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Spectrum trading in cognitive radio networks: A market-equilibrium-based approach

Cognitive radio has emerged as a new design paradigm for the next-generation wireless networks. Cognitive radio networks are designed based on the concept of dynamic spectrum sharing where cognitive radio users can opportunistically share the radio spectrum. For example, in case of vertical spectrum sharing, a spectrum owner (or primary user/service) can share (or sell) its licensed spectrum with (to) other users (i.e., secondary users/services). The economics of spectrum sharing, which is referred to as spectrum trading, is the focus of this article. The objective of spectrum trading is to maximize the revenue of the spectrum owner, and at the same time enhance the satisfaction of the cognitive radio users. We first discuss the different network architectures and protocol behaviors for dynamic spectrum sharing as well as the spectrum sharing models. Then the scope of spectrum trading is discussed in the context of different spectrum sharing models. The primary research issues related to spectrum trading in cognitive radio networks are outlined, and the possible solution approaches are discussed. To this end, we introduce a market-equilibrium-based spectrum trading mechanism that uses spectrum demand and supply of the primary and secondary users, respectively. Since spectrum supply is stochastic in nature, a distributed and adaptive learning algorithm is used for the secondary users to estimate spectrum price and adjust the spectrum demand accordingly so that the market equilibrium can be reached.