Spectrum Access Games and Strategic Learning in Cognitive Radio Networks for Delay-Critical Applications
van der Schaar, M.; Fangwen Fu
Proceedings of the IEEE
Volume 97, Issue 4, April 2009 Page(s):720 - 740
Digital Object Identifier 10.1109/JPROC.2009.2013036
Summary:With the current proliferation of high bandwidth and delay-sensitive multimedia applications and services, each wireless user will try to maximize its utility by acquiring as much spectrum resources as possible unless a preemptive mechanism exists in the network. Thus, emerging solutions for dynamic spectrum access in cognitive radio networks will need to adopt market-based approaches in order to effectively regulate the available resources. In this paper, we show how various centralized and decentralized spectrum access markets can be designed based on a stochastic game framework, where wireless users (also referred to as secondary users) can compete over time for the dynamically available transmission opportunities (spectrum ldquoholesrdquo). When operating in such spectrum access ldquomarkets,rdquo wireless users become selfish, autonomous agents that strategically interact in order to acquire the necessary spectrum opportunities. We also show how wireless users can successfully compete with each other for the limited and time-varying spectrum opportunities, given the experienced dynamics in the wireless network, by optimizing both their external actions (e.g., the resource bids, power and channel used for transmission, etc.) and their internal actions (e.g., the modulation schemes, etc.). To determine their optimal actions in an informationally decentralized setting, users will need to learn and model directly or indirectly the other users' responses to their external actions. We studied the outcome of various dynamic interactions among self-interested wireless users possessing different knowledge and determine that the proposed framework can lead to multiuser communication systems that achieve new measures of efficiency, rationality and fairness. Lastly, our illustrative results show that the presented game-theoretic solution for wireless resource management enables users deploying enhanced (ldquosmarterrdquo) learning and communication algorithms and being ab-
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le to make efficient use of the spectrum resources can derive higher utilities. This presents the designers of wireless devices and systems with important incentives to endow their next-generation products and services with enhanced capabilities to gather information, learn, and strategically compete for resources in the emerging spectrum resource markets made possible by the cognitive radio network technologies.
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