CAREER: Predicting the Development of Decentralized Communication Systems

该项目将结合关于基础设施发展和创新传播的社会科学研究，基于人为因素生成无许可频谱使用的预测性空间模型。无线技术的进步和“Wi-Fi”(IEEE 802.11a/b/g)无线数据网络目前的市场成功相结合，使许多人相信未经许可的频谱-不需要传输许可的频谱-现在是管理更大数量的无线通信的可行方法。然而，根据定义，使用未经许可的频谱是计划外的和分散的。文献将这种情况描述为“混乱”和不可预测，并警告说，频谱的零价格将很快导致拥塞失败。这个项目假设未经许可的频谱是非常可预测的，并且很有可能是可行的。到目前为止，频谱规划的方法很少考虑人为因素。例如，人口密度经常被考虑，但只是以一种简单化的方式。假设断言，城市的频谱更有可能是“满的”，而农村地区的频谱更有可能是“空的”。然而，许多高密度地区的人口是经济困难的人，他们可能不太可能使用Wi-Fi这样的技术。这项研究将努力实现准确的空间预测，其中包括几个人的因素的综合考虑，这些因素不仅仅是社会经济状况的问题。该项目将收集和绘制美国中西部选定人口普查区域的无线互联网使用情况，并将这些数据与美国人口普查的人口统计数据相结合。虽然创新扩散的文献很发达，但对扩散的空间分析更少见，有可能改变我们对新技术扩散的想法。此外，该项目将为社会科学开发无线测绘方法，这是一种很有前途的新方法。最重要的是，这项研究将根据重要的新技术和制度安排(如未经许可的频谱)重新考虑通信基础设施发展的理论，同时特别建立对无线数据网络的科学理解。未经许可是否是管理频谱的可行手段目前是这项研究可以解决的紧迫政策问题。此外，应该能够预测使用中的“漏洞”，为在普及领域制定创新政策提供基础。例如，这些发现可能表明经济不景气地区的地理范围地役权(而不是目前认为优先考虑空地的想法)。经验数据还将回答有关低功率未经许可的发射机的普遍程度以及它们彼此之间的距离等实际问题。该项目的综合教学部分促进了一种新的学生类型，他们拥有跨越工程、通信和政策的多学科专业知识。将教授一门新的基于项目的课程，教学生收集无线数据。作为一项服务项目，该课程将连续几年开发一个示范互联网“地图服务器”，允许人们通过输入他们的地址来可视化、测试和完善频谱使用的预测，从而促进公众对科学和技术的了解。

This project will combine social scientific research on infrastructure development and the diffusion of innovations to generate a predictive spatial model of unlicensed spectrum use based on human factors. Advances in wireless technology and the present market success of "Wi-Fi" (IEEE 802.11a/b/g) wireless data networking have combined to convince many that unlicensed spectrum - spectrum that does not require permission to transmit - is now a viable way to manage a much larger amount of our wireless communication. By definition, however, use of unlicensed spectrum is unplanned and decentralized. The literature has characterized this as "chaotic" and unpredictable, and has warned that a zero price for spectrum will quickly lead to congestion failure. This project hypothesizes that unlicensed spectrum is very predictable and likely viable.Approaches to spectrum planning so far have considered few human factors. For instance, population density is often considered, but only in a simplistic manner. Hypotheses assert that spectrum in cities is more likely to be "full," and that in rural areas it is more likely to be "empty." However, many high-density areas are populated by economically disadvantaged people who may be unlikely to use a technology like Wi-Fi. This research will strive for accurate spatial predictions that include the consideration of a complex of several human factors that are not simply a matter of socioeconomic status.This project will gather and map wireless Internet use in selected census tracts in the Midwestern US and combine these data with demographics from the US Census. While the diffusion of innovations literature is well-developed, spatial analysis of diffusion is rarer and has the potential to transform our thinking about diffusion of new technologies. In addition, the project will develop the methodology of wireless mapping for social science, a promising new approach. Most significantly, the research will reconsider theories of communication infrastructure development in the light of important new technology and institutional arrangements, such as unlicensed spectrum, while building the scientific understanding of wireless data networking specifically.Whether unlicensed is a viable means for managing the spectrum is currently a pressing policy question this research can address. In addition, it should be possible to predict "holes" in use that provide the basis for innovative policymaking in the area of universal access. For example, the findings might suggest geographic spectrum easements in economically depressed areas (rather than the current thinking that privileges empty areas). The empirical data would also answer practical questions on such issues as how prevalent low-powered unlicensed transmitters are and how close they are to each other. The integrated teaching component of this project promotes a new kind of student with multidisciplinary expertise across engineering, communication, and policy. A new project-based course will be taught to teach students to collect the wireless data. As a service project successive years of the course will develop a demonstration Internet "mapserver" that allows people to visualize, test and refine predictions of spectrum use by entering their addresses, thereby promoting public understanding of science and technology.