Método de detecção massiva de sistemas LS-MIMO empregando o método de Richardson modificado em aceleradores gráficos

Abstract

The evolution of wireless communications must support multiples devices and maintain high-speed data transmission. The emerging Large-Scale MIMO techniques allows improving the capacity for the next generations of communications systems. Although the benefit of multipath involves the spectral efficiency, the computational complexity of LS-MIMO detection becomes prohibitive in large systems. Seeking to overcome it, we propose to adapt the Richardson iterative method to the LS-MIMO with random matrices theory by concepts of Marchenko-Pastur and parallel executions. This method requires restricted conditions for the linear resolution that limits its applications. However, the channel knowledge allows establishing adaptations that supply the requirements of the method. The channel effect explained by Marchenko-Pastur allows associating the stability of the process with an increase in the numbers of antennas that contributed to improved the convergence and reduction the iterations. Furthermore, the shared execution with decoding blocks provide a workload distribution that surpasses the throughput of others detections. The results achieved from the comparative analysis of other proposals showed an unprecedented way to increase capability on the large scale detection and provides an efficient parallel processing. Also, the proposal demonstrated a level of adaptability that allows diversifying the association between transmission rate and complexity. Therefore, the implementation of Richardson detection establishes that the transmission rate is comparable with other projects and the increasing of 1.74dB SNR improve 150% at throughput. Based on this approach, the execution shows a significant increase in parallel transmission capacity when implemented on GPU. Also, the implementation shows scalable aspects that allow increasing the performance to Gb/s by insertion of others parallels devices (GPUs) in the system.