Improved modeling of IEEE 802.11a PHY through fine-grained measurements

  • Authors:
  • Jeongkeun Lee;Jiho Ryu;Sung-Ju Lee;Ted Taekyoung Kwon

  • Affiliations:
  • Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA 94304, USA;Seoul National University, Building 301, Room 553-1, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea;Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA 94304, USA;Seoul National University, Building 301, Room 553-1, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2010

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Abstract

In wireless networks, modeling of the physical layer behavior is an important yet difficult task. Modeling and estimating wireless interference is receiving great attention, and is crucial in a wireless network performance study. The physical layer capture, preamble detection, and carrier sense threshold are three key components that play important roles in successful frame reception in the presence of interference. Using our IEEE 802.11a wireless network testbed, we carry out a measurement study that reveals the detailed operation of each component and in particular we show the terms and conditions (interference timing, signal power difference, bitrate) under which a frame survives interference according to the preamble detection and capture logic. Based on the measurement study, we show that the operations of the three components in real IEEE 802.11a systems differ from those of popular simulators and present our modifications of the IEEE 802.11a PHY models to the NS-2 and QualNet network simulators. The modifications can be summarized as follows. (i) The current simulators' frame reception is based only on the received signal strength. However, real 802.11 systems can start frame reception only when the Signal-to-Interference Ratio (SIR) is high enough to detect the preamble. (ii) Different chipset vendors implement the frame reception and capture algorithms differently, resulting in different operations for the same event. We provide different simulation models for several popular chipset vendors and show the performance differences between the models. (iii) Based on the 802.11a standard setting and our testbed observation, we revise the simulator to set the carrier sense threshold higher than the receiver sensitivity rather than equal to the receiver sensitivity. We implement our modifications to the QualNet simulator and evaluate the impact of PHY model implementations on the wireless network performance; these result in an up to six times increase of net throughput.