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: 2335876
• 负责人: Harold Vincent Poor
• 金额: $ 40万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2335876&HistoricalAwards=false
• 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 specialized 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 to systematically address 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.This research was funded under the NSF Directorate for Engineering - UKRI Engineering and Physical Sciences Research Council Lead Agency Opportunity (ENG-EPSRC), NSF 20-510.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

当前的无线系统，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，并且随着无线连接成为人工智能驱动的传感-计算-驱动结构的一个组成部分，有必要重新思考支持无线设计的基本原则。系统。全球电信市场估计约为 8500 亿美元，其中英国电信业到 2020 年将创收约 300 亿英镑。在创造支撑 6G 的新技术原理和能力方面处于领先地位的国家将拥有显着的国际市场优势，将这一主题的基础研究作为一个重要的国家政策问题。在这种背景下，神经形态传感和计算正在成为高效数据收集和语义信号处理的替代、受大脑启发的范例，这些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、降低的精度和增加的随机性的基础上，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价值为 2250 万美元，预计到 2026 年将达到 3.336 亿美元。神经形态技术当前的商业用例包括从无人机监控到快速准确的 COVID-19 抗体的开发测试。 NeuroComm 将神经形态技术的出现视为开发高效、集成无线连接和语义处理（广泛称为无线认知）的独特机会。具体来说，NeuroComm 旨在系统地解决神经形态原理在涵盖传感、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，基于脉冲的处理和通信提出了有关最佳联合信号和计算策略的新的基本问题。 NeuroComm 将采取首先从信息理论原则开始的方法，在研究如何最好地部署基于神经形态的无线认知之前解决要实施什么的问题。为此，该项目旨在开发一个信息理论框架具有神经形态收发器的无线认知系统的分析。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，为了充分利用受大脑启发的无线认知的优势，需要在设计阶段将神经形态计算和通信紧密集成。 NeuroComm 是作为牵头机构的伦敦国王学院 (KCL) 与作为学术合作伙伴的普林斯顿大学 (PU) 以及作为工业合作伙伴的 NVIDA、英特尔实验室、AccelerComm 和 IBM Zurich 之间的合作。该研究将建立在 PI 在信息论、机器学习、通信和神经拟态计算方面的专业知识的基础上，探索理论基础、算法和硬件实现。这项研究由 NSF 工程理事会 - UKRI 工程和物理科学研究委员会资助牵头机构机会 (ENG-EPSRC)，NSF 20-510。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。