EARS: Photonically-Enabled Extremely Wideband Compressive Wireless Spectrum Sensing

摘要标题：EAR：光子支持的极宽带压缩无线频谱传感机构：约翰·霍普金斯大学摘要：非技术无线电频谱在无线通信和传感中的多种用途，无线电频谱是一种高度管制和有限的资源。目前，无线电频谱是严格和静态分配的，现代电子系统越来越依赖高带宽无线通信来进行互联网连接和设备间通信。尽管无线电频谱被严格分配，但调查表明，在任何位置和时间的使用通常是稀疏的，只有有限数量的活动信道，分散在非常广泛的频谱范围内。这一观察表明，能够有效和快速地感知频谱使用的无线电系统可以适应于利用这些临时频谱机会，从而更有效地利用有限的无线电频谱资源。这种系统的关键技术是宽带频谱感知，这项技术必须用最少的硬件资源快速实现。该计划将为微波毫米波频段开发一种极其宽带、紧凑和强大的频谱传感系统，以促进未来移动电子系统中高效的高带宽通信和高分辨率传感。该计划还将为本科生和高中生提供研究机会，开发教育工具，例如交互式在线教学应用程序，并促进外展活动，例如通过约翰·霍普金斯大学女性科学与工程(WISE)和巴尔的摩小学STEM成就(SABES)计划，这些计划针对STEM领域中代表性不足的群体。最近，压缩传感(CS)框架作为一种有前途的方法出现，它可以有效地捕获某些领域中稀疏的信号，测量明显少于传统所需的测量，从而实现更快、更简单和/或更低的功率传感。由于宽带频谱在任何给定的时空位置都未得到充分利用，因此其固有的稀疏性。因此，CS成为实现有效的低成本宽带频谱感知的一种很有前途的候选方案。认知无线电在微波和毫米波中所需的超宽带频谱感知将需要光子解决方案，因为瞬时带宽(可能为300 GHz)对于传统的电子采样硬件来说太大了，频谱机会太短暂了。这项研究计划将展示一种新的压缩光子采样方法，该方法通过在光子域中执行大部分信号处理来解决这些缺点。更具体地说，该计划将结合高速集成光子学和最近开发的光学域压缩传感的优点，开发一种极宽带芯片规模的频谱传感架构。通过将这些技术进步与为该硬件的独特能力量身定做的算法进步相结合，将证明一种极宽带频谱感知系统将在无线频谱的微波和毫米波范围内促进认知无线电系统的发展。这种架构允许极快地收集压缩传感测量结果，并将开发压缩传感理论和算法以利用这一独特的能力。为了解决未来无线电子设备所期望的高信息容量和高效的频谱利用，迫切需要这样的系统。

Abstract Title: EARS: Photonically-Enabled Extremely Wideband Compressive Wireless Spectrum SensingInstitution: Johns Hopkins UniversityAbstract:NontechnicalWith its multitude of uses in wireless communications and sensing, the radio spectrum is a highly regulated and finite resource. At present the radio spectrum is tightly and statically allocated and modern electronic systems are increasingly relying on high-bandwidth wireless communications for internet connectivity as well as inter-device communications. While the radio spectrum is tightly allocated, investigations indicate that the usage at any location and time is generally sparse with a limited number of active channels, scattered across an extremely broad spectral range. This observation indicates that a radio system that can efficiently and rapidly sense spectral usage could adapt to exploit these temporary spectral opportunities and thus make more efficient use of the finite radio spectrum resource. The key technology for such a system is wideband spectrum sensing and this technology must be implemented rapidly with minimal hardware resources. This program will develop an extremely wideband, compact, and robust spectrum sensing system for the microwave through millimeter-wave frequency bands to facilitate efficient high-bandwidth communications and high-resolution sensing in future mobile electronic systems. This program will also provide research opportunities for undergraduate and high-school students as well as develop educational tools, for example interactive on-line teaching applications, and facilitate outreach activities, for example through the Johns Hopkins University Women in Science and Engineering (WISE) and STEM Achievement in Baltimore Elementary Schools (SABES) programs, that target underrepresented groups in the STEM fields.TechnicalRecently, the framework of compressive sensing (CS) emerged as a promising method to efficiently capture signals that are sparse in some domain with significantly fewer measurements than would be traditionally necessary permitting faster, simpler, and/or lower power sensing. The wideband spectrum is inherently sparse due to its spectrum under-utilization at any given spatiotemporal location. Hence, CS emerges as a promising candidate to realize effective low-cost wideband spectrum sensing. The extremely wideband spectrum sensing necessary for cognitive radios in the microwave and mm-wave will necessitate photonic solutions, since the instantaneous bandwidths (potentially 300 GHz) are simply too large and spectral opportunities too short lived for traditional electronic sampling hardware. This research program will demonstrate a new approach for compressive photonic sampling that addresses these shortcomings by performing much of the signal processing in the photonic domain. More specifically, this program will develop an extremely wideband chip-scale spectrum sensing architecture by combining the benefits of high-speed integrated photonics with recently developed photonic-domain compressive sensing. Through the union of these technological advancements with algorithmic advancements tailored to the unique capabilities of this hardware, an extremely wideband spectrum sensing system will be proven to facilitate cognitive radio systems in the microwave and mm-wave ranges of the wireless spectrum. This architecture allows for extremely rapid collection of compressive sensing measurements and compressive sensing theory and algorithms will be developed to take advantage of this unique capability. Such a system is greatly needed to address the high information capacity and efficient spectral usage expected by future wireless electronic devices.