Research on Sub-Carriers Allocation Algorithm in MIMO-OFDM Systems
|School||Southwest Jiaotong University|
|Course||Communication and Information System|
|Keywords||MIMO-OFDM Sub-carriers Allocation Antenna Selection|
The contradiction between the shortage of wireless spectrum and the demand of high data rate is becoming more and more prominent, and it’s imperative to improve the spectral efficiency. Static radio resource allocation can’t meet the need of communication because of the complexity and uncertainty of the wireless communication environment. In order to increase the spectral efficiency, it’s necessary to investigate the way of resource allocation according to the real-time information of channels, namely adaptive radio resource allocation. On the other hand, the application of new technologies is also a feasible way to improve system performance, such as Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) that are widely used in the next generation mobile communication systems. These technologies greatly increase the flexibility and complexity of adaptive resource allocation while improving system performance. Therefore, the effective radio resource allocation algorithms play an important role in wireless communications.Adaptive sub-carriers allocation algorithm for the downlink of MIMO-OFDM system is studied and the performance of the algorithm is evaluated by the metrics including capacity, fairness and computational complexity.The channel on each sub-carrier is viewed as a flat fading MIMO channel and a new OFDM sub-carrier allocation algorithm in the MIMO environments is proposed. The purpose of the algorithm is to improve the spectral efficiency and to enhance the fairness between users. The proposed algorithm carries out the allocation of sub-carriers with the proportional fairness constraint strictly followed firstly and then the sub-carriers are swapped between users repeatedly until the capacity can’t be increased. As a result, the capacity is further improved with the proportional fairness guaranteed. Simulation shows that the algorithm can improve the capacity effectively compared with proportional resource allocation and the fairness is close to the proportional resource allocation.To make full use of the spatial advantage of multi-antenna system, resource allocation is extended from frequency to space and frequency, and a joint antenna and sub-carriers allocation algorithm is discussed. The algorithm is implemented carrier by carrier, which chooses some users from all users that need to allocate sub-carriers according to the ratio of the current rate and the proportional constraint of each user on each sub-carrier and these users have the priority to be allocated to the space-frequency resource block corresponding to the current sub-carriers. The allocation chooses the combination of the users that has the maximum capacity on the current sub-carrier from all the probable combinations of these selected users as the final allocation result. Simulation shows that capacity of the proposed algorithm has decreased slightly but the performance of computational complexity and proportional fairness is improved obviously compared with exhaustive search.Finally, joint antenna and sub-carriers allocation algorithm based on antenna selection is considered for the purpose of decreasing the computational complexity. Before the joint antenna and sub-carriers allocation, the antenna selection based on Markov Chain Monte Carlo (MCMC) is executed to reduce the quantity of space-frequency blocks used to resource allocation. Consequently, the computational complexity is reduced enormously while retaining the advantage of space diversity. Simulation shows that the algorithm has tiny capacity loss, but reduces the computational complexity greatly compared with non-antenna-selection and is an effective simplified algorithm.