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Nidal Qasem
Al-Ahliyya Amman University (AAU)
Computer Science & IT Electrical & Electronics Engineering

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Enhancing the Capacity of the Indoor 60 GHz Band Via Modified Indoor Environments Using Ring Frequency Selective Surface Wallpapers and Path Loss Models Nidal Qasem
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1362.298 KB) | DOI: 10.11591/ijece.v8i5.pp3003-3020

Abstract

The 60 GHz band has been selected for short-range communication systems to meet consumers’ needs for high data rates. However, this frequency is attenuated by obstacles. This study addresses the limitations of the 60 GHz band by modifying indoor environments with ring Frequency Selective Surfaces (FSSs) wallpaper, thereby increasing its utilization. The ring FSS wallpaper response at a 61.5 GHz frequency has been analyzed using both MATLAB and Computer Simulation Technology (CST) Microwave Studio (MWS) software. ‘Wireless InSite’ is also used to demonstrate enhanced wave propagation in a building modified with ring FSSs wallpaper. The demonstration is applied to Single Input Single Output (SISO) and Multiple Input Multiple Output (MIMO) systems to verify the effectiveness of FSSs on such systems’ capacity. The effectiveness of the suggested modification over delay spread has been studied for the MIMO scenario, as well as the effect of the human body on capacity. Simulation results presented here show that modifying a building using ring FSS wallpaper is an attractive scheme for significantly improving the indoor 60 GHz wireless communications band. This paper also presents and compares two large-scale indoor propagation Path Loss Models (PLMs), the Close-In (CI) free space reference distance model and the Floating Intercept (FI) model. Data obtained from ‘Wireless InSite’ over distances ranging from 4 to 14.31 m is analyzed. Results show that the CI model provides good estimation and exhibits stable behavior over frequencies and distances, with a solid physical basis and less computational complexity when compared to the FI model. 
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