Advanced Search
    Du Haipeng, Zheng Qinghua, Zhang Weizhan, Yan Jifeng. A Packet Loss Differentiation Algorithm for 4G-LTE Network[J]. Journal of Computer Research and Development, 2015, 52(12): 2684-2694. DOI: 10.7544/issn1000-1239.2015.20150726
    Citation: Du Haipeng, Zheng Qinghua, Zhang Weizhan, Yan Jifeng. A Packet Loss Differentiation Algorithm for 4G-LTE Network[J]. Journal of Computer Research and Development, 2015, 52(12): 2684-2694. DOI: 10.7544/issn1000-1239.2015.20150726

    A Packet Loss Differentiation Algorithm for 4G-LTE Network

    • On wireless networks, packet losses are usually caused by congestion or wireless fading. Loss differentiation is a fundamental problem of how to identify the cause of packet losses based on the transmission characteristics of wireless network. When moving on to LTE network, this remains an issue worthy of study due to the possible changes in packet loss patterns. In light of this, this paper proposes a loss differentiation algorism LDA-LTE for LTE network. We firstly conduct a detailed measurement study of the transmission characteristics of LTE network in configurable congestion and wireless channel fading scenarios. The test bed is based on an emulated LTE network in the laboratory by adopting a LTE base station emulator. Then, we find that the packet loss patterns that previous works used as the principal basis for loss differentiation do not hold when moving on to LTE network. This makes these works fail to work on LTE network. Finally, we design a loss differentiation algorism LDA-LTE, which collectively uses observed loss patterns to infer the cause of the packet losses on the LTE network in the hybrid scenario where congestion loss and wireless loss occur simultaneously. Evaluations on the test bed show that the accuracy of loss differentiation with LDA-LTE is significantly improved compared with previous work.
    • loading

    Catalog

      Turn off MathJax
      Article Contents

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return