Research On Power Allocation Mechanism In The OFDM-Based Cognitive Radio Systems

In order to resolve the current tension in wireless spectrum resource, cognitive radio has come into being, and because of the good performance of Orthogonal Frequency Division Multiplexing (OFDM), OFDM can be applied to the OFDM-based cognitive radio systems. Nowadays, the research on power allocation algorithm in the OFDM-based cognitive radio systems is very hot. This thesis aims to study some of the power allocation algorithms in the single user and multi-user OFDM-based cognitive radio systems, especially some improved power allocation algorithms based on water-filling algorithm and greedy algorithm. This thesis has important theoretical significance, and even can be applied to the power allocation in the actual cognitive radio systems.The thesis studied deeply the basic principles of cognive radio and OFDM, discussed the basic principles of the OFDM-based cognitive radio systems, gave the basic principles of the traditional power allocation algorithms, such as water-filling algorithm and greedy algorithm. Simulation results showed the performance of these two algorithms in order to understand the basic principles of the two power allocation algorithms.Finally, the thesis focused on some improved power allocation algorithms based on water-filling algorithm and greedy algorithm. Based on water-filling algorithm, in the single user OFDM-based cognitive radio systems, using the iterative partitioned water-filling algorithm, the improved algorithm considered the power leakage of the adjacent carriers, by setting some protection bands, and by forming the power distribution of the carries closed to the those with the more stringent power constraints into trapezoid, reduced the computational complexity. Based on water-filling algorithm, in the multi-user OFDM-based cognitive radio systems, the improved algorithm, based the iterative partitioned water-filling algorithm, considering the peak power constraint, was a more efficient power allocation algorithm, and by updating ordinaly the water level, reduced the computational complexity. Based on greedy algorithm, in the single user OFDM-based cognitive radio systems, the improved algorithm assigned a bit to the sub-carriers with the maximum efficiency value, that is to say, solved the 0-1 knapsack problem with dimensions of the number of primer users plus one. Based on greedy algorithm, in the multi-user OFDM-based cognitive radio systems, the improved algorithm, joining the cognitive radio base station, allocated the next bit to the subchannel/cognitive radio base station pairs with the maximum efficiency value, that is to say, solved the 0-1 knapsack problem with the dimension of the number of primer users plus that of cognitive radio base station.Simulation results showed, for all the cases studied in the thesis, the performance of all the improved power allocation algorithms was close to those of optimal power allocation algorithms, and their computational complexity was relatively low.