  We study the profit maximization problem of a cognitive virtual network
operator in a dynamic network environment. We consider a downlink OFDM
communication system with various network dynamics, including dynamic user
demands, uncertain sensing spectrum resources, dynamic spectrum prices, and
time-varying channel conditions. In addition, heterogenous users and imperfect
sensing technology are incorporated to make the network model more realistic.
By exploring the special structural of the problem, we develop a low-complexity
on-line control policies that determine pricing and resource scheduling without
knowing the statistics of dynamic network parameters. We show that the proposed
algorithms can achieve arbitrarily close to the optimal profit with a proper
trade-off with the queuing delay.
