Socially Optimal Queuing Control in Cognitive Radio Networks Subject to Service Interruptions: To Queue or Not to Queue?

• Published in: IEEE transactions on wireless communications Vol. 10; no. 5; pp. 1656 - 1666
• Main Authors: Husheng Li, Zhu Han
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.2011; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Cognitive radio; Delay; Exact sciences and technology; Numerical models; Pricing; Queueing analysis; queuing control; Radiocommunication specific techniques; Radiocommunications; Servers; service interruption; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Teleprocessing networks. Isdn; Teletraffic; Valuation and optimization of characteristics. Simulation; Wireless networks; E-learning; Interruption; Teletraffic; service interruption; Network service; Cognitive radio; Algorithm; Remote teaching; queuing control; Queue length; Optimal strategy; Computer network; Queueing system; Traffic management; Optimal control; Pricing; Traffic control; Numerical simulation; Delay time; Tariffication; Toll; Radio communication; Telecommunication services; Software radio
• ISSN: 1536-1276
• DOI: 10.1109/TWC.2011.030411.101220

The main challenge to cognitive radio is the emergence of primary users, which can be considered as the service interruptions in a queuing system. The service interruption can incur significant delays for secondary users' data packets which are considered as secondary customers. Therefore, a secondary customer needs to decide whether to join the queue or leave for other means of transmission. It is shown that the individually optimal strategy for joining the queue is characterized by a threshold of queue length. When the current queue length is above this threshold, the secondary customer should leave; otherwise it should join the queue. The socially optimal threshold of queue length is also obtained and is numerically shown to be smaller than the individually optimal one, which implies that the individually optimal strategy does not yield the socially optimal one. To bridge the gap between the individually and socially optimal strategies, a pricing mechanism is proposed to toll the service of each secondary customer, thus equalizing the two optimal strategies. When the channel statistics are unknown, an online learning procedure, based on the Kiefer-Wolfowitz algorithm, is proposed. The proposed algorithms are then demonstrated using numerical simulations.