NeTS: Small: End-User Behavior and Prospect Pricing in Wireless Data Networks

除了智能手机--发达国家的智能手机数量要多得多--世界上的手机数量正接近7B部，甚至造成了这样一种现实：在世界某些地区，有手机的人比在家里能用上电的人还多。机器对机器通信的出现增加了无线系统容量的压力。事实上，无论是产业界还是学术界都在认可和推动实现无线网络容量达到1000倍的目标。解决方案的范围从具有新频谱共享的频谱灵活的认知无线电，到使用更高频率的电磁频谱以及称为异质网络(HetNet)的更小和更密集的小区部署。虽然这是一项非常需要的活动，需要克服许多挑战，但提供HetNet所需的空间高密度无线/有线回程成本高昂，对无线容量的压倒性需求从根本上仍然存在，因为最先进的系统远未达到1000倍容量的目标，甚至可能还差一两个数量级。因此，无线服务提供商(SP)最近已求助于通过差异化和分级的货币定价来控制向最终用户提供的接入和服务。因此，当最终用户需要在高用户密度动态频谱设置中提供服务时，他们可能必须就可能提供给他们的数据速率和价格做出决定。提出了一种称为“前景定价”的补充方法，作为一种支持数据需求的方法，当技术解决方案本身无法满足无线数据的需求时，该方法依赖于使用动态定价算法来影响终端用户(人)的行为。研究议程试图从认知心理学的角度设计和研究无线网络定价，从而提出一个新的框架来理解无线网络如何受到最终用户行为的影响，反之亦然。这项研究的成功完成将为SP如何利用前景定价来管理不断增长的数据需求提供有用的指导。影响无线设备行为并从而推动系统更好地运行的监管机制已在无线电资源管理文献中得到了充分的阐述。这些机制本质上源于基于期望效用理论(EUT)的微观经济学方法，并通过工程系统设计实现，即将这些策略嵌入到由无线设备执行的链路层和网络层协议中。当服务提供商通过差异化和分级的货币定价控制对终端用户的访问时，网络的性能直接受到终端用户决策的影响，而最终用户的决策已经显示出与EUT背道而驰。前景理论是一种诺贝尔奖获得者理论，它解释了现实生活中的决策及其与EUT行为的偏差，被用于设计无线网络的“前景定价”。具体地说，无线数据的动态定价算法旨在使HetNet能够管理日益增长的数据需求，特别是在频谱和基础设施资源都有限的情况下。一个由无线网络/系统研究人员和认知心理学家组成的团队提出的研究议程结合了理论、算法开发和实验，包括：(1)利用博弈论开发无线网络前景定价框架，(2)评估HetNet中用于负载平衡和资源管理的前景定价性能，以及(3)心理物理实验，以了解最终用户对服务产品和无线网络性能的感知和偏好。该项目将把为无线网络使用体验开发的心理物理试验台作为开放资源提供。无线网络定价和认知心理学的独特结合提供了一个创新的教育机会，让电气、计算机工程和心理学的研究生和本科生参与进来。

Beyond smart phones, of which there are significantly more in developed countries, the number of mobile phones in the world is approaching 7B, even creating a reality that in some parts of the world, there are more people with access to a phone than with access to electricity at home. The advent of machine-to-machine communications adds increased pressure on wireless system capacity. In fact, there is a recognition and push in both industry and academia towards the goal of achieving "1000x" capacity for wireless. The solution approaches range from spectrally agile cognitive radios with novel spectrum sharing, to use of higher frequency electromagnetic spectrum as well as smaller and denser cell deployments referred to as heterogeneous networks (HetNets). While this is a much needed activity with many challenges to overcome, providing a spatially high density of wireless/wired backhaul as required for HetNets is expensive and the overwhelming demands on wireless capacity fundamentally remain, in that state-of-the-art systems are nowhere near the 1000x capacity target goals and perhaps even an order of magnitude or two away. Wireless service providers (SPs) in recent times have therefore resorted to control access and services being provided to end-users via differentiated and hierarchical monetary pricing. As such, end-users may have to make decisions on data rate and price offerings that may be presented to them when they need service in high user-density dynamic spectrum settings. A complementary approach termed "prospect pricing" is proposed as a way to support data demand and relies on influencing end-user (human) behavior using dynamic pricing algorithms when technological solutions by themselves cannot satisfy the demands of wireless data. The research agenda seeks to design and study wireless network pricing from a cognitive psychology perspective, thereby presenting a novel framework to understand how wireless networks can be influenced by end-user behavior and vice-versa. The successful completion of this research will serve up useful pointers to how prospect pricing can be used by the SPs to manage the ever increasing demand for data.Policing mechanisms that influence wireless device behavior and thereby drive systems to better operating points have been addressed amply in the radio resource management literature. These mechanisms essentially are borne out of expected utility theory (EUT) based microeconomics approaches, and implemented via engineered system design, i.e., embedding these strategies in the link layer and network layer protocols that are executed by wireless devices. When a SP controls access to end-users via differentiated and hierarchical monetary pricing, then the performance of the network is directly subject to end-user decision-making that has shown to deviate from EUT. Prospect Theory, a Nobel prize winning theory that explains real-life decision-making and its deviations from EUT behavior, is used to design "prospect pricing" for wireless networks. Specifically, dynamic pricing algorithms for wireless data are designed to enable HetNets to manage the ever increasing demand for data, especially when both spectrum and infrastructure resources are constrained. Using a mix of theory, algorithm development and experimentation, the research agenda proposed by a team comprised of a wireless networking/systems researcher and a cognitive psychologist includes: (1) Development of a Framework for Prospect Pricing in Wireless Networks using Game Theory, (2) Evaluation of the Performance of Prospect Pricing in HetNets for Load-Balancing and Resource Management, and (3) Psychophysics Experiments to understand End-User Perceptions and Preferences to Service Offers and Wireless Network Performance.The project will make available as an open resource the psychophysics testbed developed for wireless network usage experience. The unique marriage of wireless network pricing and cognitive psychology offers an innovative educational opportunity to involve both graduate and undergraduate students from electrical and computer engineering and psychology.