Collaborative Research: SWIFT: Dynamic Spectrum Sharing via Stochastic Optimization

下一代通信网络必须支持极其复杂的系统和具有挑战性的应用，如智能城市/家庭、智能制造、自动驾驶汽车以及虚拟和增强现实。这些新的应用程序应该在世界范围内更容易获得，并导致更广泛的统一，降低宽带成本，并减少数字鸿沟。与此同时，在对5G频谱需求不断增加的地区，雷达传感正变得越来越普遍。这些对频谱资源日益增长的需求要求采用智能频谱调度技术。与此同时，一些新技术，如可重构智能表面（RIS）和双功能无人机（uav），提供了额外的设计自由度。该项目开发了集成和优化这些新技术所需的通用数学框架，以实现共享频谱上的弹性共存。目前通信和雷达用户之间的频谱分配是由监管机构设计的，目的是在任何时候都避免用户之间的干扰。这种保守的方法不适合对吞吐量和双重通信和传感功能的需求不断增加，并且会导致容量减少。由于引入了额外的设计自由度以及与RIS模块和无人机等新技术的特性和动力学相关的相应约束，这种低效率进一步加剧。该项目开发了一种新的范例，其中频谱共享从硬确定性约束转移到具有期望的低有害干扰概率的随机方案。这可以利用随机规划的最新进展来得出弹性解决方案。在这种方法中，优化的约束是随机变量，必须以期望的高概率满足干扰极限给出的边界。这些随机约束可能是时变的，以解释动态环境中的不确定性。实现这一发展的关键组件是准确表征共存雷达和通信节点之间的相互干扰和性能权衡。他的项目开发了集成和优化这些新技术所需的通用数学框架，以实现共享频谱上的弹性共存。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The next generation of communication networks must support extremely complex systems and challenging applications such as smart city/home, smart manufacturing, autonomous vehicles, and virtual and augmented reality. These new applications should be more accessible worldwide and lead to wider harmonization, lower broadband costs, and reduce the digital divide. At the same time, radar sensing is becoming more pervasive in areas with increasing demands for the 5G spectrum. These ever-increasing demands on spectral resources require the use of intelligent spectrum scheduling techniques. Meanwhile, several new technologies like reconfigurable intelligent surface (RIS) and dual-function unmanned aerial vehicles (UAVs) provide additional design degrees of freedom. This project develops the general mathematical framework that is needed to integrate and optimize these new technologies for resilient coexistence over a shared spectrum. Current spectrum allocation between communication and radar users, designed by regulatory bodies, aims to avoid interference between users at all times. This conservative approach is not suited in the wake of increasing demand for throughput and dual communication and sensing functionality and results in a reduced capacity. This inefficiency is exacerbated by the introduction of additional design degrees of freedom and the corresponding constraints related to the characteristics and dynamics of new technologies like RIS modules and UAVs. This project develops a new paradigm in which spectrum sharing moves from hard deterministic constraints to stochastic schemes with a desired low probability of harmful interference. This enables leveraging recent advances in stochastic programming to derive resilient solutions. In this approach, the constraints of optimization are random variables that have to satisfy the bounds given by interference limits with a desired high probability. These stochastic constraints may be time-varying to account for uncertainty in the dynamic environment. A key component to enable this development is an accurate characterization of the mutual interference and performance tradeoffs among coexisting radar and communication nodes. his project develops the general mathematical framework that is needed to integrate and optimize these new technologies for resilient coexistence over a shared spectrum.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.