Entry, competition and regulation in cognitive radio scenarios: a simple game theory model

[EN] Spectrum management based on private commons is argued to be a realistic scenario for cognitive radio deployment within the current mobile market structure. A scenario is proposed where a secondary entrant operator leases spectrum from a primary incumbent operator. The secondary operator innovates incorporating cognitive radio technology, and it competes in quality of service and price against the primary operator in order to provide service to users. We aim to assess which benefit users get from the entry of secondary operators in the market. A game theory-based model for analyzing both the competition between operators and the subscription decision by users is proposed. We conclude that an entrant operator adopting an innovative technology is better off entering the market, and that a regulatory authority should intervene first allowing the entrant operator to enter the market and then setting a maximum amount of spectrum leased. This regulatory intervention is justified in terms of users utility and social welfare.This work was supported by Spanish government through project TIN2010-21378-C02-02.Guijarro Coloma, LA.; Pla, V.; Vidal Catalá, JR.; Martínez Bauset, J. (2012). Entry, competition and regulation in cognitive radio scenarios: a simple game theory model. Mathematical Problems in Engineering. 1-13. https://doi.org/10.1155/2012/620972S11

UNDERSTANDING WI-FI 2.0: FROM THE ECONOMICAL PERSPECTIVE OF WIRELESS SERVICE PROVIDERS

Wi-Fi 2.0 refers to Wi-Fi-like Internet access operating on whitespaces in the licensed spectrum using cognitive radio technology. Wi-Fi 2.0 is expected to provide better performance and larger coverage than today's Wi-Fi, thanks to the good propagation characteristics of the legacy spectrum such as TV bands. Wi-Fi 2.0 is modeled as a network consisting of an access point (called CR hotspot) and end-user terminals (CR devices) operated by a CR wireless service provider. In this article we focus on the economical perspective of Wi-Fi 2.0 and discuss various aspects in profit management of Wi-Fi 2.0 WSPs. In particular, we consider profit-maximizing optimal strategies in terms of customer admission/eviction control and inter-WSP market competition. We first show that Wi-Fi 2.0 operates on time-varying spectrum availability due to the ON-OFF channel usage of legacy users, and advocate the necessity of customer eviction control upon appearance of legacy users. We also identify two types of WSP-WSP market competition in leasing the limited spectrum resources from the licensees and in enticing end customers with a competitive price. Then we enumerate the key factors affecting the profit of collocated WSPs, such as channel leasing cost, service tariff, QoS provisioning, and coexistence with legacy services. By examining Wi-Fi 2.0 from an economic point of view, we show its commercial value in developing next-generation CR applications that benefit both legacy and CR users.close41

Market Mechanisms Towards Secondary Spectrum Usage

Widespread adoption of smartphones, tablets and other smart devices has resulted in mobile operators (MOs) making a transition from voice to data centric business model. As a consequence there has been an increase in demand for radio spectrum. Spectrum availability in the future can be a cause of concern, the main reason of which is being attributed to the traditional and inflexible approach towards spectrum management. Hence it is required to overhaul the existing spectrum management techniques and adopt those models which aim at higher spectrum utilization. As part of our research methodology we first perform a state-of-the-art review on secondary usage of radio spectrum. We observe that most research assumes a clean slate approach towards the emergence of secondary spectrum markets which are typically designed with an underlying assumption of participating actors being of homogeneous type. In contrast with above we take an evolutionary approach while designing market mechanisms towards heterogeneous secondary usage of spectrum. The evolution of trading markets is reflected in the incremental steps used in our research, i.e. starting from Wireless Fidelity (Wi-Fi IEEE 802.11) capacity markets, followed by super Wi-Fi (IEEE 802.11af) capacity markets and finally TV White Spaces (TVWS) spectrum leasing markets. We make use of Value Network Configuration (VNC) methodology for illustrating the design of market mechanism and further evaluate the designed mechanism using Agent Based Modeling (ABM). Based on our simulation results we observe that a generic trade-off exist between the length of lease time, trade facilitation cost and the extent of trading activity within the markets. We also observe that there exists an optimal range of lease time for which all the market players find themselves in economically favourable situation. We compare super Wi-Fi capacity markets and TVWS spectrum leasing markets over performance of MOs and TV broadcasters and according to our evaluation local area strategy seems to offer more benefits for TVWS spectrum usage

Efficient Identification and Utilization of Spectrum Opportunities in Cognitive Radio Networks.

There has been an exponential increase in spectrum demands due to new emerging wireless services and applications, making it harder to find unallocated spectrum bands for future usage. This potential resource scarcity is rooted at inefficient utilization of spectrum under static spectrum allocation. Therefore, a new concept of dynamic spectrum access (DSA) has been proposed to opportunistically utilize the legacy spectrum bands by cognitive radio (CR) users. Cognitive radio is a key technology for alleviating this inefficient spectrum utilization, since it can help discover spectrum opportunities (or whitespaces) in which legacy spectrum users do not temporarily use their assigned spectrum bands. In a DSA network, it is crucial to efficiently identify and utilize the whitespaces. We address this issue by considering spectrum sensing and resource allocation. Spectrum sensing is to discover spectrum opportunities and to protect the legacy users (or incumbents) against harmful interference from the CR users. In particular, sensing is an interaction between PHY and MAC layers where in the PHY-layer signal detection is performed, and in the MAC-layer spectrum sensing is scheduled and spectrum sensors are coordinated for collaborative sensing. Specifically, we propose an efficient MAC-layer sensing scheduling algorithm that discovers spectrum opportunities as much as possible for better quality-of-service (QoS), and as fast as possible for seamless service provisioning. In addition, we propose an optimal in-band spectrum sensing algorithm to protect incumbents by achieving the detectability requirements set by regulators (e.g., FCC) while incurring minimal sensing overhead. For better utilization of discovered spectrum opportunities, we pay our attention to resource allocation in the secondary spectrum market where legacy license holders temporarily lease their own spectrum to secondary wireless service providers (WSPs) for opportunistic spectrum access by CR users. In this setting, we investigate how a secondary WSP can maximize its profit by optimally controlling the admission and eviction of its customers (i.e., CR users). In addition, we also focus on the price and quality competition between co-located WSPs where they contend for enticing customers by providing more competitive service fee while leasing the channels with best matching quality.Ph.D.Electrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78741/1/hyoilkim_1.pd