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In cognitive radio (CR),power allocation plays an important role in protecting primary user from disturbance of secondary user. Some existing studies about power allocation in CR utilize ’interference temperature’ to achieve this protection,which might not be suitable for the OFDM-based CR. Thus in this paper,power allocation problem in multi-user orthogonal frequency division multiplexing (OFDM) and distributed antenna cognitive radio with radio over fiber (RoF) is firstly modeled as an optimization problem,where the limitation on secondary user is not ’interference temperature’,but that total throughput of primary user in all the resource units (RUs) must be beyond the given threshold. Moreover,based on the theorem about maximizing the total throughput of secondary user,equal power allocation algorithm is introduced. Furthermore,as the optimization problem for power allocation is not convex,it is transformed to be a convex one with geometric programming,where the solution can be obtained using duality and Karush-Kuhn-Tucker (KKT) conditions to form the optimal power allocation algorithm. Finally,extensive simulation results illustrate the significant performance improvement of the optimal algorithm compared to the existing algorithm and equal power allocation algorithm.
Some existing studies about power allocation in CR Utilization ’interference temperature’ to achieve this protection, which might not be suitable for the OFDM- based CR. Thus in this paper, power allocation problem in multi-user orthogonal frequency division multiplexing (OFDM) and distributed antenna cognitive radio with radio over fiber (RoF) is first modeled as an optimization problem, where the limitation on secondary user is not ’interference temperature’, but that total throughput of primary user in all the resource units (RUs) must be beyond the given threshold. Furthermore, based on the theorem about maximizing the total throughput of secondary user, equal power allocation algorithm is introduced. , as the optimization problem for power allocation is not convex, it is transformed to be a convex one with geometric programming, where the solution can be be ined using duality and Karush-Kuhn-Tucker (KKT) conditions to form the optimal power allocation algorithm. Finally, extensive simulation results illustrate the significant performance improvement of the optimal algorithm compared to the existing algorithm and equal power allocation algorithm.