A Study On Power Allocation Algorithms In The OFDM-Based Cognitive Radio System

In recent years, the need of wireless communication grows highly and the number of users increases gradually. As the spectrum occupies quickly, how to make use of the scarce spectrum resources has become one of the research hotspots in the field of wireless communications. In order to improve the spectrum efficiency and utilization, the cognitive OFDM system combines the OFDM technology with the cognitive radio technology, and divides the spectrum resources dynamically. The power distribution technology has been a key issue in the cognitive OFDM system. Based on the theory of power control, this paper presents some power allocation algorithms in the cognitive OFDM system. The main content includes a water-filling power allocation algorithm based on the OFDM and a power allocation algorithm based on the energy efficiency.It has been proved that the classical water-filling power allocation algorithm is optimal in cognitive OFDM systems. The interference temperature limit on the cognitive user channel is taken into account and a double factor binary search optimization algorithm is proposed. A monotonical surplus function is introduced under the total power constraints, the accurate value of Lagrangian multipliers is attained through the double binary search iteration method, and the power allocation of the sub-channels is conducted through the value of Lagrangian multipliers. Simulation results show that the algorithm can effectively use the spectrum hole between primary users. The data transmission rate of the cognitive users can be maximized under both total power constraints and interference temperature constraints. The data transmission rate of the presented algorithm is approaching to that of the traditional water-filling algorithm.In addition, maximization of energy efficiency is another objective in the paper. The power on each subcarrier is reallocated and an algorithm based on energy efficiency is proposed. Compared with the traditional transport strategy, the algorithm can not only obtain high transmission rate, but also maximize the energy efficiency of the system. The system thus could find a tradeoff between the transmission rate and the power efficiency.