Optimal Pricing Strategies in Cognitive Radio Networks With Heterogeneous Secondary Users and Retrials

Abstract

In a cognitive radio (CR) system, excessive access services for secondary users (SUs) lead to a substantial increase in congestion and the retrial phenomenon, both of which degrade the performance of CR networks, especially in overload conditions. This paper investigates the price-based spectrum access control policy that characterizes the network operator's provision to heterogeneous and delay-sensitive SUs through pricing strategies. Based on shared-use dynamic spectrum access (DSA), the SUs can occupy the dedicated spectrum without degrading the operations of primary users (PUs). The service to transmission of SUs can be interrupted by an arriving PU, while the interrupted SUs join a retrial pool called an orbit, later trying to use the spectrum to complete the service. In the retrial orbit, the interrupted SU competes fairly with other SUs in the orbit. Such a DSA mechanism is formulated as a retrial queue with service interruptions and general service times. Regarding the heterogeneity of delay-sensitive SUs, we consider two cases: the delay-sensitive parameter follows a discrete distribution and a continuous distribution, respectively. In equilibrium, we find that the revenue-optimal price is unique, while there may exist a continuum of equilibria for the socially optimal price. In addition, the socially optimal price is always not greater than the revenue-optimal price, and thus the socially optimal arrival rate is not less than the revenue-optimal one, which is contrary with the conclusion, i.e., the socially optimal and revenue-optimal arrival rates are consistent, drawn in the literature for homogeneous SUs. Finally, we present numerical examples to show the effect of various parameters on the operator's pricing strategies and SUs' behavior. INDEX TERMS Cognitive radio network, dynamic spectrum access, retrial queue, optimal pricing, strategic behavior.

Non-Cooperative Spectrum Access Strategy Based on Impatient Behavior of Secondary Users in Cognitive Radio Networks

“…The non-cooperative game theory can be used to model and analyze the interaction between SUs [38]. Each SU is assumed to be risk neutral, that is, it only has interests in maximizing the expected value of its own benefit [39]. Therefore, we assume that when each SU arrives at the system, it will decide whether to join the waiting queue of the channel and share the spectrum resources with other SUs according to its estimated net welfare.…”

Modified Erlang loss system for cognitive wireless networks

“…Salameh et al [9,10] consider models with limited number of sensing secondary users. Other queueing models of cognitive radio networks could be found in [11][12][13][14][15][16][17]. In [11][12][13]18], the service time distributions of primary and secondary customers are either restricted to Markovian distributions (exponential or phase-type distributions) and/or the assumption that the number of active secondary users are finite.…”

Optimal Pricing Analysis of Computer Networks Based on a Queueing System With Retrial Mechanism

“…On the other hand, from the viewpoint of economics analysis, some papers consider strategic behavior of customers in retrial queues with linear retrial rate; see for instance, Kulkarni [21], [22], Hassin and Haviv [14], Zhang et al [32], [34]- [36], Wang et al [28], [31], among others. Under the constant retrial policy, Economou and Kanta [10] studied a single server retrial queueing system and discussed the equilibrium customer strategies as well as the social and profit maximization problems.…”