i-manager Publications

i-manager's Journal on Wireless Communication Networks (JWCN)

Current Issue Vol. 13 Issue 1

Most Cited

A Review on Optimized FFT/IFFT Architectures for OFDM Systems
Balanced Unequal Clustering AlgorithmFor Wireless Sensor Network
HHT and DWT Based MIMO-OFDM for Various ModulationSchemes: A Comparative Approach
Study and Comparison of Distributed Energy Efficient Clustering Protocols in Wireless Sensor Network: A Review
Diagnosis of Anemia using Non-Invasive Anemia Detector through Parametrical Analysis

Volume 5 Issue 1 April - June 2016

Research Paper

Extending Implementation- A Castalia with a Multimedia Sensor Node Framework

Hanafy Mahmoud Ali*

Assistant Professor, Department of Computers and Systems Engineering, Minia University, El Minia, Egypt.

Ali, H.M. (2016). Extending Implementation- A Castalia with a Multimedia Sensor Node Framework. i-manager's Journal on Wireless Communication Networks, 5(1), 1-10. https://doi.org/10.26634/jwcn.5.1.6018

Abstract

Currently available Wireless Sensor Network (WSN) tools may be adapted for the Wireless Multimedia Sensor Network (WMSN). However, this requires more effort to configure and tune such tools for the requirements of current WMSN. On the other hand, many extensions for available WSN tools were developed to extend their functionalities in order to support WMSN. Although this seems to solve the problem, such extensions are usually developed as layers or plugins over the existing ones, which introduce many performance issues. In this paper, Castalia is extended to support the multimedia content simulation. First, the general multimedia requirements are discussed and defined, then the Castalia is enhanced by adding the defined requirements.

References

[1]. P. Suriyachai, U. Roedig and A. Scott, (2012). “A Survey of MAC Protocols for Mission-Critical Applications in Wireless Sensor Networks”. IEEE Communications Surveys & Tutorials, Vol.14, No.2, pp.240-264.

[2]. M. Stehlik, (2011). “Comparison of Simulators for Wireless Sensor Networks”. (Masters Dissertation, Brno: Masaryk University, Faculty of Informatics).

[3]. Y. Zhang, N. Meratnia and P. Havinga, (2010). "Outlier Detection Techniques for Wireless Sensor Networks: A Survey”. IEEE Communications Surveys & Tutorials, Vol.12, No.2, pp.159-170.

[4]. I. Butun, S. D. Morgera and R. Sankar, (2014). “A Survey of Intrusion Detection Systems in Wireless Sensor Networks”. IEEE Communications Surveys & Tutorials, Vol.16, No.1, pp.266-282.

[5]. M. Chitnis, (2011). “A Framework to Support Wireless Multimedia Sensor Networks”. (Doctoral Dissertation, Pisa, Italy: ScuolaSuperioreSant'Anna, Pisa).

[6]. B. Harjito and S. Han, (2010). “Wireless Multimedia Sensor Networks Applications and Security Challenges”. In International Conference on Broadband, Wireless Computing, Communication and Applications, pp.842- 846.

[7]. Hanafy M. Ali, (2010). “Simulation of Wireless Multimedia Sensor Networks (WMSN)”. Retrieved from http://nsnam.isi.edu/nsnam/index.php/Main Page

[8]. OMNeT++ Project, (2010). Retrieved from http://www.omnetpp.org/

[9]. Lund University, (n.d.). “TrueTime: Simulation of Networked and Embedded Control Systems”. Retrieved from http://www.control.lth.se/truetime/

[10]. Opnet. Retrieved from http://www.opnet.com/

[11]. X. Zeng, R. Bagrodia and M. Gerla, (1998). “GloMoSim: a library for parallel simulation of large-scale th wireless networks”. In Proceedings of the 12 Workshop on Parallel and Distributed Simulations, Banff, Alberta, Canada.

[12]. INET, (2014). “INET Framework”. Retrieved from http://inet.omnetpp.org/

[13]. MiXiM, (2011). “MiXiM Project”. Retrieved from http://mixim.sourceforge.net/

[14]. The Castalia Simulation Model. Retrieved from http://castalia.npc.nicta.com.au/

[15]. PAWiS - A Simulation Framework for Wireless Sensor Networks. Retrieved from http://pawis.sourceforge.net/

[16]. C. Nastasi and A. Cavallaro, (2011). “WiSE-MNet: An experimental environment for wireless multimedia sensor networks”. Sensor Signal Processing for Defence (SSPD 2011), pp.1-5.

[17]. D. Rosário, Z. Zhao, C. Silva, E. Cerqueira and T. Braun, (2013). “An OMNeT++ framework to evaluate video transmission in mobile wireless multimedia sensor th networks”. In Proceedings of the 6 International ICST Conference on Simulation Tools and Techniques.

[18]. C. Pham, (2011). “A video sensor simulation model with OMNET++”. LIUPPA Labs, University of Pau, France. Retrieved from http://cpham.perso.univ-pau.fr/WSNMODEL/ wvsn.html

[19]. C. Pham and A. Makhoul, (2010). “Performance study of multiple cover-set strategies for mission-critical video surveillance with wireless video sensors”. In IEEE WiMob, pp.208-216.

[20]. OpenCV, (2015). OpenCV Organization Homepage. Retrieved from opencv.org [Accessed 2015].

[21]. Nvidia, (2015). Nvidia CUDA Zone - OpenCV. Retrieved from https://developer.nvidia.com/opencv [Accessed 2015].

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Research Paper

CPW-Fed Printed Slot Antenna for Wireless and Future Mobile Broad-Band Applications

Girijesh Giri* , G.S. Tripathi, Sudhanshu Verma*

* PG Scholar, Department of Electronics and Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

-* Faculty, Department of Electronics and Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

Giri,G., Tripathi, G.S., and Verma, S. (2016). CPW-Fed Printed Slot Antenna for Wireless and Future Mobile Broad-Band Applications. i-manager's Journal on Wireless Communication Networks, 5(1), 11-15. https://doi.org/10.26634/jwcn.5.1.6019

Abstract

In this paper, coplanar waveguide fed patch antenna with quad band application is presented. The proposed antenna 3 has a compact size of (50×30×1.6 mm ). The design consist four bands from (1.66 GHz to 2.2 GHz) centered at 1.80 GHz, is better for wireless application from (3.55GHz to 3.8 GHz) centered at 3.5 GHz for WIMAX, from (4.30 GHz to 5.07 GHz ) centered at 4.7 GHz and from (5.7 GHz to 6.02 GHz ) centered at 5.8 GHz for WLAN application. A good return loss of more than -20 dB are achieved which are making it compatible for various mobile broadband application. The objective of the proposed antenna is to cover the various L band and C band applications. Further, the proposed antenna has low profile which makes easy installation in different devices. The whole simulation is done by using HFSS-13 software.

References

[1]. Chih-Yu Huang and En-Zo-Yu, (2011). “A Slot monopole antenna for dual band WLAN application”. IEEE Antennas and Wireless Propagation Letters, Vol.10, pp.500-502.

[2]. W.-C. Liu, C.-M. Wu, and N.-C. Chu, (2010). “A compact CPW-fed slotted patch antenna for dual-band operation”. IEEE Antennas Wireless Propag. Lett., Vol.9, pp.110-113.

[3]. A.P. Saghati, M. Azarmanesh, and R. Zaker, (2010). “A novel switchable single- and multifrequency triple-slot antenna for 2.4-GHz Bluetooth, 3.5-GHz WiMax, and 5.8- GHz WLAN”. IEEE Antennas Wireless Propag. Lett., Vol.9, pp.534-537.

[4]. H. Jasik, (1961). Antenna Engineering Handbook. New York: McGraw-Hill, pp.1-3.

[5]. J. F. Li, B. H. Sun, S. L. Zuo, and Q. Z. Liu, (2009). “Design of combined PIFAs with high port-to-port isolation for GSM/DCS and WLAN mobile phones”. Electron. Lett., Vol.45, No.11, pp.532-533.

[6]. K.L. Wong and L. C. Chou, (2006). “Internal composite monopole antenna for WLAN/WiMAX operation in the laptop computer”. Microw. Opt. Technol. Lett., Vol.48, pp.868-871.

[7]. M.J. Ammanna, (2001). “The pentagonal planar monopole for digital mobile terminals; bandwidth considerations and modelling”. In Proc. Int. Conf. Antennas Propag., Vol.1, pp.82-85.

[8]. S. Chaimool and K.-L. Chung, (2009). “CPW-fed mirrored-L monopole antenna with distinct triple bands for WiFi and WiMAX applications”. Electron. Lett., Vol.45, No.18, pp.928-929.

[9]. T.-H. Kim and D.-C. Park, (2005). “Compact dualband antenna with double L-slits for WLAN operations”. IEEE Antennas Wireless Propag. Lett., Vol.4, pp.249-252.

[10]. K.G. Thomas and M. Sreenivasan, (2009). “Compact triple band antenna for WLAN/WiMAX applications”. Electron. Lett., Vol.45, No.16, pp.811-813.

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Research Paper

Performance Analysis of Evolutionary Algorithm for PAPR Reduction in OFDM System

Prabhneet Kaur* , Mangal Singh**

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

** Associate Professor, Department of Electronics and Telecommunication Engineering, Chhatrapati Shivaji Institute of Technology, Durg, India.

Kaur, P., and Singh, M. (2016). Performance Analysis of Evolutionary Algorithm for PAPR Reduction in OFDM System. i-manager's Journal on Wireless Communication Networks, 5(1), 16-22. https://doi.org/10.26634/jwcn.5.1.6020

Abstract

Orthogonal Frequency Division Multiplexing (OFDM) is a wireless transmission technique in which the digital data are transmitted in a radio environment at a very high speed. But one of the major drawbacks of OFDM system is, high peak to average power ratio which demands costly linear amplifiers with wide dynamic range. In this paper, less-complexity based partial transmit sequence technique is used for reducing the PAPR of OFDM system. PTS techniques can improve the PAPR statistics of an OFDM signals, but the computational complexity is a potential problem for the implementation in practical systems. Inorder to reduce this computational complexity, an optimization algorithm can be used. This paper shows the comparison between two population-based stochastic search techniques which is widely used in many scientific and engineering fields. Here, the Differential Evolutionary (DE) algorithm is compared with the Genetic Algorithm (GA).

References

[1]. H.L. Hung and Y.F. Huang, (2012). “Peak-to-average power ratio reduction in orthogonal frequency division multiplexing system using differential evolution-based partial transmit sequences scheme”. IET Comm., Vol.6, No.11, pp.1483-1488.

[2]. Saurabh Ghosh, Subhrajit Roy, Swagatam Das, Ajith Abraham & S.K. Minhazal Islam, (2011). “Peak-to- Average Power Ratio Reduction in OFDM Systems Using an Adaptive Differential Evolution Algorithm”. IEEE, pp.1941- 1948.

[3]. Chien-Erh Weng, Chuan-Wang Chang, Chuang- Hsien Chen and Ho-Lung Hung, (2013). “Novel Low- Complexity Partial Transmit Sequences Scheme for PAPR Reduction in OFDM Systems Using Adaptive Differential Evolution Algorithm”. Springer, pp.679-694.

[4]. M.N. Seyman and N. Taspinar, (2012). “Optimization of pilot tones using differential evolution algorithm in MIMO-OFDM systems”. Turk J Elec Eng & Comp Sci, Vol.20, No.1.

[5]. Jiang T. and Wu Y., (2008). “An Overview: Peak-toaverage power ratio reduction techniques for OFDM signals”. IEEE Trans. Broadcasting, Vol.54, No.2, pp.257- 268.

[6]. Wang, Xia, Songhua He, and Tao Zhu, (2014). “A Genetic-Simulated Annealing Algorithm Based on PTS Technique for PAPR Reduction in OFDM System”. In Computer Applications and Communications (SCAC), IEEE Symposium on, pp.120-124.

[7]. H. Liang, Y.R. Chen, Y.F. Huang, and C. H. Cheng, (2009). “A Modified Genetic Algorithm PTS Technique for PAPR Reduction in OFDM Systems”. In Proc. IEEE Asia-Pacific Conference on Communication, pp.182-185.

[8]. Hung and Ho-Lung, (2011). “Using evolutionary computation technique for trade-off between performance peak-to average power ration reduction and computational complexity in OFDM systems”. Computers & Electrical Engineering, Vol.37, No.1, pp.57-70.

[9]. S.H. Han and J.H. Lee, (2004). “PAPR reduction of OFDM signals using a reduced complexity PTS technique”. Signal Processing Letters, IEEE, Vol.11, No.11, pp.887-890.

[10]. M. Breiling, S. H. Muller-Weinfurtner, and J. B. Huber, (2011). “SLM peak power reduction without explicit side information”. IEEE Commun. Lett., Vol.5, pp.239-241.

[11]. Yang, Lin, Ru-Shan Chen, Yun-Ming Siu, and Kwok- Kai Soo, (2006). “PAPR reduction of an OFDM signal by use of PTS with low computational complexity”. Broadcasting, IEEE Transactions. Vol.52, No.1, pp.83-86.

[12]. Han, Seung Hee, and Jae Hong Lee, (2005). “An overview of peak-to-average power ratio reduction techniques for multicarrier transmission”. Wireless Communications, IEEE. Vol.12, No.2, pp.56-65.

[13]. S.S. Kim, M.J. Kim, and T.A. Gulliver, (2008). “PAPR Reduction of OFDM Signals Using Genetic Algorithm PTS Technique”. IEICE Trans. Commun., Vol.E91–B, No.4, pp.1194-1197.

[14]. Chen, Jung-Chieh, (2009). “Partial transmit sequences for peak-to-average power ratio reduction of OFDM signals with the cross-entropy method”. Signal Processing Letters, IEEE. Vol.16, No.6, pp.545-548.

[15]. Gao, Jing, Jin-kuan Wang, and Zhi-bin Xie, (2009). “A Novel PTS PAPR Reduction Algorithm with Low Computational Complexity in OFDM System”. Journal of Northeastern University (Natural Science), Vol.4.

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Research Paper

N-Shape Dielectric Resonator Antenna for Wireless Communication

Roshni Gupta* , Mangal Singh, Dipali Soren*

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

Associate Professor, Department of Electronics and Telecommunication Engineering, Chhatrapati Shivaji Institute of Technology, Durg, India.

* Professor, Department of Electronics and Telecommunication Engineering, Christian College of Engineering and Technology, Bhilai, India.

Gupta, R., Singh, M., and Soren, D. (2016). N-Shape Dielectric Resonator Antenna for Wireless Communication. i-manager's Journal on Wireless Communication Networks, 5(1), 23-28. https://doi.org/10.26634/jwcn.5.1.6021

Abstract

This paper presents the simulation study of an ultra-wideband Dielectric Resonator Antenna (DRA). The simulation study has been carried out using CST Microwave Studio Software. The design procedure and simulation results of the rectangular dielectric resonator antenna and N-shaped dielectric resonator antenna are compared. The proposed antenna is designed on FR4 substrate with dielectric constant of = 4.6 and the overall size of the proposed DR antenna r 2 is 20 × 35 mm . The dielectric resonator of N- shape is only 5.12 mm thickness and a very low permittivity constant (10.2). The simulated DR antenna operates from 4.4 to 11.7 GHz to cover most of the existing wireless mobile standards. The radiation pattern is Omni-directional and has a simulated gain values up to 4 dB and the total efficiency of antenna is 99%. The results are showing acceptable performance in terms of return loss, VSWR, radiation pattern and realized gain. The results presented here may be useful in designing the portable personal communication device antennas and in analyzing the performance of these antennas for wireless communication.

References

[1]. Federal Communications Commission, (2010). Revision of Part 15 of the Commission's Rules Regarding Ultra-wideband Transmission Systems. FCC - 10-151.

[2]. S. Long, M. McAllister, and L. Shen, (1983). “The Resonant Cylindrical Dielectric Cavity Antenna”. IEEE Transaction on Antenna and Propogation, Vol.31, No.3, pp.406-412.

[3]. Y. Gao, Z. Feng, and LiZhang, (2012). “Compact asymmetrical T-shaped Di- electric Resonator Antenna for broadband applications”. IEEE Trans. Antennas Propag., Vol.60, No.3, pp.1611-1615.

[4]. M. Abedian, S.K.A. Rahim, and M. Khalily, (2012). “Two-segment compact Dielectric Resonator Antenna for UWB application”. IEEE Antennas Wireless Propag. Lett., Vol.11, pp.1533-1536.

[5]. K. Lan, S. K. Chaudhuri, and S. Safavi Naeini, (2005). “Design and analysis of a combination antenna with rectangular dielectric resonator and inverted L-plate”. IEEE Trans. Antennas Propag., Vol.53, No.1, pp.495-501.

[6]. A. Petosa, (2007). Dielectric Resonator Antenna Handbook. Artech House Publishers.

[7]. D. Soren, R. Ghatak, R.K. Mishra, and D. R. Poddar, (2014). “Dielectric Resonator Antenna: Designs and Advances”. Progress in Electromagnetics Research B, Vol.60, pp.195-213.

[8]. M.S.M. Aras, M.K.A. Rahim, A. Asrokin, and M.Z. Abdul Aziz, (2008). “Dielectric Resonator Antenna (DRA) for Wireless Communication”. IEEE International in RF and Microwave Conference Proceedings. pp.454-458.

[9]. M. Lapierre, Y.M. Antar, A. Ittipiboon, and A. Petosa, (2005). “Ultrawideband monopole/dielectric resonator antenna”. IEEE Microwave and Wireless Components Letters, Vol.15, No.1, pp.7-9.

[10]. K. Ishimiya, J. Langbacka, Z. Ying and J. I. Takada, (2008). “A Compact MIMO DRA Antenna”, International Workshop on Antenna Technology: Small Antennas and Novel Metamaterials, iWAT 2008, pp.286-289.

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Research Paper

Design of a Wideband Bandpass Filter using Two Cross-Coupled Three Short Ended Section

Ajay Kumar Yadav* , Vipin Kumar Upaddhayay, Dileep kumar yadav*

* Postgraduate, Department of Electronics and Communication Engineering, SIIT, Gorakhpur, India.

-* Postgraduate, Department of Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

Yadav, A.K., Upaddhyay, V.K., and Yadav, D.K. (2016). Design of a Wideband Bandpass Filter using Two Cross-Coupled Three Short Ended Section. i-manager's Journal on Wireless Communication Networks, 5(1), 29-33. https://doi.org/10.26634/jwcn.5.1.6022

Abstract

A new compact wideband band pass filter is designed by using two short-ended cross coupled sections between the input and output port up to some length. Shorting of section improves its cutoff frequencies fall off. It also helps in size reduction and its covered area. It has measured 3dB pass band of (2 to 4.86) GHz band. The circuit size is reduced considerably and its size is (17.86×10.95) mm. This structure comprised of basically a ring resonator in which cross coupling and short ended section is provided. This wideband BPF is mainly applicable for IEEE defined S-Band applications. This wide band BPF was designed using ANSYS HFSS.

References

[1]. Runqi Zhang and Lei Zhu, (2014). “Design of a Wideband Bandpass Filter with Composite Short-circuited and Open-Circuited Stubs”. IEEE Microwave and Wireless Components Letters, Vol.24, No.2.

[2]. Xiuping Li and Xiang Ji, (2014). “Novel Compact UWB Bandpass Filters Design With Cross-Coupling between Short-Circuited Stubs”. IEEE Microwave and Wireless Components Letters, Vol.24, No.1.

[3]. YuePing Zhang and Mei Sun, (2006). “Dual-Band Microstrip Bandpass Filter Using Stepped-Impedance Resonators With New Coupling Schemes”. IEEE Transactions on Microwave Theory And Techniques, Vol.54, No.10.

[4]. Sheng Sun, and Lei Zhu, (2007). “Wideband Microstrip Ring Resonator Bandpass Filters under Multiple Resonances”. IEEE Transactions on Microwave Theory and Techniques, Vol.55, No.10.

[5]. Shuai Yang, Lei Lin, Jianzhong Chen, Kun Deng and Chang-Hong Liang, (2014). “Design of compact dualband bandpass filter using dual-mode steppedimpedance stub resonators”. Electron. Lett. Vol.50, No.8, pp.611-613.

[6]. Si-Wei Ren and Hong-Li Peng, (2012). “Compact Quasi- Elliptic Wideband Bandpass Filter Using Cross- Coupled Multiple-Mode resonators”. IEEE Microwave and Wireless Component Lett., Vol.22, No.8.

[7]. J.G. Zhou, W.J. Feng and W.Q. Che, (2012). “Dualwideband bandpass filter using T-shaped structure based on transversal signal-interaction concepts”. Electron. Lett, Vol.48, No.24.

[8]. Robert Rehner, Dirk Schneiderbanger, Michael Sterns, Siegfried Martius, Lorenz-Peter Schmidt J.T. Kuo, and E. Shin, (2010). “Novel Coupled Microstrip Wideband Filters withn Spurious Response Suppression”. Proceedings th of the 37 European Microwave Conference.

[9]. Qing-xin Chu, and Lei-lei, (2013). “Wideband Balanced Bandpass Filter Using Slot Resonators and Backto- Back Structure”. IEEE, Vol.49, No.19, pp.1230-1232.

[10]. Wen-Hsia Huang, Teng-Bang Hou, and Ching-Wen, (2002). “Design of A Bandpass Filter with Wide Passband and wide rejection bandwidth”. IEEE Microwave Wireless Component Lett., Vol.12, No.10, pp.383-385.

[11]. Seyyed Kamal Hashemi, (2011). “Dual-Band th Bandpass Filters Based on Multilayer Ring Resonators”. 11 Mediterranean Microwave Symposium (MMS), pp.34-37.

[12]. Yongsheng Dai, Qunfei Han, Min Han, Honghao Yin, Ping Li, Tongsheng Zuo and QiuyueXie, (n.d.). “A Novel Miniaturized Wideband Bandpass Filter using LTCC Technology”. International Symposium on Communication and Information Technologies.

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Review Paper

Influence of Compressive Sensing on Performance Metrics of Wireless Sensor Networks – A Survey

N. Subhashini* , M. Murugan**

* Assistant Professor, Department of Electronics and Communication Engineering, Valliammai Engineering College, Tamil Nadu, India.

** Professor and Vice Principal, Department of Electronics and Communication Engineering, Valliammai Engineering College, Tamil Nadu, India.

Subhashini, N., and Murugan, M. (2016). Influence of Compressive Sensing on Performance Metrics of Wireless Sensor Networks – A Survey. i-manager's Journal on Wireless Communication Networks, 5(1), 34-42. https://doi.org/10.26634/jwcn.5.1.6023

Abstract

Compressive sensing outperforms the traditional limits of the sampling theory. Based on the principle of sparsity and incoherence, the Compressive sensing retrieves the original signal with the least number of samples compared to the conventional method. Wireless sensor network consists of a large number of sensor nodes or motes with varying size depending upon the application. The spatially distributed nodes transmit the data sensed from the field in cooperation with other nodes to the fusion center. If the monitoring field is wide, the data collected from the field is also large consuming more energy, bandwidth and capacity of the network. Increase in the energy consumption of the node results in the decrease in the lifetime of the node. Hence, to increase the lifetime of the node, the data traffic in the network is reduced by associating compressive sensing with the wireless sensor network. This paper deals with the variation of the performance metrics of wireless sensor networks, in the presence of compressive sensing.

References

[1]. Bajwa, W., Haupt, J., Sayeed, A., & Nowak, R. (2006). “Compressive Wireless Sensing Categories and Subject Descriptors”. Conf. on Info Processing Sensor Networks (IPSN '06).

[2]. Balouchestani, M. (2011). “Compressed sensing in wireless sensor networks: Survey”. Canadian Journal on Multimedia and Wireless Networks, Vol.2, No.1, pp.1-4. Retrieved from http://ampublisher.com/Feb 2011/MWN- 1102-012.pdf

[3]. Bonavolontà, F., D'Apuzzo, M., Liccardo, A., & Vadursi, M. (2014). “New Approach Based on Compressive Sampling for Sample Rate Enhancement in DASs for Low-Cost Sensing Nodes”. Sensors, Vol.14, pp.18915-18940. Retrieved from http://doi.org/10.3390/ s141018915

[4]. Brunelli, D., & Caione, C. (2015). “Sparse Recovery Optimization in Wireless Sensor Networks with a Sub- Nyquist Sampling Rate”. Sensors, Vol.15, No.7, pp.16654- 16673. Retrieved from http://doi.org/10.3390/ s150716654

[5]. Candès, E. (2006). “Compressive sampling”. Proceedings of the International Congress of Mathematicians, pp.1433-1452.

[6]. Candes E. and Wakin B Michael, (2008). “An Introduction to Compressive Sampling”. IEEE Signal Processing Magazine, Vol.25, No.2, pp.21-30.

[7]. Chen, C. (n.d.). A Survey on Sub-Nyquist Sampling. Retrieved from www.seas.ucla.edu

[8]. Colonnese, S., Cusani, R., Rinauro, S., Ruggiero, G., & Scarano, G. (2013). “Efficient compressive sampling of spatially sparse fields in wireless sensor networks”. EURASIP Journal on Advances in Signal Processing, Vol.1, pp.136. Retrieved from http://doi.org/10.1186/1687-6180-2013- 136

[9]. Davenport, M.A, Duarte, M. F. M., Eldar, Y. C. Y., & Kutyniok, G. (2011). “Introduction to compressed sensing”. Preprint, Vol.93, pp.1-68. Retrieved from http://doi.org/10.1287/mksc. 20.3.244.9764

[10]. Donoho, D.L.L. (2006). “Compressed sensing”. IEEE Transactions on Information Theory, Vol.52, No.4, pp.1289- 1306. Retrieved from http://doi.org/Doi 10.1109/Tit.2006.871582

[11]. Foucart, S., & Rauhut, H. (2013). A Mathematical Introduction to Compressive Sensing. Retrieved from http://doi.org/ 10.1007/978-0-8176-4948-7

[12]. García-Hernández, C. F., Ibarguengoytia- Gonzalez, P. H., García-Hernández, J., & Pérez-Díaz, J. A. (2007). “Wireless Sensor Networks and Applications: A Survey”. Int. Journal of Computer Science and Network Security, Vol.7, No.3, pp.264-273.

[13]. Grant, M., & Boyd, S. (2015). CVX Users ' Guide. CVX Research, Inc. , pp.1-72.

[14]. Hayashi, K., Nagahara M., & Tanaka, T. (2013). “A User's Guide to Compressed Sensing for Communications Systems”. IEICE Transactions on Communications, E96. B(3), pp. 685 - 712. Retrieved from http://doi.org/10.1587/transcom. E96.B.685

[15]. Ji. S., Huang, L. ., Wang, J., Shen, J. , & Kim, J.-U. . (2014). “An improved reconstruction methods of compressive sensing data recovery in wireless sensor networks”. International Journal of Security and Its Applications, Vol.8, No.1, pp.1-8. Retrieved from http://doi.org/10.14257/ ijsia.2014.8.1.01

[16]. Liu, X. L., Luo, C., & Wu, F. (2012). “Compressive cooperation for Gaussian half-duplex relay channel”. Journal on Wireless Communication Networks, pp.1-10.

[17]. Luo, J., Xiang, L., & Rosenberg, C. (2010). “Does Compressed Sensing Improve the Throughput of Wireless Sensor Networks”. IEEE International Conference on Communications, pp. 1-6. Retrieved from http://doi.org/10.1109/ ICC.2010.5502565

[18]. Masiero, R., Quer, G., Pillonetto, G., Rossi, M., & Zorzi, M. (2009). “Sensing, Compression and Recovery for Wireless Sensor Networks: Sparse Signal Modelling”. IEEE Global Communication Conference (GLOBECOM), Honululu.

[19]. Masoum, A., Meratnia, N., & Havinga, P. J. M. (2013). “A distributed compressive sensing technique for data gathering in Wireless Sensor Networks”. Procedia Computer Science, Vol.21, pp.207-216. Retrieved from http://doi.org/10.1016/j.procs.2013.09.028

[20]. Pope, G. (2009). Compressive Sensing: A Summary of Reconstruction Algorithms. Matrix, (August 2008).

[21]. Qaisar, S., Bilal, R. M., Iqbal, W., Naureen, M., & Lee, S. (2013). “Compressive sensing: From theory to applications, a survey”. Journal of Communications and Networks, Vol.15, No.5, pp.443-456. Retrieved from http://doi.org/10.1109/JCN.2013.000083

[22]. Rawat, P., Deep, K., Chaouchi, H., & Marie, J. (2014). “ Wireless sensor networks: A sur vey on recent developments and potential synergies”. The Journal of Supercomputing, Vol.68, No.1, pp.1-48. Retrieved from http://doi.org/10.1007/s11227-013-1021-9

[23]. Strohmer, T. (2012). “Measure what should be measured: Progress and challenges in compressive sensing”. IEEE Signal Processing Letters, Vol.19, No.12, pp.887-893. Retrieved from http://doi.org/10.1109/ LSP.2012.2224518

[24]. Villaverde, J. F., Chung, W.-Y., & Chen, S.-L. (2015). “Compressive Sensing Algorithm for Wireless Sensor Network Power Management”. International Journal of Computer and Electrical Engineering, Vol.7, No.3, pp. 199-205. Retrieved from http://doi.org/10.17706/IJCEE. 2015.7.3.199-205

[25]. Walke, S. R., & Jaini, P. (2014). “Compressed Sensing Using Deterministic Measurement”. Int. Journal of Advanced Comput. Engg., and Networking, Vol.2, No.5, pp.60-63.

[26]. Xiayong Z., Houjun W.,Yang, & Zhijian D. (2010). “Wireless Sensor Networks based on Compressive Sensing”. IEEE Int. Conf. Comput. Sci. Inf. Technol., Vol.9, pp.90-92.

[27]. Xie, R., Jia, X., & Society, C. (2014). “Transmission- Efficient Clustering Method for Wireless Sensor Networks Using Compressive Sensing”. IEEE Transactions on Parallel & Distributed Systems,Vol.25, No.3, pp.806-815.

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i-manager's Journal on Wireless Communication Networks (JWCN)

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Volume 5 Issue 1 April - June 2016

Extending Implementation- A Castalia with a Multimedia Sensor Node Framework

Hanafy Mahmoud Ali*

Assistant Professor, Department of Computers and Systems Engineering, Minia University, El Minia, Egypt.

Ali, H.M. (2016). Extending Implementation- A Castalia with a Multimedia Sensor Node Framework. i-manager's Journal on Wireless Communication Networks, 5(1), 1-10. https://doi.org/10.26634/jwcn.5.1.6018

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CPW-Fed Printed Slot Antenna for Wireless and Future Mobile Broad-Band Applications

Girijesh Giri* , G.S. Tripathi**, Sudhanshu Verma***

* PG Scholar, Department of Electronics and Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India. **-*** Faculty, Department of Electronics and Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

Giri,G., Tripathi, G.S., and Verma, S. (2016). CPW-Fed Printed Slot Antenna for Wireless and Future Mobile Broad-Band Applications. i-manager's Journal on Wireless Communication Networks, 5(1), 11-15. https://doi.org/10.26634/jwcn.5.1.6019

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Performance Analysis of Evolutionary Algorithm for PAPR Reduction in OFDM System

Prabhneet Kaur* , Mangal Singh**

* PG Scholar, Department of Electronics and Telecommunication Engineering, Chhatrapati Shivaji Institute of Technology, Durg, India. ** Associate Professor, Department of Electronics and Telecommunication Engineering, Chhatrapati Shivaji Institute of Technology, Durg, India.

Kaur, P., and Singh, M. (2016). Performance Analysis of Evolutionary Algorithm for PAPR Reduction in OFDM System. i-manager's Journal on Wireless Communication Networks, 5(1), 16-22. https://doi.org/10.26634/jwcn.5.1.6020

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N-Shape Dielectric Resonator Antenna for Wireless Communication

Roshni Gupta* , Mangal Singh**, Dipali Soren***

Gupta, R., Singh, M., and Soren, D. (2016). N-Shape Dielectric Resonator Antenna for Wireless Communication. i-manager's Journal on Wireless Communication Networks, 5(1), 23-28. https://doi.org/10.26634/jwcn.5.1.6021

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Design of a Wideband Bandpass Filter using Two Cross-Coupled Three Short Ended Section

Ajay Kumar Yadav* , Vipin Kumar Upaddhayay**, Dileep kumar yadav***

* Postgraduate, Department of Electronics and Communication Engineering, SIIT, Gorakhpur, India. **-*** Postgraduate, Department of Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

Yadav, A.K., Upaddhyay, V.K., and Yadav, D.K. (2016). Design of a Wideband Bandpass Filter using Two Cross-Coupled Three Short Ended Section. i-manager's Journal on Wireless Communication Networks, 5(1), 29-33. https://doi.org/10.26634/jwcn.5.1.6022

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Influence of Compressive Sensing on Performance Metrics of Wireless Sensor Networks – A Survey

N. Subhashini* , M. Murugan**

* Assistant Professor, Department of Electronics and Communication Engineering, Valliammai Engineering College, Tamil Nadu, India. ** Professor and Vice Principal, Department of Electronics and Communication Engineering, Valliammai Engineering College, Tamil Nadu, India.

Subhashini, N., and Murugan, M. (2016). Influence of Compressive Sensing on Performance Metrics of Wireless Sensor Networks – A Survey. i-manager's Journal on Wireless Communication Networks, 5(1), 34-42. https://doi.org/10.26634/jwcn.5.1.6023

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Girijesh Giri* , G.S. Tripathi, Sudhanshu Verma*

* PG Scholar, Department of Electronics and Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

-* Faculty, Department of Electronics and Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

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

** Associate Professor, Department of Electronics and Telecommunication Engineering, Chhatrapati Shivaji Institute of Technology, Durg, India.

Roshni Gupta* , Mangal Singh, Dipali Soren*

Ajay Kumar Yadav* , Vipin Kumar Upaddhayay, Dileep kumar yadav*

* Postgraduate, Department of Electronics and Communication Engineering, SIIT, Gorakhpur, India.

-* Postgraduate, Department of Communication Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.

* Assistant Professor, Department of Electronics and Communication Engineering, Valliammai Engineering College, Tamil Nadu, India.

** Professor and Vice Principal, Department of Electronics and Communication Engineering, Valliammai Engineering College, Tamil Nadu, India.