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.

当前从Wi-Fi到5G的无线系统是通过以下原理设计的，这些原理在过去70年中没有改变。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。随着计算系统用专门的电路代替人工智能（AI）的通用数字处理器，并且当无线连接成为AI供电的传感 - 计算输入织物的组成部分，因此，重新考虑基本原理是无线系统设计的基本原理。全球电信市场估计约为8500亿美元，英国电信行业在2020年产生了约300亿英镑。将领导新的技术原理和能力为6G的新技术和能力的国家将具有重要的国际市场优势，从而使对本学问题的基本研究成为重要的国家政策问题。在这种情况下，神经形态感测和计算正在作为替代性，脑力启发的，有效的数据收集和语义信号处理的范例，这些范例基于事件驱动的测量，内存计算，基于尖峰的信息处理，降低的精度和增加的精度和增加的随机性以及通过在硬件中进行学习。神经形态感测和计算市场在2020年的价值为2250万美元，预计到2026年，它的价值为3.336亿美元。当前的神经形态技术的商业用例从无人机监测到快速，准确的CovID-COVID-19抗体测试的开发。 Neurocomm认为神经形态技术的出现是开发高效，集成的无线连接性和语义处理的独特机会 - 广泛地称为无线认知。具体而言，神经通讯旨在系统地解决神经形态原理在端到端系统中的集成，包括感应，计算和无线通信。神经形态计算的信息货币不是位，而是尖峰的时间。长期以来，神经科学家已经研究了基于尖峰的传播在生物神经元中的效率和有效性。在无线认知的背景下，基于尖峰的处理和沟通引发了有关最佳关节信号传导和计算策略的新基本问题。 Neurocomm将采取从第一，信息理论，原则开始的方法，以解决如何在研究如何最佳部署基于神经形态的无线认知之前实施的问题。为此，该项目旨在开发一个信息理论框架，以分析具有神经术传感器的无线认知系统。神经形态计算的效率取决于硬件和软件的共同设计。 Neurocomm认为，将需要在设计阶段进行神经形态计算和通信的密切整合，以充分利用受脑启发的无线认知的好处。 Neurocomm是国王学院（KCL）担任首席机构与普林斯顿大学（PU）之间的合作，并与NVIDA，Intel Labs，Accelercomm和IBM Zurich一起担任学术合作伙伴。这项研究将基于PIS信息理论，机器学习，沟通和神经形态计算的专业知识，以探索理论基础，算法和硬件实施。这项研究是在NSF工程局 - 乌克里（Ukri）工程和物理科学和物理科学研究委员会领导机构领导机构（ENG-EPSRC）的NSF董事会下资助的。认为值得通过基金会的智力优点和更广泛影响的评论标准来评估值得支持。