• DocumentCode
    660633
  • Title

    CUDA-Enabled Multiple Symbol Detection for PCM/FM Demodulation

  • Author

    Renliang Zhao ; Haixin Zheng ; Ying Liu ; Liheng Jian ; Xianglong Gu ; Bingyin Han ; Zhongya Wang

  • Author_Institution
    Sch. of Comput. & Control, Univ. of Chinese Acad. of Sci., Beijing, China
  • fYear
    2013
  • fDate
    4-6 Nov. 2013
  • Firstpage
    9
  • Lastpage
    15
  • Abstract
    PCM/FM has been widely used in telemetry system. Multiple Symbol Detection (MSD) based signal demodulation methods can achieve lower BER (Bit Error Rate) than other methods. Due to its high computational complexity, current MSD algorithms are implemented in specialized signal processing devices, such as FPGAs (Field Programmable Gate Arrays). As the rapid development of CUDA, GPU has successfully accelerated applications in a variety of domains. In this paper, we explore to utilize CUDA-enabled GPU to accelerate MSD-based signal demodulation method. The computation core of MSD, sliding correlation problem, is formulated and an efficient parallelization scheme is proposed. CU-MSD (CUDA-enabled MSD) algorithm is implemented by adapting CUDA-enabled sliding correlation. Various optimization techniques are used to achieve the maximum performance. We evaluate our implementation by using data sets from a real aerospace PCM/FM integrated baseband system. The experimental results demonstrate up to 52.8x speedup.
  • Keywords
    demodulation; error statistics; graphics processing units; optimisation; parallel architectures; telemetry; BER; CUDA; GPU; MSD; PCM/FM demodulation; bit error rate; multiple symbol detection; optimization; rapid development; signal demodulation methods; signal processing; sliding correlation problem; telemetry system; Correlation; Demodulation; Frequency modulation; Graphics processing units; Instruction sets; Phase change materials; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud and Service Computing (CSC), 2013 International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/CSC.2013.10
  • Filename
    6693172