LEAD: leveraging protocol signatures for improving wireless link performance

  • Authors:
  • Jun Huang;Yu Wang;Guoliang Xing

  • Affiliations:
  • Michigan State University, East Lansing, USA;Michigan State University, East Lansing, USA;Michigan State University, East Lansing, USA

  • Venue:
  • Proceeding of the 11th annual international conference on Mobile systems, applications, and services
  • Year:
  • 2013

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Abstract

Error correction is a fundamental problem in wireless system design as wireless links often suffer high bit error rate due to the effects of signal attenuation, multipath fading and interference. This paper presents a new cross-layer solution called LEAD to improve the performance of existing channel decoders. While the traditional wisdom of cross-layer design is to exploit physical layer information at upper-layers, LEAD represents a paradigm shift in that it leverages upper-layer protocol signatures to improve the performance of physical layer channel decoding. The approach of LEAD is motivated by two key insights. First, channel codes can correct more errors when the values of some bits, which we refer to as {\em pilots}, are known before decoding. Second, some header fields of upper-layer protocols are often fixed or highly biased toward certain values. These distinctive bit pattern signatures can thus be exploited as pilots to assist channel decoding. To realize this idea, we first characterize bit bias in real-life network traffic, and develop an efficient algorithm to extract pilot bits with assured prediction accuracy. We then propose a decoding framework to allow existing channel decoders to effectively exploit extracted pilots. We implement LEAD on GNURadio/USRP platform and evaluate its performance by replaying real-life packet traces on a testbed of 12 USRP links. Our results show that LEAD significantly improve wireless link performance, while incurring very low overhead. Specifically, LEAD reduces more than 90\% bit errors for 48.9\% packets, and improves the end-to-end link throughput by 1.43x to 1.93x over existing error correction schemes.