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

目前的无线系统，从Wi-Fi到5G，都是按照过去70年没有改变的原则设计的。这种方法为我们提供了可靠的、通用的无线连接解决方案，可以传输任何类型的数字信息。随着计算系统用专门的电路取代通用数字处理器来取代人工智能(AI)，随着无线连接成为人工智能驱动的传感-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是至关重要的。据估计，全球电信市场规模约为8500亿美元，其中英国电信业2020年的收入约为300亿英镑。将引领创造支撑6G的新技术原则和能力的国家将拥有显著的国际市场优势，使对该主题的基础研究成为关键的国家政策问题。在这种背景下，神经形态传感和计算正在成为另一种受大脑启发的有效数据收集和语义信号处理的范例，其基础是事件驱动的测量、记忆中的计算、基于脉冲的信息处理、降低的精确度和增加的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用例包括从无人机监控到开发快速准确的新冠肺炎抗体检测。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的独特机会--广义上指的是无线认知。具体地说，NeuroComm的目标是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流通不是比特，而是尖峰的时间。神经学家长期以来一直在研究生物神经元中基于棘波的交流的效率和有效性。在无线认知的背景下，基于脉冲的处理和通信提出了关于最优联合信令和计算策略的新的基本问题。NeuroComm将采取首先从信息论原则出发的方法，解决在研究如何最好地部署基于神经形态的无线认知之前实现什么的问题。为此，该项目旨在开发一个信息论框架，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共同设计。NeuroComm认为，为了充分利用大脑启发的无线认知的好处，在设计阶段需要将神经形态计算和通信紧密结合起来。NeuroComm是伦敦国王学院(KCL)作为牵头机构，普林斯顿大学(PU)作为学术合作伙伴，以及NVIDA、英特尔实验室、AccelerComm和IBM苏黎世作为行业合作伙伴之间的合作。这项研究将建立在PI在信息论、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。这项研究由NSF工程局-UKRI工程和物理科学研究理事会牵头机构机会(ENG-EPSRC)资助，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势和更广泛的影响审查标准进行评估，被认为值得支持。

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.