated at around USD 850 billion, with the UK telecom industry generating around GBP 30 billion in 2020. The countries that will lead in the creation of the new technological principles and capabilities underpinning 6G will have a significant international market edge, making fundamental research on the subject a critical national policy issue. In this context, neuromorphic sensing and computing are emerging as alternative, brain-inspired, paradigms for efficient data collection and semantic signal processing that build on event-driven measurements, in-memory computing, spike-based information processing, reduced precision and increased stochasticity, and adaptability via learning in hardware. The neuromorphic sensing and computing market was valued at USD 22.5 million in 2020, and it is projected to be worth USD 333.6 million by 2026. Current commercial use cases of neuromorphic technologies range from drone monitoring to the development of fast and accurate COVID-19 antibody testing. NeuroComm views the emergence of neuromorphic technologies as a unique opportunity for the development of efficient, integrated wireless connectivity and semantic processing -- referred to broadly as wireless cognition. Specifically, NeuroComm aims systematically addressing the integration of neuromorphic principles within an end-to-end system encompassing sensing, computing, and wireless communications.The informational currency of neuromorphic computing is not the bit, but the timing of spikes. Neuroscientists have long studied the efficiency and effectiveness of spike-based communications in biological neurons. In the context of wireless cognition, spike-based processing and communication raise novel fundamental questions regarding optimal joint signaling and computing strategies. NeuroComm will take the approach of starting from first, information-theoretic, principles, addressing the problem of what to implement before investigating how to best deploy neuromorphic based wireless cognition. To this end, the project aims at developing an information-theoretic framework for the analysis of wireless cognition systems with neuromorphic transceivers. The efficiency of neuromorphic computing hinges on the co-design of hardware and software. NeuroComm posits that a close integration of neuromorphic computing and communications at the design stage will be needed in order to fully leverage the benefits of brain-inspired wireless cognition. NeuroComm is a collaboration between King's College London (KCL) as lead institution and Princeton University (PU) as academic partner, along with NVIDA, Intel Labs, AccelerComm, and IBM Zurich as industrial partners. The research will build on the PIs' expertise in information theory, machine learning, communications, and neuromorphic computing to explore theoretical foundations, algorithms, and hardware implementation.

目前的无线系统，从Wi-Fi到5G，都是按照过去70年来没有改变的原则设计的。这种方法为我们提供了可靠的通用无线连接解决方案，可以提供任何类型的数字信息。随着计算系统用人工智能（AI）专用电路取代通用数字处理器，以及无线连接成为由AI驱动的传感-计算-驱动结构的组成部分，重新思考支撑无线系统设计的基本原则至关重要。全球电信市场估计约为8500亿美元，英国电信业在2020年的收入约为300亿英镑。在创建6 G新技术原则和能力方面处于领先地位的国家将拥有显著的国际市场优势，使该主题的基础研究成为关键的国家政策问题。在这种情况下，神经形态感测和计算正在成为替代的，大脑启发的，有效的数据收集和语义信号处理的范例，建立在事件驱动的测量，内存计算，基于尖峰的信息处理，降低精度和增加随机性，以及通过硬件学习的适应性。2020年，神经形态传感和计算市场的价值为2250万美元，预计到2026年将达到3.336亿美元。目前，神经形态技术的商业应用范围从无人机监测到快速准确的COVID-19抗体检测。NeuroComm将神经形态技术的出现视为开发高效、集成的无线连接和语义处理（广义上称为无线认知）的独特机会。具体来说，NeuroComm旨在系统地解决神经形态原理在包括传感、计算和无线通信的端到端系统中的集成。神经形态计算的信息货币不是比特，而是尖峰的时间。神经科学家长期以来一直在研究生物神经元中基于尖峰的通信的效率和有效性。在无线认知的背景下，基于尖峰的处理和通信提出了关于最佳联合信令和计算策略的新的基本问题。NeuroComm将采取从第一，信息理论，原则开始的方法，解决在调查如何最好地部署基于神经形态的无线认知之前实施什么的问题。为此，该项目旨在开发一个信息理论框架，用于分析具有神经形态收发器的无线认知系统。神经形态计算的效率取决于硬件和软件的协同设计。NeuroComm认为，为了充分利用大脑启发的无线认知的好处，需要在设计阶段将神经形态计算和通信紧密集成。NeuroComm是伦敦国王学院（KCL）作为领导机构和普林斯顿大学（PU）作为学术合作伙伴，沿着NVIDA，英特尔实验室，加速器和IBM苏黎世作为工业合作伙伴的合作。该研究将建立在PI在信息理论，机器学习，通信和神经形态计算方面的专业知识基础上，以探索理论基础，算法和硬件实现。