REU Site: Undergraduate Research Experiences in Long Range Communications with Ham Radios, Cool Algorithms, and Innovative Antennas

这个本科生研究经验（REU）站点每年夏天将为8名本科生（24名学生，3年以上）提供支持，在经验丰富的教师和高级研究生研究人员的指导下，获得与高频（HF）远程无线通信相关主题的研究经验。远程高频通信可以实现数千公里的无线通信，而不需要卫星，对军事和政府、航空、空对地通信、海事服务、公共安全和公务遇险通信、空间和卫星业务、气象站、调频和电视广播以及许多其他通信需求具有不可估量的重要性。这个REU网站将在这个令人兴奋的领域为参与的学生提供高质量的、身临其境的和动手的学习体验。参与者将接受指导，为研究生院和专业发展做准备，他们将被指导成为独立的创造性思想家和研究人员。与会者将获得科学传播和交流方面的经验，包括在专业会议和期刊上发表文章，以及发表科学报告。远距离高频通信是通过大气层电离层反射无线电波来工作的。这些通信可以绕着地球的曲率传播，并且不需要卫星、蜂窝网络、互联网等重要基础设施。高频通信面临的挑战是，通过电离层传播可能不可靠，电离层条件可能变化非常快，不同频率通过电离层具有不同的传播特性。成功的通信取决于一天中的时间、用户的位置、频率的选择、调制、天线类型和功率水平。该项目将为关键问题提供新的解决方案，从而实现更可靠和高效的远程高频通信。具体而言，该项目将研究和开发：(i)用于高频通信的频谱敏捷无线电的新设计，可以切换通信参数，如调制，编码，脉冲形状，均衡器，功率等；（ii）能够根据不断变化的信道条件学习最佳通信参数的机器学习算法；可用于高频通信的低轮廓天线；提前预测可能出现的网络级连接的软件和算法；定性和定量电离层通信模式；灵活和自动天线调谐电路；（vii）智能算法，可以从过去在不同电离层条件、天气情况、时间和地点的经验中学习。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。

This Research Experiences for Undergraduates (REU) Site will provide support for eight undergraduate students each summer (24 students over 3 years) to gain research experience under the mentorship of a team of experienced faculty and advanced graduate student researchers in topics related to high frequency (HF) long range wireless communications. Long range HF communications allow wireless communication over thousands of kilometers without the need for satellites, and are of immeasurable importance to military and government, aviation, air-to-ground communications, maritime services, public safety and civil service distress communications, space and satellite operations, weather stations, FM and TV broad casting, and many other communication needs. This REU site will provide participating students a high quality, immersive, and hands-on learning experience in this exciting area. Participants will receive coaching to prepare for graduate school and professional development, and they will be mentored into becoming independent creative thinkers and researchers. Participants will gain experience in scientific dissemination and communication, including publishing in professional conferences and journals, and giving scientific presentations.Long range HF communications work by the reflection of radio waves by the ionosphere layer of the atmosphere. These communications can travel around curvature of the earth, and work without the need for significant infrastructure like satellites, cellular networks, internet, etc. The challenge with HF communications is that propagation via the ionosphere may be unreliable, the ionospheric conditions may change very rapidly, and different frequencies have different propagation characteristics via the ionosphere. Successful communication depends on the time of day, location of users, selection of frequency, modulation, antenna type, and power level. This project will generate new solutions to key problems that will enable more dependable and efficient long range HF communications. Specifically this project will investigate and develop: (i) New designs for spectrum agile radios for high frequency communications that can switch communication parameters such as modulation, coding, pulse shape, equalizer, power, etc.; (ii) Machine learning algorithms that can learn the best communication parameters for changing channel conditions; (iii) Low profile antennas that can be used in HF communications; (iv) Software and algorithms to predict network level connections that are possible ahead of time; (v) Qualitative and quantitative Ionospheric communications models; (vi) Flexible and automatic antenna tuning circuits; and (vii) Smart algorithms that can learn from their past experiences in varying Ionospheric conditions, weather situations, time and location.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.