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Original Articles

Fractional Fourier Transform based Beamforming for Next Generation Wireless Communication Systems

, MIETE, , AMIETE & , FIETE
Pages 357-366 | Published online: 26 Mar 2015
 

Abstract

Today's mobile communication systems are primarily designed to provide cost efficient wide area coverage for a limited number of users with moderate bandwidth. The future telecommunication will provide the same services in a wireless fashion as provided by fixed network these days and thereby requiring high bandwidths. It is expected that future telecommunication users will be neither willing to sacrifice functionality for the added value of mobility nor to pay more for it—mainly because he will hardly be using any other stationary telecommunication devices. Third generation mobile systems proposals such as UMTS and IMT-2000 only partially address these requirements by providing mobile internet services, with up to 2 Mbps in certain areas. Thus future mobile and wireless applications will require significantly higher data rates and significantly reduced costs per transmitted bit as compared to third generation systems. These requirements on data rate, link quality, spectral efficiency, and mobility cannot be met with conventional beamforming. Therefore new beamforming techniques are essential to increase the spectral efficiency of wireless communication systems. This paper provides the results achieved through use of a new technique Fractional Fourier transform (FRFT) based beamforming which is especially useful in moving and accelerating source problem. The conventional Minimum Mean Squared Error (MMSE) beamforming in the frequency domain or spatial domain becomes a special case of optimal beamforming with FRFT. The advantage of the proposed optimum FRFT domain beamformer is the practical consideration that the synthesis or analysis of the FRFT can be implemented with the same complexity as the conventional Fast Fourier Transform (FFT).

Additional information

Notes on contributors

Rajesh Khanna

Rajesh Khanna was born in Ambala, India. He received BSc (Engg) degree in Electronics & Comm. in 1988 from Regional Engineering College, Kurkshetra and ME degree in 1998 from Indian Institute of Sciences, Bangalore. He was with Hartron R&D centre till 1993. Until 1999, he was in All India Radio as Assistant Station Engineer. Presently he is working as Assistant Professor in the department of Electronics & Communication at Thapar Institute of Engineering & Technology, Patiala. He is also pursuing his PhD in the area of adaptive antennas for mobile communication. He has published 12 papers in national and International conferences.

Kulbir Singh

Kulbir Singh was born in Batala, India. He received his BTech degree in Instrumentation Engg in 1997 from Punjab Technical University, Jalandhar and ME degree in 2000 from Thapar Institute of Engg and Tech., Patiala. He is now working as Lecturer in the Department of Electronics & Communication at Thapar Institute of Engineering & Technology, Patiala. He is pursuing his PhD in the area of Fractional Fourier transforms and their applications to Signal Processing. He has published 11 papers in national and International conferences. His research interest includes FRFT, Image processing, Wavelets, DSP.

Rajiv Saxena

Rajiv Saxena was born in Gwalior, India. He received his BE degree in Electronics and Telecommunication Engineering from Jabalpur University, ME degree in Elect Engg from Jiwaji University, Gwalior and PhD from University of Roorkee in 1982, 1990 and 1996 respectively. He worked as an engineer in GRASIM and Reliance Textile Industries till 1983. In 1984 he joined Electronics Engineering Department of Madhav Institute of Technology and Sciences, Gwalior as Lecturer. He became Reader in 1990 and Professor in 2002. Presently he is Principal Rustam Ji Institute of Technology, BSF Academy, Tekanpur Distt.—Gwalior (MP). He has published more than 53 papers in various national and International Journals and conferences. His research interests include wireless and mobile communication and Digital Signal Processing.

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