The Algorithm Analysis And Simulation Of Adaptively Allocate Resource And Antenna Selection In MIMO-OFDM

MIMO-OFDM takes the advantage of MIMO in improving spectrum efficiency and has the OFDM resistance frequency selective fading. These characteristics determine the MIMO-OFDM system will be the core of next-generation mobile communication technology.Adaptive resource allocation is allocating dynamic bits and power based on the characteristics of sub-channel, which can improve system performance. There are many algorithms for adaptive resource allocation. The paper selected two classical algorithms: the greedy algorithm and the Chow algorithm. One of the greedy algorithm has been improved, then simulate the improved greedy and the Chow algorithm. The simulation results showed that the distribution in line with the ideas put forward. The allocation of the bits and power according to the channel response is reasonable, which make the system resources efficient. Through the simulation analysis and comparison of these two classic algorithm in performance and computation, we find that the performance is almost the same, but in complexity and can be carried out, the improved greedy is inadequate. Chow algorithm has a large advantage in terms of performance, complexity, can be carried out, and so it become a first choice in system.MIMO-OFDM enhance the robustness and channel capacity of receive signal through multiple transmitter and receiver antennas. However, the use of multi-antenna increases the cost of hardware and signal processing complexity. Antenna selection take the small loss of system capacity to achieve the savings for the cost of hardware and data-processing complexity by selecting part of signal from all the antennas signal to process. The main concern of this paper is the use of antenna selection in space reuse, which introduces the optimal selection and the Eigen Vectors-Based Gradual Elimination(EVBGE) and analyzes the characteristics of a simplified EVBGE, and then simulate and compare performance in capacity. The simplified EVBGE in the performance of capacity is worse than optimal selection algorithm but it save the cost of hardware and data-processing complexity. Antenna selection maintains high-capacity when make full use of the antennas.