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

这个本科生研究体验(REU)网站将为每年夏天的8名本科生(3年内24名学生)提供支持，让他们在一支经验丰富的教师和高级研究生研究人员团队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。远距离短波通信允许在不需要卫星的情况下进行数千公里的无线通信，对于军事和政府、航空、空对地通信、海事服务、公共安全和民用遇险通信、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网站将在这个激动人心的领域为参与的学生提供高质量、身临其境的实践学习体验。参与者将接受培训，为研究生院和专业发展做准备，并将指导他们成为独立的创造性思考者和研究人员。与会者将获得科学传播和通信方面的经验，包括在专业会议和期刊上发表文章，以及进行科学演讲。通过大气层电离层反射无线电波进行远程短波通信工作。这些通信可以绕地球的曲率传播，无需卫星、蜂窝网络、互联网等重要基础设施即可工作。短波通信面临的挑战是，通过电离层的传播可能不可靠，电离层条件可能变化非常迅速，不同的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，使长距离短波通信更加可靠和高效。具体地说，这个项目将研究和开发：(I)用于高频通信的频谱捷变无线电的新设计，它可以切换通信参数，如调制、编码、脉冲形状、均衡器、功率等；(Ii)机器学习算法，可以学习改变信道条件的最佳通信参数；(Iii)可用于短波通信的低轮廓天线；(Iv)预测可能的网络级连接的软件和算法；(V)定性和定量的电离层通信模型；(Vi)灵活和自动的天线调谐电路；和(Vii)智能算法，可以学习他们在不同电离层条件、天气情况、时间和地点方面的过去经验。这一奖项反映了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。

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.