Throughput analysis in mobile ad hoc networks with directional antennas

  • Authors:
  • Yin Chen;Jiajia Liu;Xiaohong Jiang;Osamu Takahashi

  • Affiliations:
  • School of Systems Information Science, Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, Hokkaido 041-8655, Japan and The State Key Lab of ISN, Xidian University, China;Graduate School of Information Sciences, Tohoku University, Aobayama 6-3-09, Sendai 980-8579, Japan;School of Systems Information Science, Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, Hokkaido 041-8655, Japan;School of Systems Information Science, Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, Hokkaido 041-8655, Japan

  • Venue:
  • Ad Hoc Networks
  • Year:
  • 2013

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Abstract

A major obstacle stunting the application of mobile ad hoc networks (MANETs) is the lack of a general throughput analysis theory for such networks. The available works in this area mainly focus on asymptotic throughput study (order sense) in MANETs with omnidirectional antennas or directional antennas. Although the order sense results can help us to understand the general scaling behaviors, it tells us little about the exact achievable throughput. This paper studies the achievable throughput of a MANET where each node is equipped with a directional antenna of beamwidth @q for transmission. A generalized two hop relay scheme with packet redundancy f is adopted for packet routing. Based on the Markov chain and automatic feedback theory, we explore a general theoretical framework that enables the achievable throughput analysis to be conducted for a directional antenna-based MANET. Based on the results of the achievable per node throughput, we further explore the throughput optimization problem for a fixed beamwidth @q and determine the corresponding optimal setting of f to achieve the optimal throughput. Numerical studies are also conducted to demonstrate the efficiency of these models.It shows that the maximum achievable throughput obtained from our theoretical framework matches nicely (with at most 7% difference) with that obtained from simulation under a realistic model.