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.
|Effective start/end date||10/1/14 → 9/30/17|
- National Science Foundation (National Science Foundation (NSF))
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