iosr-JECE   Volume-11 ~ Issue-6 ~ Nov-Dec 2016

Abstract: In computer vision robust feature detection, image matching are the latest concepts that most of the researchers have carried out in this field. Face recognition is also an important field of research. It is also considered one of the most prolific forms of biometrics. The personal identity based on geometric or statistical feature derived from face images are automatically recognised. This paper proposes various methods and algorithms used for face recognition and registration such as SIFT, SURF and FAST AFFINE. Feature extraction and feature matching are the steps of image registration and the accuracy of image registration depends on feature matching..........

Keywords: SIFT, SURF, FASF, Affine transform, and RANSAC.

[1] Y. Tian and S.G. Narasimhan. Globally optimal estimation of nonrigid image distortion. IJCV, 98(3):279–302, 2012.
[2] Barbara Zitova, Jan Flusser, "IMAGE REGISTRATION METHODS: A SURVEY",Image and Vision Computing 21 (2003) 977–1000
[3] Rochdi Bouchiha, Kamel Besbes,"AUTOMATIC REMOTE-SENSING IMAGE REGISTRATION USING SURF", International Journal of Computer Theory and Engineering, Vol. 5, No. 1, February 2013
[4] Andreas Haug, Stefan Hinterstoisser, 4 December 2005, "DESCRIPTION, DETECTION AND MATCHING OF IMAGE FEATURES – SIFT AND NEAREST NEIGHBOR SEARCH" from wwnavab.cs.tum.ed
[5] Bay, H., Tuytelaars, T., Gool, L.V. (2006). SURF: Speeded up robust features. In Computer Vision –ECCV 2006 : 9th European Conference on Computer Vision, 7-13 May 2006. Springer, Part II, 404-417.

Abstract: OFDM technology considered to be next generation mobile wireless communication technique against the multipath fading channel. OFDM is the effective method for the data transmission for fast speed communication. It has less complexity to implement and having distortion resistance.AlthoughOFDM having some PAPR problem which isthe major drawback for multicarrier transmission system which stimulus power inefficiency for RF section of the transmitter. It has larger no of subcarrier which are independent in nature, because of that its amplitude having highest peak value. In this paper Companding technique is used for reducing PAPR of OFDM system.

Keywords: Companding, Orthogonal Frequency Division Multiplexing (OFDM), Peak to Average Power Ratio (PAPR), Frequency Division Multiplexing (FDM), Multiple Input Multiple Output (MIMO), etc.

[1]. A.Sohail and M.N.Jafri, "Adaptive OFDM over Frequency Selective and Fast Fading Channel Using Blockwise Bit Loading Algorithm", IEEE International Conferenece on Wireless and Optical Communication Networks,pp. 1-4, July 2007.
[2]. J.Faezah and and K.Sabira "Adaptive Modulation for OFDM Systems" , International Journal of Communication Networks and Information Security (IJCNIS) Aug 2009
[3]. P.Kothai , R.Prabhu" PAPR Reduction in MIMO OFDM Using Adaptive SLM Scheme" International Journal for Research in Applied Science & Engineering Technology (IJRASET) May2015
[4]. M.I.Rahman, S.S.Das, Y.Wang, F.B.Frederiksen and R.Prasad, "Bit and Power Loading Approach for Broadband Multi-Antenna OFDM System", IEEE Transactions Communications, pp. 1689-1693, 2007.
[5]. Srinu Pyla, "PAPR reduction in OFDM systems using PTS and various modulation schemes", 978-1-4673-2818-0/13/$31.00 ©2013 IEEE.

Abstract: In 5G wireless communication, Cognitive Femtocell is modern technology that can satisfy the demand of cellular mobile communication in high density area (i.e. indoor , outdoor ,airport and home etc.) . In this network macro base station in macrocell and femto base station in femtocell are considered primary and secondary system. Macrocell User (MU) is called primary user and Femtocell User (FU) is called secondary user. One Macrocell cover more than one femtocells. Macrocell and Femtocell uses the same frequency channel. Spectrum allocation management function follows as........

Keywords: Cognitive radio, 5G, Macrocell, Femtocell , Femto-User, Fusion Center

[1]. Cheng-Xiang Wang, Heriot-Watt University and University of Tabuk, "Cellular Architecture and Key Technologies for 5G Wireless Communication Networks" ,IEEE Communications Magazine , February 2014.
[2]. Ekram Hossain and Monoware Hasan,"5G Cellular: Key Enabling Technologies and Research Challenges", IEEE Instrumentation & Measurement Magazine, Volume:18 ,Issue:3, Pages: 11 – 21, Year: 2015.
[3]. P. Demestichas, A. Georgakopoulos and D. Karvounas, K. Tsagkaris, V. Stavroulaki, J. Lu, C. Xiong, and J. Yao, "5G on the horizon: Key challenges for the radio-access network," IEEE Vehicular Technology Magazine, vol. 8, no. 3, pp. 47-53, Sept. 2013.
[4]. A. Zakrzewska, S. Ruepp, and M. Berger, "Towards converged 5G mobile networks - Challenges and current trends," in Proc. ITU Kaleidoscope Academic Conference, pp. 39-45, Jun. 2014.
[5]. Cognitive Radio,http://searchnetworking.techtarget.com/definition/cognitive-radio.