i-manager Publications

i-manager's Journal on Communication Engineering and Systems (JCS)

Current Issue Vol. 13 Issue 2

Design and Development of Patient Care Voice Actuated Bed in Hospital
A Low Profile Dual U Shaped Monopole Antenna for WLAN/WiMAX/C Band Applications
A Miniaturized Dual L Shaped with Truncated Ground Rectangular Monopole Antenna for 5G and Wireless Communications
A Centre C-Shaped Dual Band Rectangular Monopole Antenna for Wi-Fi and Wireless Communication
Impact of Subchannel Symbol Rates on WSS Filtering Penalty in Elastic Optical Networks: A Comparative Study

Most Cited

Volume 3 Issue 3 May - July 2014

Research Paper

Frame Error Rate Performance for Adaptive M-QAM / S-OFDM Based Wireless Systems

A. Raja* , V. Thulasi Bai**

* Research Scholar, Sathyabama University, Chennai, India

** Professor and Dean, Department of ECE, Prathyusha Institute of Technology and Management, Chennai, India

Raja, A., and Thulasibai, V. (2014). Frame Error Rate Performance for Adaptive M-QAM / S-OFDM Based Wireless Systems. i-manager’s Journal on Communication Engineering and Systems, 3(3), 1-6. https://doi.org/10.26634/jcs.3.3.3176

Abstract

OFDM is an high data rate transmission modulation scheme which has complexity in wireless channels and can be merged with scalability for improving reliability of system called S-OFDM. In this paper, the authors proposed a performance analysis of Frame Error Rate (FER) for hybrid S-OFDM system in Rayleigh channel. The proposed scheme is shown to achieve lower Bit Error Rate (BER) and capturing more efficient receiver of multipath energy. Selecting a fraction of subcarriers with conjugate symmetric inputs to achieve the spreading. A channel SNR versus BER for both time and frequency for a 512-subcarrier OFDM with single-transmitter and single-receiver systems over an indoor wireless channel. The performance is evaluated for an S-OFDM system based on the IEEE 802.11. Simulation results shows, that the proposed scheme can achieve low BER and FER for a QAM- S-OFDM Symbols. The average channel SNR is 10 dB. The 16-QAM and 64-QAM are used in cable modem and many wireless technology applications.

References

[1]. Cheong Yui Wong, Roger S. Cheng, Khaled Ben Letaief, and Ross D. Murch, (1999). “Multiuser OFDM with Adaptive Subcarrier, Bit, and Power Allocation,” IEEE Journal on selected areas in communications, Vol. 17, No. 10.

[2]. Khalid El Baamrani, Abdellah Ait Ouahman, Victor P. Gil Jim ´Enez, Ana Garcia Armada and Said Allaki, (2006). “Subcarrier and Power Allocation for the Downlink of Multiuser OFDM Transmission,” Wireless Personal Communications, 39:(4) 457–465. www.researchegate.net.

[3]. C. Y. Wong, R. S. Cheng, K. B. Letaief, and R. D. Murch, (1999). “Multiuser OFDM system with adaptive subcarrier, bit, and power allocation,”IEEE J.Select. Areas Commun, Vol. 17, pp. 1747-1758.

[4]. Z. Shen, J. G. Andrews, B. L. Evans, (2005). “Adaptive resource allocation in multiuser OFDM systems with proportional rate constraints,” IEEE Trans. wireless commun, Vol. 4, pp. 2726-2737.

[5]. J. Hui, and Y. Zhou, “Enhanced rate adaptive resource allocation scheme in downlink OFDMA system,” in Proc. IEEE VTC 2006-Spring, Vol. 5, pp. 2464-2468.

[6]. Bin Da and C.C.Ko, “Dynamic Subcarrier Sharing Algorithms for Uplink OFDMA Resource Allocation,” in Proc.IEEE ICICS, 2007, Vol.1, pp.0983-7.

[7]. L. Hanzo, W.T. Webb, T. Keller, “Single- and Multi-carrier Quadrature Amplitude Modulation”. www.mobile.ecs. soton.ac.uk

[8]. Sarah Kate Wilson, R. Ellen Khayata and John M. Cioffi, (1994). ”16-QAM modulation with orthogonal frequencydivision multiplexing in a Rayleigh-fading environment", In Proc. VTC-1994, pp. 1660-1664, Stockholm, Sweden.

[9]. Peter Hoeher, (1991). “TCM on frequency-selective th land-mobile fading channels", In Proc. of the 5 Tirrenia International Workshop on Digital Communications, Tirrenia, Italy.

[10]. Min li imec, leuven, (2007). ”The quality-energy scalable ofdma modulation for low power transmitter and vliw processor based implementation.” in global Telecommunications Conference, Globecom '07. IEEE.

[11]. IEEE 802.11 specification – “Orthogonal frequency division multiplexing (OFDM) PHY specification for the 5 GHz band” – Chapter 17

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Research Paper

Performance Analysis of Co-Operative Spectrum Sensing Using Rayleigh Fading Channel in Cognitive Radio

Yamini verma* , K. Neelam Dewangan**

* PG Scholar, Department of Electronics and Telecommunication, Chhatrapati Shivaji Institute of Technology, Durg, Chhattisgarh.

** Department of Electronics and Telecomm, Chhatrapati Shivaji Institute of Technology, Durg Chhattisgarh, India.

Verma, Y., and Dewangan, K. N. (2014). Performance Analysis of Co-Operative Spectrum Sensing Using Rayleigh Fading Channel in Cognitive Radio. i-manager’s Journal on Communication Engineering and Systems, 3(3), 7-13. https://doi.org/10.26634/jcs.3.3.3177

Abstract

One of the emerging techniques in wireless communication is cognitive radio which is used for the efficient utilization of radio frequency spectrum. One important requirement of cognitive radio is spectrum sensing. In this paper, various types of spectrum sensing techniques are mentioned. Cooperative sensing seemed to be the best method among all spectrum sensing techniques applied to overcome the problem of detection and false alarm associated by using single user. This paper studies the cooperative spectrum sensing scheme as means of optimizing the sensing performance in Rayleigh channels. Plot of SNR versus probability of detection for different values of false alarm is shown in this paper. All this output is achieved using MATLAB.

References

[1]. Srinu.S, Samrat L. Sabat, (2013). "Cooperative Spectrum Sensing Under Noisy Control Channel for Cognitive Radio Network". IEEE School of Physics University of Hyderabad, pp 1-5.

[2]. Saada.W.K, Ismaila.M, Nordina.R and el-saleh.A.Aug 2013). "On the performance of cooperative spectrum sensing of cognitive radio networks in AWGN and Rayleigh fading environments". KSII transactions on internet and information systems, Vol.7,No. 8.

[3]. Verma.P.K, Taluja.S, Dua.R.L, (2012). “Performance analysis of Energy Detection, Matched filter detection & cyclostationary feature detection spectrum sensing techniques," International Journal Of Computation Engineering Research, Vol.2(5), pp.20-21.

[4]. Chaudhari.S, Lunden.J, Koivunen.V, and Poor.H, (2012). "Cooperative sensing with imperfect reporting channels: Hard decisions or soft decisions?" IEEE Transactions on Signal Processing, Vol. 60, No. 1, pp.18-28.

[5]. Subhedar.M and Birajdar.G (2011). "Spectrum sensing technique in cognitive radio network: A survey" International Journal of Next-Generation Networks (IJNGN), Vol.3, No.2.

[6]. Zhang Lie (2010). "Performance Analysis of Cooperative Spectrum Sensing Algorithm for Cognitive Radio Networks" International Conference On Computer Design And Applications (ICCDA) .

[7]. Duan.D and Yang.L, (2010). "Cooperative diversity of spectrum sensing for cognitive radio systems," IEEE transactions on signal processing, Vol. 58, No. 6, pp. 3218–3227.

[8]. Srinu. S, Sabat.S.L, and Udgata.S, (2010). "FPGA implementation of cooperative spectrum sensing for cognitive radio networks," in IEEE proceedings, UKIWCWS, pp. 1–5.

[9]. T. Yucek and H. Arslan, (2009). "A survey of spectrum sensing algorithms for cognitive radio applications," IEEE Communications Surveys and Tutorials, Vol. 11, No. 1, pp. 116 –130.

[10]. Letaief ben.k and Zhang. W, (2009). "Cooperative communications for cognitive radio networks," in IEEE proceedings, pp. 878–893.

[11]. Xing.C and Zhi-song.B, (2008). "Detection efficiency of cooperative spectrum sensing in cognitive radio network," Journal of china Universities of posts and telecommunications, Vol. 15, No. 3, pp. 1–7.

[12]. Liang.Y.C, Zeng. Y, Peh.E and Hoang.A, (2008). "Sensing-Throughput Tradeoff for Cognitive Radio Networks," IEEE TRANS Wireless Communications, Vol. 7, pp. 1326-1337.

[13]. Ghasemi.A and E. S Sousa, (Nov. 2005). "Collaborative spectrum sensing for opportunistic access in fading environments," in Proc.1, IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks, Baltimore, USA, pp.131-136.

[14]. Haykin.S, (Feb 2005). "Cognitive radio: Brainempowered wireless communications," IEEE Journal on Selected Areas in Communications, Vol. 23, No. 2, pp. 201–219.

[15]. Cabric.D, Mishra.S.M, and Brodersen R.W., (Nov. 2004). "Implementation issues in spectrum sensing for cognitive radios," in Proc. of Asilomar Conf on Signals, Systems, and Computers, Pacific Grove, CA, USA, pp. 772 – 776.

[16]. Stotas.S and Nallanathan.A (JAN 2012). " On the throughput and spectrum sensing enhancement of opportunistic spectrum access cognitive radio networks", IEEE transaction on wireless communication, Vol.11, No. 1.pp.1536-1276.

[17]. Sahai.A, Hoven.N, and Tandra.R, (Oct 2004). " Some fundamental limits on cognitive radio," in Proc. Allerton Conf. on Commun., Control and Computing, Monticello, Illinois.

[18]. J. Mitola and G. Q. Maguire, (Aug. 1999). "Cognitive radio: Making software radios more personal," IEEE Personal Commun., Vol. 6, pp. 13-18.

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Research Paper

MSE and SER Compare For LS, MMSE and SMMSE for BCE Technique in OFDM

Divya Pandey* , K. Neelam Dewangan**

*PG Scholar, Department of Communication Engineering, Chhattisgarh Swami Vivekanand Technical University (CSVTU) Bhilai, Chhattisgarh.

**Department of Electronics and Telecomm, Chhatrapati Shivaji Institute of Technology, Durg Chhattisgarh, India.

Pandey, D., and Dewangan, K. N. (2014). MSE and SER Compare For LS, MMSE and SMMSE for BCE Technique in OFDM. i-manager’s Journal on Communication Engineering and Systems, 3(3), 14-21. https://doi.org/10.26634/jcs.3.3.3178

Abstract

Orthogonal frequency division multiplexing (OFDM) technique is the modulation technique provides less bandwidth usage and speed communication and hence preferred in many areas now a days. Channel estimation techniques are used to know the behavior of the channel and then that information is further used by receiver to eliminate the irregularities introduced by channel on transmitted signal. This paper includes Block type pilot assisted channel estimation technique (BCE).least square (LS), minimum mean square error (MMSE) and simplified minimum mean square error (SMMSE) techniques are used here. SMMSE technique is simplified MMSE technique which is similar to MMSE but with reduced complexity. The results are obtained by using MATLAB software. Performance evaluation is done by comparing values of mean squared error (MSE) and symbol error rate (SER) for different values of SNR. Performance of LS in comparison with other two techniques is less. MMSE and SMMSE have almost same performance, seen from results.

References

[1]. Bhoyar, D. B., & Niranjane, V. B. (2013). “Channel Estimation for MIMO-OFDM Systems”. International Journal of Engineering Research and Applications (IJERA), Vol.2, No.1, pp.044-050.

[2]. Beek, J. J., Edfors, O., Sandell, M., Wilson, S. K. & Borjesson, P. O. (1995). “On channel estimation in OFDM systems”. Chicago: IEEE 45th Vehicular Technology Conference, Vol.2, pp.815-819.

[3]. Coleri, S., Ergen, M., Puri, A., & Bahai, A. (2002). Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems”. IEEE transactions, Vol.3, pp.223-229.

[4]. Doukopoulos, G., & Moustakides, G. V. (2006). “Blind adaptive channel estimation in OFDM”. IEEE transaction on wireless communication. IEEE, Vol.5, No.7, pp.1716-1725.

[5]. Ergen, M., & Colreri, S. (2002). “A Survey On Channel Estimatin Techniques Based On Pilot Arrangement In OFDM System”. Paris, Vol.48, No.3, pp.223-229.

[6]. Ghauri1, S. A., Alam, S., Farhan, M. S., & Ali, A. (2013). “Implementation Of OFDM And Channel Estimation Using LS And MMSE Estimators”. International Journal of Computer and Electronics Research, Vol.2, No.1, pp.41- 46.

[7]. Geoffrey, Ye Li. (2000). “Pilot-Symbol-Aided Channel Estimation for OFDM in Wireless Systems”. IEEE, Vol.49, No.4.

[8]. Harris, F. (2004). “Orthogonal Frequency Division Multiplexing OFDM”. San Diego State University: Cubic Signal Processing Chair, Vehicular Technology Conference.

[9]. Khan, L. U., Khan, N., Khattak, M. I., & Shafi, M. (2014). “LS Estimator: Performance Analysis for Block-Type and Comb-Type Channel Estimation in OFDM System”. UET Peshawar: IEEE. pp.420-424.

[10]. Khan, L. U., Khan, G. M., Mahmud, S. A., & Sabir, Z. (2013). “Comparison of Three Interpolation Techniques in Comb-Type Pilot-Assisted Channel Coded OFDM System”. Advanced Information Networking and Applications Workshops (WAINA). 27th International Conference.

[11]. Khan, Md. N. I., & Alam, Md. J. (2014). “Efficient Scheme For Channel Estimation In OFDM”, Journal Of Networks. Academy Publisher, Vol.17, No.7, pp.1352-1355.

[12]. Kansal, L., Kansal, A., & Singh, K. (2011). “Performance Analysis of MIMO-OFDM System Using QOSTBC Code Structure for M-PSK”. Signal Processing: An International Journal (SPIJ). Vol.5, No.2, pp.19-32.

[13]. Liu, H., & Li, G. (2005). “OFDM-based Broadband Wireless Networks. Design and optimization”. New jersey ; John Wiley & sons. pp.251

[14]. Manasseh, E., Ohno, S., & Nakamoto, M. (2013). “Pilot symbol assisted channel estimation for OFDM-based cognitive radio systems”. EURASIP Journal on Advances in Signal Processing, pp.1-11.

[15]. Morelli, M., & Mengali, U. (2001). “A Comparison of Pilot Aided Channel Estimation Methods for OFDM Systems”. IEEE Transactions On Signal Processing, Vol.49, No.12, pp.3065-3073.

[16]. Prasad, R. (2004). “OFDM for wireless communication systems”. Universal Personal Communication Series.

[17]. Shen, Y., & Martinez, Ed. (2006, Proceedings of 2014). “Channel Estimation in OFDM Systems. Pakistan, Islamabad: Free scale Semiconductor”, AN3059 Inc. 11th International Bhurban Conference on Applied Sciences & Technology (IBCAST), pp.1-15.

[18]. Saleem, S., & Islam, Q. Ul. (2011). “Performance and Complexity Comparison of Channel Estimation Algorithms for OFDM System”. IJECS-IJENS, Vol.11, No.2, pp.6-11.

[19]. Song, B., Gui, L., & Zhang, W. (2006). “Comb type pilot aided channel estimation in OFDM systems with transmit diversity”. IEEE Transactions.

[20]. Xie, H., Guillaume, A., Wang, Y., Diouris, J. F., & Feng, S. (2011). “Robust threshold compressed sensing based sparse multipath channel estimation in OFDM system. Information”, Communications and Signal Processing (ICICS) 8th International Conference. pp.1-5.

[21]. Xiao, Y. (2003). “Orthogonal Frequency Division Multiplexing Modulation And Inter Carrier Interference Cancellation”. Dalian university of technology.

[22]. Yang, L., Ren, G., & Qiu, Z. (2010). “Novel noise reduction algorithm for LS channel estimation in OFDM system with frequency selective channels”. Communication Systems (ICCS): IEEE International Conference, pp.478-482.

[23]. Pandey, D., & Dewangan, N. (2014). “A Survey on Channel Estimation Techniques in OFDM System”. International Journal of Research in Computer and Communication technology.

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Research Paper

A Comparative Analysis of Reversible Data Hiding in H.264/AVC and H.265/HEVC Video Streams

kiruthika.T* , P.Sundaravadivel**

* PG Scholar in Embedded System Technologies, KSR College of Engineering,Tiruchencode, Namakkal, India.

** Assistant Professor, KSR College of Engineering,Tiruchencode, Namakkal, India.

Kiruthika,T., and Sundaravadivel, P. (2014). A Comparative Analysis of Reversible Data Hiding in H.264/AVC and H.265/HEVC Video Streams. i-manager’s Journal on Communication Engineering and Systems, 3(3), 22-27. https://doi.org/10.26634/jcs.3.3.3179

Abstract

In the course of the past decade, data hiding technologies had progressed from limited use to pervasive deployment. With the swift advancement of smart mobile devices, the need to protect valuable exclusive information has generated a surplus new methods and technologies. Using cryptographic techniques to encrypt data before transmission may overcome any type of security problems. But the camouflaged appearance of the encrypted data may arouse suspicion. A technique for hiding data with two level of security to embed data along with good perceptual quality and high payload capacity is proposed. This gives rise to improved version of dual steganography which will provide better security. An improved scheme of data hiding directly in the compressed version of H.264/AVC video stream and H.265/HEVC video stream is proposed, which includes the following three parts, i.e., data encryption, video compression, data embedding, and data extraction. A comparative analysis is made which proves that H.265 video stream provides a better compression and at the same time preserving the video quality. The scheme can ensure both the format compliance and the strict file size preservation.

References

[1]. Vadi Dipcin,Melih Pazarci (2003). “Data embedding in scrambled digital video”, in proceedings of the 8th IEEE International Symposium on Computers and Communication, pp. 498-503.

[2]. G. Bjontegaard, T.Wiegand, G.J.Sullivan (July 2003). “Overview of the H.264/AVC standard,” IEEE Trans Circuits Syst Video Technol, Vol. 13, No. 7, pp. 560–576.

[3] . Y.Won, Kim, S.M, Kim,S.B, Hong, C.S. (2007). “Data hiding on H.264/AVC compressed videos”, Proceedings of ICIAR LNCS, Vol. 4633, pp. 698–707.

[4]. Minkyu Choi, Arup Kumar Bhaumik, (June 2009). “Data Hiding in Video”, International Journal of Database Theory and Application, M. Young, The Technical Writer's Handbook. Mill Valley, CA: University Science, Vol.2, No.2M.

[5]. A. Saxena, J.Han, and K.Rose, (Mar. 2010) “Towards jointly optimal spatial prediction and adaptive transform in video and image coding,” in proc IEEE Int Conf. acoustics, speech and signal processing (ICASSP), pp. 726–729.

[6] Y. Liu, J. G. Jiang, Z. P. Su, G. Zhang, and S. Xing, (2010). “An improved selective encryption for H.264 video based on intra prediction mode scrambling”, J. Multimedia, Vol. 5, No. 5, pp. 464–472.

[7]. Z. Shahid, M. Chaumont, and W. Puech, (May 2011) “Fast protection of H.264/AVC by selective encryption of CAVLC and CABAC for I and P frames”, IEEE Trans. Circuits Syst. Video Technol, Vol. 21, No. 5, pp. 565–576.

[8] H. Guermazi, C.A.Fernandes and F. Kossentini (July 2011). “ALF using vertical-size 5 filters with up to 9 coefficients,” JCTVC-F303.

[9]. C.M. Fu, C.Y.Chen, and S. Lei,( Oct. 2011). “Sample adaptive offset for HEVC,” in Proc. int. workshop on multimedia signal processing (MMSP), pp.1-5.

[10] C.Y.Chen, C.Y.Tsai, C.M.Fu, and S.Lei, (Nov. 2011). “One-pass encoding algorithm for adaptive loop filter in high-efficiency video coding,” in proc visual communications and image processing (VCIP), pp.1-4.

[11] J. Lainema, K.Ugur, and A.Hallapuro (Nov. 2011). “Single entropy coder for HEVC with high throughput binarization mode,” JCTVC-G569.

[12] . D. W. Xu and R. D. Wang, (2011). “Watermarking in H.264/AVC compressed domain using Exp-Golomb code words mapping”, Vol. 50, No. 9, pp. 097-402.

[13]. Advanced Video Coding for Generic Audiovisual Services, ITU, Geneva, Switzerland, Mar. 2005.

[14] T. Stutz and A.Uhl (Mar 2012). “A survey of H.264 AVC/SVC encryption”, IEEE trans. Circuits Syst Video Technol, Vol.22, No.3, pp. 325–339.

[15]. B. Bross, W.J Han, G. J. Sullivan, J.R.Ohm, and T. Wiegand,( Feb. 2012). “High efficiency video coding (HEVC) text specification,” JCTVC H1003.

[16]. M. Rama Koteswara Rao, Bhookya Nageswararao Naik, (August 2012). “A robust secured datahiding technique in videos and associated estimated artifacts” International Journal of Engineering Research and Applications (IJERA), Vol. 2, pp.1577-1582.

[17]. D.W. Xu, R. D. Wang, and J.C. Wang, (2012). “Prediction mode modulated data-hiding algorithm for H.264/AVC”, J. Real-Time Image Process., Vol. 7, No. 4, pp. 205–214.

[18]. G. J. Sullivan,W.J. Han, T.Wiegand (Dec. 2012) “Overview of high efficiency video coding (HEVC) standard,” in IEEE Trans. on circuits and syst. for video technol., Vol. 22, No. 12, pp.1649-1668.

[19]. M. N. Asghar and M. Ghanbari, (Mar. 2013). “An efficient security system for CABAC bin-strings of H.264/SVC”, IEEE Trans Circuits Syst Video Technol, Vol. 23, No. 3, pp. 425–437.

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Review Paper

Survey on Mutual Coupling Reduction Techniques for Imaging Radar Application

C. Mekala* , P. Saranya, V. Sathya Narayanan*

- PG Scholar, Department of Communication Systems, Kongu Engineering College, Erode, Tamil Nadu.

Assistant Professor, Department of Electronics and Communication Engineering , Kongu Engineering College, Erode, Tamil Nadu.

Mekala, C., Saranya, P., Narayanan, V. S. (2014). Survey on Mutual Coupling Reduction Techniques for Imaging Radar Application. i-manager’s Journal on Communication Engineering and Systems, 3(3), 28-32. https://doi.org/10.26634/jcs.3.3.3181

Abstract

Mutual Coupling is the general problem occurring in arrays used in Imaging Radars. It is the electromagnetic phenomena, which is produced from absorption of radiating energy of one antenna by another. It significantly affects input impedance of the antenna, performance of array processing algorithm, magnitude and phase of the re-radiated waves, radiation pattern and also the received element voltage. Hence this paper provides the review of different methods to protect system from these effects by reducing mutual coupling. This survey on mutual coupling reduction techniques of antenna array in Imaging RADARs are discussed deeply. The discussion initiates with the effect of mutual coupling in antenna and covers the topics such as, parameters affected by coupling effect, coupling reduction techniques and also about the functionality of these techniques in performance improvement. Concludes with the selection of specific reduction scheme for suitable application. This survey also concentrates on comparison of coupling effect reduction through arrangement of array element in square and triangular lattice of array.

References

[1]. Guiping Zheng ; Dept. of Electr. Eng., Mississippi Univ., MS ; Kishk, A.A. ; Glisson, A.W. ; Yakovlev, A.B., (9-14 July 2006). “A mutual coupling reduction technique for dielectric resonator antennas over AMC surface”. Antennas and Propagation Society International Symposium, IEEE, pp.377 - 380.

[2]. Shaker, G., Rafi, G.; Safavi-Naeini, S.; Sangary, N. (5-11 July 2008). “A synthesis technique for reducing mutual coupling between closely separated patch antennas”. Antennas and Propagation Society International Symposium IEEE., pp.1-4.

[3]. Abdallah, Y. ; Menudier, C.; Thevenot, M.; Monediere, T. (April 2013). “Investigations of the Effects of Mutual Coupling in Reflectarray Antennas”. Antennas and Propagation Magazine, IEEE, Vol. 55 (2 ), pp.49-61.

[4]. Gaikwad. G.N, Dixit. V.V, Ganage.D.G, Chincholkar. Y.D, Alwandi. U.P, Pawar. S.R and Kolhe. J.P, (March 2011). “Mutual coupling reduction between microstrip antennas using electromagnetic bandgap structure”. ICTACT Journal on Communication Technology, Vol. 02 ( 0 1), pp.241-245

[5]. Raimondo, L. ; De Paulis, F.; Orlandi, A., (2010). “A Simple and Efficient Design Procedure for Planar Electromagnetic Bandgap Structures on Printed Circuit Boards”. Electromagnetic Compatibility, IEEE Transactions. Vol. 53 (2), pp.482 - 490

[6]. Balamati Choudhury, Sangeetha Manickam, and R. M. Jha, (2013). “Soft Computing Techniques for Mutual Coupling Reduction in Metamaterial Antenna Array”. Journal of Optimization, pp.7.

[7]. Lakshmi, C.R, (2013). “A Review on Mutual Coupling in Antenna Arrays and Decoupling Methods in MRI Antenna Arrays”. OSR Journal of Engineering (IOSRJEN)”. Vol. 3 (12), pp. 46 - 49.

[8]. F.Y. Zulkifli, E.T. Rahardjo, and D. Hartanto, (2010). "Mutual coupling reduction using dumbbell defected ground structure for multiband microstrip antenna array," Progress In Electromagnetics Research Letters, Vol. 13, pp 29-40.

[9]. Hon Tat Hui, (2007). “Decoupling Methods for the Mutual Coupling Effect in Antenna Arrays: A Review”. Recent Patents on Engineering. Vol ,1 (2), pp.187-193.

[10]. Hui HT1, Li BK, Crozier S., (2006). “A new decoupling method for quadrature coils in magnetic resonance imaging”. IEEE Trans Biomed Eng., Vol. 53 (10), pp.2114-6.

[11]. Wallace, J.W., Jensen, M.A. (2004). “Mutual coupling in MIMO wireless systems: a rigorous network theory analysis”. Wireless Communications, IEEE Transactions on. Vol. 3 (4), pp.1317-1325.

[12]. Aumann, H.M.; Fenn, A.J.; Willwerth, F.G. (1989). “Phased array antenna calibration and pattern prediction using mutual coupling measurements”. Antennas and Propagation, IEEE Transactions on . Vol, 37 (7), pp.844-850.

[13]. Yongxi Qian ; Deal, W.R.; Kaneda, N.; Itoh, T. (1999). “A uniplanar quasi-Yagi antenna with wide bandwidth and low mutual coupling characteristics”. Antennas and Propagation Society International Symposium, Vol. 2 (1), pp.924-927.

[14]. Fredrick, Jonathan D; Yuanxun Wang; Itoh, T., (2004). “Smart antennas based on spatial multiplexing of local elements (SMILE) for mutual coupling reduction”. Antennas and Propagation, IEEE Transactions on. Vol. 52 (1), pp.106- 114.

[15]. Noordin, N.H.; El-Rayis, A.O.; Haridas, N.; Flynn, B. et.al (2011). “Triangular lattices for mutual coupling reduction in patch antenna arrays”. Antennas and Propagation Conference (LAPC), Loughborough , pp.1-4.

i-manager's Journal on Communication Engineering and Systems (JCS)

Current Issue Vol. 13 Issue 2

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Volume 3 Issue 3 May - July 2014

Frame Error Rate Performance for Adaptive M-QAM / S-OFDM Based Wireless Systems

A. Raja* , V. Thulasi Bai**

* Research Scholar, Sathyabama University, Chennai, India ** Professor and Dean, Department of ECE, Prathyusha Institute of Technology and Management, Chennai, India

Raja, A., and Thulasibai, V. (2014). Frame Error Rate Performance for Adaptive M-QAM / S-OFDM Based Wireless Systems. i-manager’s Journal on Communication Engineering and Systems, 3(3), 1-6. https://doi.org/10.26634/jcs.3.3.3176

Abstract

References

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Performance Analysis of Co-Operative Spectrum Sensing Using Rayleigh Fading Channel in Cognitive Radio

Yamini verma* , K. Neelam Dewangan**

* PG Scholar, Department of Electronics and Telecommunication, Chhatrapati Shivaji Institute of Technology, Durg, Chhattisgarh. ** Department of Electronics and Telecomm, Chhatrapati Shivaji Institute of Technology, Durg Chhattisgarh, India.

Verma, Y., and Dewangan, K. N. (2014). Performance Analysis of Co-Operative Spectrum Sensing Using Rayleigh Fading Channel in Cognitive Radio. i-manager’s Journal on Communication Engineering and Systems, 3(3), 7-13. https://doi.org/10.26634/jcs.3.3.3177

Abstract

References

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MSE and SER Compare For LS, MMSE and SMMSE for BCE Technique in OFDM

Divya Pandey* , K. Neelam Dewangan**

*PG Scholar, Department of Communication Engineering, Chhattisgarh Swami Vivekanand Technical University (CSVTU) Bhilai, Chhattisgarh. **Department of Electronics and Telecomm, Chhatrapati Shivaji Institute of Technology, Durg Chhattisgarh, India.

Pandey, D., and Dewangan, K. N. (2014). MSE and SER Compare For LS, MMSE and SMMSE for BCE Technique in OFDM. i-manager’s Journal on Communication Engineering and Systems, 3(3), 14-21. https://doi.org/10.26634/jcs.3.3.3178

Abstract

References

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A Comparative Analysis of Reversible Data Hiding in H.264/AVC and H.265/HEVC Video Streams

kiruthika.T* , P.Sundaravadivel**

* PG Scholar in Embedded System Technologies, KSR College of Engineering,Tiruchencode, Namakkal, India. ** Assistant Professor, KSR College of Engineering,Tiruchencode, Namakkal, India.

Kiruthika,T., and Sundaravadivel, P. (2014). A Comparative Analysis of Reversible Data Hiding in H.264/AVC and H.265/HEVC Video Streams. i-manager’s Journal on Communication Engineering and Systems, 3(3), 22-27. https://doi.org/10.26634/jcs.3.3.3179

Abstract

References

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Survey on Mutual Coupling Reduction Techniques for Imaging Radar Application

C. Mekala* , P. Saranya**, V. Sathya Narayanan***

*-** PG Scholar, Department of Communication Systems, Kongu Engineering College, Erode, Tamil Nadu. *** Assistant Professor, Department of Electronics and Communication Engineering , Kongu Engineering College, Erode, Tamil Nadu.

Mekala, C., Saranya, P., Narayanan, V. S. (2014). Survey on Mutual Coupling Reduction Techniques for Imaging Radar Application. i-manager’s Journal on Communication Engineering and Systems, 3(3), 28-32. https://doi.org/10.26634/jcs.3.3.3181

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* Research Scholar, Sathyabama University, Chennai, India

** Professor and Dean, Department of ECE, Prathyusha Institute of Technology and Management, Chennai, India

* PG Scholar, Department of Electronics and Telecommunication, Chhatrapati Shivaji Institute of Technology, Durg, Chhattisgarh.

** Department of Electronics and Telecomm, Chhatrapati Shivaji Institute of Technology, Durg Chhattisgarh, India.

*PG Scholar, Department of Communication Engineering, Chhattisgarh Swami Vivekanand Technical University (CSVTU) Bhilai, Chhattisgarh.

**Department of Electronics and Telecomm, Chhatrapati Shivaji Institute of Technology, Durg Chhattisgarh, India.

* PG Scholar in Embedded System Technologies, KSR College of Engineering,Tiruchencode, Namakkal, India.

** Assistant Professor, KSR College of Engineering,Tiruchencode, Namakkal, India.

C. Mekala* , P. Saranya, V. Sathya Narayanan*

- PG Scholar, Department of Communication Systems, Kongu Engineering College, Erode, Tamil Nadu.

Assistant Professor, Department of Electronics and Communication Engineering , Kongu Engineering College, Erode, Tamil Nadu.