  This work investigates the diffusion of cooperative behavior over time in a
decentralized cognitive radio network with selfish spectrum-sensing users. The
users can individually choose whether or not to participate in cooperative
spectrum sensing, in order to maximize their individual payoff defined in terms
of the sensing false-alarm rate and transmit energy expenditure. The system is
modeled as a partially connected network with a statistical distribution of the
degree of the users, who play their myopic best responses to the actions of
their neighbors at each iteration. Based on this model, we investigate the
existence and characterization of Bayesian Nash Equilibria for the diffusion
game. The impacts of network topology, channel fading statistics, sensing
protocol, and multiple antennas on the outcome of the diffusion process are
analyzed next. Simulation results that demonstrate how conducive different
network scenarios are to the diffusion of cooperation are presented for further
insight, and we conclude with a discussion on additional refinements and issues
worth pursuing.
