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）之外，世界上移动的手机数量正在接近70亿部，甚至在世界某些地区，拥有手机的人比家里有电的人还要多。机器对机器通信的出现增加了对无线系统容量的压力。事实上，工业界和学术界都认识到并推动实现无线“1000倍”容量的目标。解决方案的范围从具有新型频谱共享的频谱敏捷认知无线电，到使用更高频率的电磁频谱以及称为异构网络（HetNet）的更小和更密集的小区部署。虽然这是非常需要的活动，需要克服许多挑战，但是提供HetNet所需的空间高密度的无线/有线回程是昂贵的，并且对无线容量的压倒性需求基本上仍然存在，因为最先进的系统远未接近1000倍容量目标，甚至可能是一两个数量级。因此，近来无线服务提供商（SP）已经采取了经由有区别的和分级的货币定价来控制提供给终端用户的接入和服务。因此，终端用户可能必须在他们需要高用户密度动态频谱设置中的服务时对可能呈现给他们的数据速率和价格供应做出决定。被称为“前景定价”的补充方法被提出作为支持数据需求的方式，并且当技术解决方案本身不能满足无线数据的需求时，依赖于使用动态定价算法来影响最终用户（人）行为。研究议程旨在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提供了有用的指针，如何前景定价可以使用的SP管理不断增长的需求data.Policing机制，影响无线设备的行为，从而驱动系统更好的工作点已经在无线电资源管理文献中充分解决。这些机制基本上是基于预期效用理论（EUT）的微观经济学方法，并通过工程系统设计来实现，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SP通过差异化和分级货币定价来控制对最终用户的访问时，网络的性能直接受制于最终用户的决策，而最终用户的决策已显示出偏离EUT。前景理论是一种获得诺贝尔奖的理论，它解释了现实生活中的决策及其与EUT行为的偏差，用于设计无线网络的“前景定价”。具体而言，无线数据的动态定价算法旨在使HetNet能够管理不断增长的数据需求，特别是当频谱和基础设施资源都受到限制时。 使用理论，算法开发和实验的混合，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包括：（1）使用博弈论开发用于无线网络中的前景定价的框架，（2）用于负载平衡和资源管理的HetNet中的前景定价的性能的评估，及（3）心理物理学实验，以了解最终用户对服务提供和无线网络性能的感知和偏好。该项目将以开放资源形式提供为无线网络使用体验而开发的心理物理学测试平台。无线网络定价和认知心理学的独特婚姻提供了一个创新的教育机会，涉及电气和计算机工程和心理学的研究生和本科生。

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.