Joint rate adaption, power control, and spectrum allocation for OFDMA-based multi-hop CRNs

The overall performance of multi-hop cognitive radio networks (CRNs) can be improved significantly by deploying the channel diversity of orthogonal licensed channels in spectrum underlay fashion. However, interference due to the sharing of common radio channels among links and congestion due to the contention among those flows that share the same link become an obstacle to meet this challenge. How to control congestion efficiently and allocate power as well as channel optimally in order to obtain a high end-to-end throughput motivates a framework of cross-layer optimization design for OFDMA-based multi-hop CRNs. By taking into account the problem of joint rate adaption, power control, and spectrum allocation (JRPS), we propose a new cross-layer optimization framework. The formulation is shown to be a mix-integer non-linear programming (MINLP) problem, which is NP-hard in general. To solve the problem, we develop a partially distributed solution, which has been proved to converge to the global optimum within reasonable times.