Dynamic Spectrum Sharing Among Repeatedly Interacting Selfish Users With Imperfect Monitoring

Computer Science – Information Theory

Scientific paper

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20 pages excluding 7 figures and 3 tables

Scientific paper

In this paper, we develop a novel design framework for dynamic spectrum sharing among secondary users (SU) who adjust their power allocation while satisfying under interference temperature (IT) constraints imposed by primary users. The considered interaction among the secondary users is characterized by the following three unique features. First, SUs are selfish and aim to maximize their own long-term payoffs from utilizing the network rather than obeying the prescribed allocation of a centralized controller. Second, SUs are interacting with each other repeatedly and they can coexist in the system for a long time as long as the IT constraints are not violated. Third, SUs have imperfect and limited monitoring ability: they only observe whether the IT constraints are violated, and their observation is imperfect due to the erroneous measurements. To capture these unique features, we model the interaction of secondary users as a repeated game with imperfect monitoring. We first characterize the set of Pareto optimal operating points that can be achieved by deviation-proof spectrum sharing policies, which are policies that the selfish users find it in their interest to comply with. Next, for any given operating point in this set, we show how to construct a deviation-proof policy (protocol) to achieve it. The constructed deviation-proof policy is amenable to distributed implementation, and allows users to transmit in a time-division multiple-access (TDMA) fashion. In the presence of strong multi-user interference, our policy outperforms existing spectrum sharing policies that dictate users to transmit at constant power levels simultaneously. Moreover, our policy can achieve Pareto optimality even when secondary users have imperfect and limited monitoring ability, as opposed to existing solutions based on repeated game models, which require perfect monitoring abilities.

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