Algorithms for optimal resource allocation in heterogeneous cognitive radio networks

In this paper, the problem of resource allocation in heterogeneous cognitive radio networks is investigated under the constraints of interference temperature limit. The resource allocation problem is formulated as a mixed-integer programming problem and solved by Lagrangian dual method based on which a centralized subgradient update algorithm is proposed. The approximate optimality of this algorithm is promised by time-sharing condition. We also realize this centralized algorithm distributively following the implication of dual decomposition. Two algorithms are compared in terms of complexity, communication signaling, latency etc.. At last, simulations are carried out to validate the proposed algorithms.