Cognitive radios with ergodic capacity guarantees for primary users

Cognitive radios implement adaptive resource allocation schemes that exploit knowledge of the channel state information to optimize the performance of the secondary users while limiting the interference to the primary users. The algorithms in this paper are designed to maximize the weighted sum-rate of secondary users which transmit orthogonally and adhere to three different constraints: i) limits on the long-term (average) power at each secondary transmitter; ii) limits on the long-term interfering power at each primary receiver; and iii) limits on the long-term capacity loss inflicted to each primary receiver. Although the long-term capacity constraints render the resultant optimization problem non-convex, it holds that it has zero-duality gap and that, due to the favorable structure in the dual domain, it can be efficiently solved.