Método de detecção massiva de sistemas LS-MIMO empregando o método de Richardson modificado em aceleradores gráficos
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 eff...
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| Formato: | doctoralThesis |
| Idioma: | por |
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/22517 |
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| Resumo: | 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. |
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