Market-Driven Spectrum Sharing in Cognitive Radio

With the development of technologies in various fields of electrical and computer engineering, wireless communication has become increasingly popular and even indispensable in our daily life. Electronic devices or equipments, such as mobile phones, tablets, global positioning system (GPS), cordless computer peripherals, remote controllers, and satellite televisions, are all based on wireless communication technology. As a consequence, wireless technology has experienced rapid evolution in the past decade, and has been attracting more and more research, application, and business interests from both academia and industry.

Mechanism design is a subfield of microeconomics and game theory. It considers how to implement good system-wide solutions to problems that involve multiple self-interested agents [1]. In 2007, the Nobel Prize in economics was awarded to Leonid Hurwicz, Eric Maskin, and Roger Myerson “for having laid the foundations of mechanism design theory.” This indicates the importance and popularity of mechanism design in various areas of applied economics as well as market-driven applications. For instance, mechanism design has been extensively studied in practical engineering problems, such as electronic market design, distributed scheduling, and radio resource allocation.

In this chapter, we consider a more complicated scenario of spectrum sharing with multiple spectrum sellers. In this model, a CR network with multiple heterogeneous POs and SUs is considered. Each PO has a different amount of spectrum to lease in different specific areas, and has a different users’ (PUs’) activity. Each SU has heterogeneous requirements in terms of spectrum demands and attitudes toward POs’ potential spectrum recall. Obviously, in this case, spectrum sharing needs to jointly consider both spectrum allocation and individual strategies. However, solving such a joint optimization problem is challenging due to the facts that (1) PUs’ activities are random and heterogenous among all POs; and (2) before the spectrum allocation has been done, it is impossible to know the quantity of spectrum recalled from each SU. In order to deal with the high computational complexity involved in solving such problem, we introduce a new method called Two-stage resource allocation scheme with combinatorial auction and Stackelberg game in spectrum sharing (TAGS) mechanism [1], which decomposes the solution into two separate stages. In the first stage, a suboptimal spectrum allocation is derived by formulating a combinatorial spectrum auction without considering the potential spectrum recall. Based on the winner determination in the first stage, each PO then decides a maximum amount of spectrum that may be recalled in the second stage, and each winning SU claims a payment reduction so as to offset the risk of utility degradation. Such a decision making process is viewed as a Stackelberg pricing game, and the best strategies for both POs and SUs are figured out accordingly. Theoretical and simulation results demonstrate that TAGS mechanism is efficient in increasing the spectrum utilization and economically feasible for all participants.

The rest of this chapter is organized as follows: Sect. 4.2 describes the system model and summarizes all important notations used in this chapter. Section 4.3 presents the first stage of TAGS mechanism, i.e., the combinatorial spectrum auction. A recall-based pricing game is formulated in Sect. 4.4 to study the strategy decision process in the second stage of TAGS. Section 4.5 shows the analyses of some desired economic properties and a detailed time-line of the TAGS mechanism. Simulation results are illustrated in Sect. 4.6. Finally, a brief summary is given in Sect. 4.7.

Without the synchronization of allocation periods, it is impossible to run the spectrum sharing mechanism in an offline manner. Thus, in this chapter, we investigate the online spectrum allocation problem in CR networks with uncertain activities of both PUs and SUs. In this system model, there is a PBS who owns multiple licensed radio channels and is responsible to protect PUs’ spectrum usages. At the same time, the PBS also runs an online auction to lease its idle channels to SUs who request and access spectrum on the fly. By considering a more practical situation that the PBS has no a priori information of PUs’ activities, the PBS may suffer a great penalty if it is only eager to improve its potential auction revenue while ignoring its own PUs’ spectrum usages. On the other hand, if the PBS reserves channels excessively to completely protect its own PUs, it may lose economic profits from the spectrum auction. To balance the penalties introduced by incomplete services for PUs and the auction profits from granted SUs’ spectrum requests, we present a new approach, called virtual online double spectrum auction (VIOLET) mechanism [1]. In this mechanism, the concept of virtual spectrum sellers is introduced to describe the channel uncertainties. The well-designed online admission and pricing scheme of VIOLET can ensure non-deficit utility of the PBS while resisting mendacious behaviors from selfish SUs. Theoretical analyses prove that the VIOLET mechanism is economic robust in terms of budget-balance, individual rationality, and incentive compatibility. In addition, simulation results show that the VIOLET mechanism can improve the utility of the PBS, enhance spectrum utilization, and achieve better satisfaction of SUs.

Radio spectrum scarcity has become a critical limitation for the development of new wireless equipments, applications, and services. To alleviate such burden, more and more researches have been conducted for improving the spectrum utilization efficiency. In this brief, we focused on one of the most promising technologies, i.e. CR-based dynamic spectrum sharing, from the view of engineering economics. In Chap. 1, the architecture of CR networks and the characteristics of traditional DSA were first presented. Then, the framework of market-driven spectrum sharing was illustrated. As mathematical backgrounds, Chap. 2 reviewed the fundamentals of mechanism design theory, and described some well-known existing mechanisms, such as SPSB, VCG and LOS. After that, three featured spectrum sharing mechanisms were demonstrated in detail. Specifically, a recall-based spectrum auction mechanism was studied in Chap. 3, where a single-seller spectrum sharing model with dynamic spectrum availabilities was considered. In Chap. 4, a two-stage spectrum sharing framework was modeled, in which a multi-seller recall-based spectrum sharing problem was analyzed by a first-stage combinatorial auction mechanism along with a second-stage Stackelberg pricing game. Chapter 5 introduced an online spectrum allocation mechanism, which aims to the scenarios with both PUs and SUs declaring their spectrum usage requests on the fly. In addition, theoretical analyses and numerical results were provided in all these chapters to prove the feasibility, efficiency, and superiority of all aforementioned designs.