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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(4): 342-346 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.334

Integration of Smart Antenna System in Mobile Ad Hoc Networks

Mohammed A. Abdala and Areej K. Al-Zuhairy
Abstract—The capacity of a Mobile Ad-hoc Network (MANET) can be severely limited due to interference constraints. One way of improving the overall capacity of ad-hoc networks is by the use of smart antenna system (SAS). SAS has the advantage over traditional omnidirectional antennas of being able to orientate radio signals into the concerned directions in either transmission mode or in reception mode. The omnidirectional antennas in broadcasting over the whole network are the source of an excessive redundancy of broadcast packet receptions within each node. The SAS consist of a uniform linear array (ULA) and the signal processing unit, employing constant modulus algorithm (CMA) is implemented using MATLAB R2012a. For the MANET we used geographic routing protocol (GRP) which is Optimum Network Engineering Tool’s (OPNET’s) custom model routing protocol where each node uses the global positioning system (GPS) to identify its own position and implemented in OPNET modeler 14.5. A co-simulation is then made between OPNET modeler 14.5 and MATLAB R2012a to take advantage of SAS and uses it with MANET in OPNET 14.5. Using this approach, exploring SAS for MANET improves throughput and Signal to Noise Ratio overall the network and decreases Bit Error Rate compared to omnidirectional antenna.

Index Terms—CMA, mobile Ad Hoc network, omnidirectional antenna, smart antenna system.

The authors are with College of Information Engineering, Al-Nahrain University, Baghdad, Iraq (e-mail: dr.maabdala@ieee.org, areejalzuhairy@gmail.com).

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Cite:Mohammed A. Abdala and Areej K. Al-Zuhairy, "Integration of Smart Antenna System in Mobile Ad Hoc Networks," International Journal of Machine Learning and Computing vol.3, no. 4, pp. 342-346, 2013.

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