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GPP-Based Soft Base Station Designing and Optimization

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Abstract

It is generally acknowledged that mobile communication base stations are composed of hardware components such as Field Programming Gate Array (FPGA), Digital Signal Processor (DSP), which promise reliable and fluent services for the mobile users. However, with the increasing demand for energy-efficiency, approaches of low power-consumption and high-flexibility are needed urgently. In this circumstance, General Purpose Processor (GPP) attracts people’s attention for its low-cost and flexibility. Benefited from the development of modern GPP in multi-core, Single Instruction Multiple Data (SIMD) instructions, larger cache, etc., GPPs are capable of performing high-density digital processing. In this paper, we compare several software-defined radio (SDR) prototypes and propose the general architecture of GPP-based soft base stations. Then, the schematic design of resource allocation and algorithm optimization in soft base station implementation are studied. As an application example, a prototype of GPP-based soft base station referring to the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) is realized and evaluated. To the best of our knowledge, it is the first Soft-LTE prototype ever reported. In the end, we evaluate the timing performance of the LTE soft base station and a packet loss ratio of less than 0.003 is obtained.

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Correspondence to Xiao-Feng Tao.

Additional information

This work is supported by the International Scientific and Technological Cooperation Program of China under Grant No. 2010DFA11060, the National Natural Science Foundation of China under Grant No. 61027003, the National Science and Technology Major Project of China under Grant No. 2012ZX03003008-003, and the Beijing Municipal Science and Technology Project under Grant No. D121100002112002.

The preliminary version of the paper was published in the proceedings of CHINACOM 2012.

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Tao, XF., Hou, YZ., Wang, KD. et al. GPP-Based Soft Base Station Designing and Optimization. J. Comput. Sci. Technol. 28, 420–428 (2013). https://doi.org/10.1007/s11390-013-1343-3

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  • DOI: https://doi.org/10.1007/s11390-013-1343-3

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