Chance-Constrained Optimization of OFDMA Cognitive Radio Uplinks

A resource allocation task for the uplink of OFDMA-based cognitive radio (CR) systems is considered. The weighted sum-rate is maximized over subcarrier assignment as well as over power loading per CR user, while protecting primary user (PU) systems. However, due to the lack of explicit support from PU systems, the channels from CR users to the PU may not be accurately acquired. Thus, the PU interference constraint is posed as a chance constraint, for which conservative convex approximation is employed for tractability. In particular, to mitigate the combinatorial complexity incurred for optimal subcarrier assignment, a separable structure is pursued, and the dual decomposition method is adopted to obtain near-optimal solutions. Numerical tests verify that the proposed algorithms yield higher weighted sum-rate at lower computational complexity than a benchmark algorithm.