LTE physical layer implementation using GPU based high performance computing

S. Bhattacharjee, S. Yadav, S. K. Patra
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引用次数: 4

Abstract

In recent years Graphics Processing Unit (GPU) has evolved as a high performance data processing technology allowing users to compute large blocks of parallel data using an array of low complexity processors. This paper proposes the implementation of compute intensive portions of 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) physical layer using GPU. LTE employs Orthogonal Frequency Division Multiple Access (OFDMA) in downlink and Single Carrier Frequency Division Multiple Access (SC-FDMA) in uplink. Both these demand computationally complex Inverse Fast Fourier Transform (IFFT) and Fast Fourier Transform (FFT) processing at the transmitter and the receiver. The computational requirements at the base station increases significantly with the increase in number of users. This paper presents a simulation model utilizing the massively parallel architecture of GPU to reduce computation time of IFFT and FFT operations. Simulation results demonstrate that GPU provides a framework for fast data processing in this application.
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LTE物理层实现采用基于GPU的高性能计算
近年来,图形处理单元(GPU)已经发展成为一种高性能数据处理技术,允许用户使用一组低复杂度的处理器来计算大量并行数据。本文提出了利用GPU实现第三代合作伙伴计划(3GPP)长期演进(LTE)物理层的计算密集型部分。LTE下行链路采用正交频分多址(OFDMA),上行链路采用单载波频分多址(SC-FDMA)。这两者都需要计算复杂的反快速傅里叶变换(IFFT)和快速傅里叶变换(FFT)处理在发射机和接收机。随着用户数量的增加,基站的计算需求也在显著增加。本文提出了一种利用GPU大规模并行架构的仿真模型,以减少IFFT和FFT运算的计算时间。仿真结果表明,GPU为该应用的快速数据处理提供了一个框架。
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