  We investigate opportunistic cooperation between unlicensed secondary users
and legacy primary users in a cognitive radio network. Specifically, we
consider a model of a cognitive network where a secondary user can
cooperatively transmit with the primary user in order to improve the latter's
effective transmission rate. In return, the secondary user gets more
opportunities for transmitting its own data when the primary user is idle. This
kind of interaction between the primary and secondary users is different from
the traditional dynamic spectrum access model in which the secondary users try
to avoid interfering with the primary users while seeking transmission
opportunities on vacant primary channels. In our model, the secondary users
need to balance the desire to cooperate more (to create more transmission
opportunities) with the need for maintaining sufficient energy levels for their
own transmissions. Such a model is applicable in the emerging area of cognitive
femtocell networks. We formulate the problem of maximizing the secondary user
throughput subject to a time average power constraint under these settings.
This is a constrained Markov Decision Problem and conventional solution
techniques based on dynamic programming require either extensive knowledge of
the system dynamics or learning based approaches that suffer from large
convergence times. However, using the technique of Lyapunov optimization, we
design a novel greedy and online control algorithm that overcomes these
challenges and is provably optimal.
