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

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Design and Development of Patient Care Voice Actuated Bed in Hospital
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Volume 6 Issue 1 November - January 2017

Research Paper

Distance Based Node Localization and Tracking of “Off-Road Vehicle Racing” With Gauss-Newton Algorithm

Rajdeep Singh Sohal* , Jaipreet Kaur**

* Assistant Professor, Department of Electronics and Communication Engineering, Guru Nanak Dev University Regional Campus, Fattu Dhinga, Punjab, India.

** Assistant Professor, Department of Electronics and Communication Engineering, Guru Nanak Dev University Regional Campus, Sathiala, Punjab, India

Sohal, R. S., and Kaur, J. (2017). Distance Based Node Localization and Tracking of “Off-Road Vehicle Racing” With Gauss-Newton Algorithm. i-manager’s Journal on Communication Engineering and Systems, 6(1), 1-8. https://doi.org/10.26634/jcs.6.1.10353

Abstract

Target Localization and Tracking are the primary challenges for Wireless Sensor Networks (WSNs), where adding GPS receivers or other tracking based sensors to every node could be expensive. The use of technology is increased to enrich the experience of sporting events. Such technology, along its associated graphics and statistics not only entertains viewers, but also enables them to gain insight into the performance of athletes. Localization schemes for sensor networks use a small number of seed nodes that know their location and protocols, whereby the locations of other nodes are estimated from the messages sent from all nodes to seed nodes. Several such localization techniques have been proposed, but none of them consider mobile nodes and seeds. The traditional localization methods attain high location accuracy in line of sight (LOS) environment. But the localization accuracy degrades significantly in non-line of sight (NLOS) environment. This paper addresses the problems of tracking a mobile target by localizing a node. It appears that mobility would make localization more difficult. To solve this problem, the Gauss-Newton algorithm is adopted in this paper. It uses connectivity information to find the location of nodes in a network and can take advantage of additional data, such as estimated distances between neighbours or known positions for certain anchor nodes. It can exploit mobility to improve the accuracy and precision of localization. This scheme outperforms the best known static localization schemes under a wide range of conditions. The proposed algorithm is implemented in MATLAB. This approach works much better for topologies in which the shortest path distance between two nodes does not correspond well to their Euclidean distance.

References

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[9]. Shah, R.C., and Rabaey, J.M., (2002). “Energy aware routing for low energy ad hoc sensor networks”. In Proceedings of the IEEE Wireless Communications and Networks Conference (WCNC '02), Orlando, FL, USA, pp.350-355.

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[12]. Li, L., Halpern, J.Y., (2001). “Minimum energy mobile wireless networks revisited”. In Proceedings of IEEE International Conference on Communications (ICC'01), Helsinki, Finland, pp.278-283.

[13]. Yang, J., Xu, M., Zhao, W., Xu, B., (2010). “A multipath routing protocol based on clustering and Ant Colony Optimization for Wireless Sensor Networks”. Sensors, Vol.10, No.5, pp.4521-4540.

[14]. Li X., Xu L., Wang H., Song J., Yang S.X., (2010). “A Differential evolution-based routing algorithm for environmental monitoring Wireless Sensor Networks”. Sensors, Vol.10, No.6, pp.5425-5442.

[15]. Youssef, W., Younis, M., (2010). “Optimized asset planning for minimizing latency in Wireless Sensor Networks”. Wirel. Netw., Vol.16, No.1, pp. 65-78.

[16]. Yang H., Ye F., Sikdar B., (2008). “A swarmintelligence- based protocol for data acquisition in networks with mobile sinks”. IEEE Trans. Mobile Comput., Vol.7, No.8, pp. 931-945.

[17]. Stojmenovic I., Lin X., (2001). “Power-aware localized routing in wireless networks. IEEE Trans. Parallel Distrib. Syst., Vol.12, No.11, pp.1121-1133.

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Research Paper

A Proposed ACO Routing In Peer-To-Peer Networks

Hanafy Mahmoud Ali*

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

Ali, H. M. (2017). A Proposed ACO Routing In Peer-To-Peer Networks. i-manager’s Journal on Communication Engineering and Systems, 6(1), 9-21. https://doi.org/10.26634/jcs.6.1.10377

Abstract

With the rapid development of computer network techniques and novel concepts of distributed computing, many of the modifying researchers are now facing new challenges on how to merge some old protocols to take the advantage of each of them to create a new technique stack that has a lot of advantages in various directions providing us an effective use and solving complex problems. Peer-to-Peer (P2P) network based network technology is grabbing more attention due to its feasibility to build applications. In this paper, the author has focused on the development of a new improvement algorithm based on P2P network environment, and presented the details of implementations with some basic performance evaluations. The main goal of the paper is to present a new algorithm that provides us with a lot of facilities like shortest path, focusing on to the security problems. So the integrated architecture gives us good results as the choice of the shortest path with, more trust bath that is based on the reputation values of end nodes. The reputation is defined to express subjective trustable relationship among individuals and objective trust view. The recommended routing algorithm depends on the reputation values and metric value. Finally, by this routing algorithm, the P2P network performance is greatly enhanced.

References

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[28]. Zhengqiang Liang, and Weisong Shi, (2005). “PET: A Personalized Trust model with reputation and risk evaluation for P2P resource sharing”. In: HICSS '05, The 38^th Annual Hawaii International Conference on System Sciences, IEEE Computer Society, Washington DC, USA, pp.201.

[29]. Runfang Zhou, and Fellow-Kai Hwang, (2007). “Power trust: A robust and scalable reputation system for trusted peer-to-peer computing”. IEEE Transactions on Parallel and Distributed Systems, Vol.18, No.4, pp.460–473.

[30]. Rappaport, Theodore S., (2002). Wireless Communications,- Principles and Practice. Second edition, Prentice Hall, ISBN 0130422320. Hanafy M. Ali, Mohamed Z. Abdelmegid, and Mohamed M. Ali, (2009). “Secure Active Routing for Peer-to- Peer Networks”. Journal of Engineering Sciences, Assiut University, Vol. 37, No. 5, pp. 1099-1108.

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Research Paper

Energy Efficient Relaying For Target Coverage In DenseWireless Sensor Networks

Abhilash C.N.* , S.H. Manjula, K.R. Venugopal*

*-*** Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bangalore, India.

Abhilash C.N., Manjula, S.H., and Venugopal, K. R. (2017). Energy Efficient Relaying For Target Coverage In Dense Wireless Sensor Networks. i-manager’s Journal on Communication Engineering and Systems, 6(1), 22-31. https://doi.org/10.26634/jcs.6.1.10355

Abstract

Wireless Sensor Networks (WSN) have been the most widely selected research area for a decade now. Researchers have identified the usability of sensor networks in huge variety of applications. The emergence of cognitive networks has led the sensor networks to adapt to the network conditions and the application dynamics. The work presented in this paper proves a unique cognitive solution for the problem of dynamic target coverage problem in the designated area of military surveillance. The nodes used for the acquisition of target coverage problem in the network remains static and transmits the information to the neighboring nodes using a movement prediction algorithm. The proposed approach shows better improvement in coverage and network lifetime in terms of position estimation and tracking target when compared to non-relaying techniques.

References

[1]. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, (2002). “A Survey on Sensor Networks”. IEEE Communications Magazine, Vol.40, No.8, pp.102-116.

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[5]. Zorbas D, Glynos D, and Douligeris C, (2009). “Connected Partial Target Coverage and Network Lifetime in Wireless Sensor Networks”. Wireless Days (WD), 2 International Funders for Indigenous Peoples (IFIP), pp.1–5.

[6]. Qun Zhao, and Mohan Gurusamy, (2008). “Lifetime Maximization for Connected Target Coverage in Wireless Sensor Networks”. IEEE/ACM Transactions on Networking, Vol.16, No.6, pp.1378-1391.

[7]. K. Yong-hwan Kim, Youn-Hee Han, Chang-min Mun, and Chan Yeol Park, (2010). “Lifetime Maximization Considering Connectivity and Overlapped Targets in Wireless Sensor Networks”. 2 International Conference on Information Technology Convergence and Services (ITCS).

[8]. Ehsan Saradar Torshizi, Saleh Yousefi, and Jamshid Bagherzadeh, (2012). “Lifetime Maximization for Connected Target Coverage in Wireless Sensor Networks with Sink Mobility”. 6 International Symposium on Tele communications (IST), pp. 743 -748.

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Research Paper

Smart Antennas For Spectrum Sensing Using CognitiveRadio Networks

Veerendra Dakulagi* , MD. Bakhar, Vani R.M.*

* Assistant Professor, Department of Electronics and Communication Engineering, Guru Nanak Dev Engineering College, Bidar, Karnataka, India.

Professor, Department of Electronics and Communication Engineering, Guru Nanak Dev Engineering College, Bidar, Karnataka, India.

* Reader/Technical Officer-II & Head, University Science Instrumentation Centre, Gulbarga University, Gulbarga, India.

Veerendra, Bakhar, Md., and Vani R.M.(2017). Smart Antennas For Spectrum Sensing Using Cognitive Radio Networks. i-manager’s Journal on Communication Engineering and Systems, 6(1), 32-37. https://doi.org/10.26634/jcs.6.1.10357

Abstract

Smart antenna systems have been studied for many years for signal detection and estimation and are used only in military applications until recently. These are becoming popular from recent years and are used in commercial applications due to impulsive advancement in the digital signal processing and VLSI technology. In array signal processing, plethora of problems related to signal detection and estimation is solved using various Direction Of Arrival (DOA) algorithms, including Bartlett, Maximum Likelihood Method (MLM), and Maximum Eigen Value (MEV) method. These algorithms and many variants of these algorithms deteriorate from its performance either for narrow angle or wide angle separation. Hence the authors proposed the DOA estimation algorithm based on Hannan-Quinn (HQ) criterion for wideband spectrum sensing in cognitive networks. Simulation results validate the effectiveness of this method.

References

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[2]. S. Haykin, D. Thomson, and J. Reed, (2009). “Spectrum sensing for cognitive Radio”. Proceedings of the IEEE, Vol.97,No.5, pp.849–877.

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[7]. R.O. Schmidt, (1986). “Multiple emitter location and signal parameter estimation”. IEEE Trans. Antennas Propagation, Vol. 34, No. 3, pp. 276–280.

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[13]. Veerendra, Md. Bakhar, and Vani. R.M, (2016a). “Robust Blind Beam formers for Smart Antenna System using Window Techniques”. Procedia Computer Science (Elsevier), Vol.93, pp.713–720.

[14]. Veerendra, Md. Bakhar, and Vani. R.M, (2016b). “Smart antennas for next generation cellular mobile communications”. Journal on Digital Signal Processing, Vol.4, No.3, pp.6-11.

[15]. Veerendra, Md. Bakhar, and Vani. R.M, (2016c). “Smart Antennas for Interference Rejection in Mobile Communications”. Journal of Mobile Applications and Technologies, Vol.2, No.4, pp.11-18.

[16]. Veerendra, Md. Bakhar, and Kishan Singh, (2016d). “Direction of Arrival Algorithms for Mobile user Detection”. International Journal for Scientific Research and Development (Conference 8: NCACC - 2016), pp.7-13.

[17]. Veerendra, Md. Bakha, and Vani. R.M, (2015). “Subspace based Direction of Arrival Estimation using no Snapshot Criteria for Mobile Communications”. The IUP Journal of Telecommunications, Vol.7, No.3, pp.29-37.

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Research Paper

Integrated Dual Port Ultra-Wide Band/ReconfigurableAntenna For Cognitive Radio Application

Hemant Verma* , Sudhanshu Verma**

* PG Scholar, Department of Electronics and Communication Engineering, MMMUT, Gorakhpur, India.

** Assistant Professor, Department of Electronics and Communication Engineering, MMMUT, Gorakhpur, India.

Verma, H., and Verma, S. (2017). Integrated Dual Port Ultra-Wide Band/Reconfigurable Antenna For Cognitive Radio Application. i-manager’s Journal on Communication Engineering and Systems, 6(1), 38-41. https://doi.org/10.26634/jcs.6.1.10352

Abstract

An integrated Ultra-Wide Band (UWB)/ reconfigurable slot antenna is proposed for cognitive radio applications. The proposed antenna consists of an elliptical shape UWB disc monopole and a H-shaped slot resonator, which is precisely embedded in disc monopole. The UWB antenna covers entire UWB band from 3.1 to 10.6 GHz and is used for channel sensing. The H-shape slot resonator works as a narrow band antenna operating in the range 7.2 to 8 GHz. The slot is fed by off-centered microstrip line that creates the desired matching across tunable frequency band. The proposed antenna design is simulated using HFSS 15.

References

[1]. Simon Haykin, (2005). “Cognitive radio: Brain empowered wireless communications”. IEEE J. Sel. Areas Communication, Vol.23, No.2, pp.201-220.

[2]. Federal Communications Commission, (2002). Spectrum Policy Task Force. Rep. ET Docket.

[3]. Y. Tawk, and C.G. Christodoulou, (2009). “A new reconfigurable antenna design for cognitive radio”. IEEE Antennas and Wireless Propagation Lellers, Vol.8, pp.1378-1381.

[4]. R.N. Simons, (2001). Coplanar Waveguide Circuits, Components and Systems. New York: Wiley-Inter science.

[5]. E. Ebrahimi, J.R. Kelly, and P. Hall, (2011). “Integrated wide-narrowband antenna for multi-standard radio”. IEEE Trans. Antennas Propag., Vol.59, No.7, pp.2628–2635

[6]. Y. Tawk, J. Costantine, K. Avery, and C.G. Christodoulou, (2011). “Implementation of a cognitive radio front-end using rotatable controlled reconfigurable antennas”. IEEE Trans. Antennas Propag., Vol.59, No.5, pp. 1773–1778.

[7]. M. Zamudio, Y. Tawk, J. Kim, and C. G. Christodoulou, (2011). “Integrated cognitive radio antenna using th reconfigurable bandpass filters”. In Proc. 5 Eur. Conf. Antennas Propag., pp. 2108–2112.

[8]. M. R. Hamid, P. Gardner, P. S. Hall, and F. Ghanem, (2011). “Vivaldi antenna with integrated switchable bandpass resonator”. IEEE Trans. Antennas Propag., Vol.59, No.11, pp.4008–4015.

[9]. J.R. Kelly, P.S. Hall, and P. Song, (2009). “A reconfigurable wide band handset antenna operating from 460 MHz to 12 GHz”. In Proc. IEEE Antennas Propag. Soc. Int. Symp., pp.1–4.

[10]. E. Ebrahimi, and P.S. Hall, (2009). “A dual port wide-narrowband antenna for cognitive radio”. In Proc. 3 Eur. Conf. Antennas Propag., pp. 809-812.

[11]. P. Gardner, M.R. Hamid, P.S. Hall, J. Kelly, F. Ghanem, and E. Ebrahimi, (2008). “Reconfigurable antennas for cognitive radio: Requirements and potential design approaches”. In Proc. IET Seminar Wideband, Multi band Antennas Arrays Defense Civil Appl., pp. 89-94.

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Review Paper

Simulation Of Spatial Multiplicity Enhancement For DenseSpace Division Multiplexing: A Review

Nirmala Tirkey* , Vikas Sahu, Sharad Mohan Shrivastava, Anshu, Aakash Joshi

*,**,* PG Scholar, Department of Electronics and Communication Engineering, Shri Shankracharya Technical Campus, Bhilai, CG, India.

,*** Assistant Professor, Department of Electronics and Telecommunication, Faculty of Engineering and Technology, Shri Shankracharya Technical Campus, Bhilai, CG, India.

Tirkey, N., Sahu, V., Shrivastava, S. M., Anshu and Joshi, A. (2017). Simulation Of Spatial Multiplicity Enhancement for Dense Space Division Multiplexing: A Review. i-manager’s Journal on Communication Engineering and Systems, 6(1), 42-48. https://doi.org/10.26634/jcs.6.1.10356

Abstract

This paper aims to make understand the fundamentals and recent advancement in Dense Space Division Multiplexing (DSDM). Similar to Dense WDM (DWDM) with dense wavelength spacing and high count of over several tens of wavelength channels, it is shown that DSDM with high spatial density and large spatial multiplicity is effective for greatly expanding transmission capacity. Multicore fibers and few-mode fibers have potential application in realizing Dense Space Division Multiplexing system. As the main objective was to study the most important parameter that establishes the performance of optical fiber in distance and capacity. As in MCF, many cores tightly packaged together is inevitable that signals cause undesired effects from one core to another. Beside the physical space available for core, the maximum tolerated crosstalk dictates the maximum quantity of cores we can use. Design of single-mode 31 core fiber with Quasi Single Mode (QSM) core is demonstrated. Measurement of Spatial Channel Count (SCC) for different number of cores is studied. And to give the readers a glimpse of recent development in DSDM and MCF technology, some noticeable research papers have also been discussed.

References

[1]. R.G.H. Uden, R.A. Correa, E.A. Lopez, F.M. Huijskens, C. Xia, G. Li, A. Schulzgen, H. Waardt, A.M.J. Koonen, and C.M. Okonkwo, (2014). “Ultra High Density Space Division Multiplexing with a Few-mode Multicore Fibre”. Nature Photonics, Vol.8, pp. 865-870.

[2]. Shoichiro Matsuo, Katsuhiro Takenaga, Yusuke Sasaki, Yoshimichi Amma, Shota Saito, Kunimasa Saitoh, Takashi Matsui, Kazuhide Nakajima, Takayuki Mizuno, Hidehiko Takara, Yutaka Miyamoto, and Toshio Morioka, (2016). “High Spatial Multiplicity Multicore Fibers for Future Dense Space Division Multiplexing Systems”. Journal of Lightwave Technology (JLT), Vol.34, No 6, pp.1464-1475.

[3]. Takayuki Mizuno, Hidehiko Takara, Akihide Sano, and Yutaka Miyamoto, (2016). “Dense Space Division Multiplexed Transmission Systems using Multi-core and Multi-mode Fiber”. Journal of Lightwave Technology (JLT), Vol.34, No.2, pp.582-592.

[4]. K. Shibahara, T. Mizuno, H. Takara, A. Sano, H. Kawakami, D. Lee, Y. Miyamoto, H. Ono, M. Oguma, Y. Abe, T. Kobayashi, T. Matsui, R. Fukumoto, Y. Amma, T. Hosokawa, S. Matsuo, K. Saito, H. Nasu, and T. Morioka, (2015). “Dense SDM (12 core 3 mode) Transmission over 527 km with 33.2-ns Mode Dispersion Employing Low Complexity Parallel MIMO Frequency Domain Equalization” .Conference on Optical Fiber Communication (OFC), Los Angeles, Th5C.2.

[5]. Yutaka Miyamoto, and Hirokazu Takenouchi, (2016). “Dense Space Division Multiplexing Optical Communications Technology for Petabits/s Class Transmission”. NTT Technical Review.

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[7]. Ye, F., et al., (2015). “High count multi-core fibers for Space Division Multiplexing with propagation direction interleaving”. Paper presented at Optical Fiber Communication Conference (OFC), Los Angeles (California), paper Th4C.3, doi: 10.1364/OFC.2015.Th4C.3.

[8]. Ye, F. et al., (2016). “Wavelength Dependence of intercore Crosstalk in Homogeneous Multi-Core Fibers”. IEEE Photon. Technol. Lett, Vol.28, No.1, pp.27-30.

[9]. K. Takenaga, S. Tanigawa, N. Guan, S. Matsuo, K. Saitoh and M. Koshiba, (2010). “Reduction of Crosstalk by Quasi Homogeneous Solid Multicore Fiber” Conference on Optical Fiber Communication (OFC), San Diego, OWK7.

[10]. Kunimasa Saitoh, and Shoichiro Matsuo, (2016). “Multicore Fiber Technology”. Journal of Lightwave Technology (JLT), Vol.34, No.11, pp.55 - 66.

[11]. Yusuke Sasaki, Yoshimichi Amma, Katsuhiro Takenga, Shoichiro Matsuo, Kunimasa Saitoh, and Masanori Koshiba, (2015). “Few Mode Multicore Fiber with 36 Spatial Modes (Three Modes (LP₀₁ , LP_11a , LP_11b ) 12 Cores)”. Journal of Lightwave Technology (JLT), Vol.33, No.5, pp.964-970.

[12]. J. Sakaguchi, W. Klaus, J.M.D. Mendinueta, B.J. Puttnam, R.S. Luis, Y. Awaji, N. Wada, T. Hayashi, T. Nakanishi, T. Watanabe, Y. Kokubun, T. Takahata, and T. Kobayashi, (2015). “Realizing a 36-core, 3-mode Fiber with 108 Spatial Channels”. Optical Fiber Communication Conference, Optical Society of America.

[13]. Takayuki Mizuno, Hidehiko Takara, Akihide Sano, and Yutaka Miyamoto, (2015). “High Capacity Dense SDM Transmission using Multi-core Few-mode Fiber”. IEEE Photonics Conference (IPC) IEEE.

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[17]. S. Takasaka, H. Matsuura, W. Kumagai, M. Tadakuma, Y. Mimura, Y. Tsuchida, K. Maeda, R. Miyabe, K. Aiso, K. Doi, and R. Sugizaki, (2013). “Cladding Pumped Seven Core EDFA using a Multimode Pump Light Coupler” European Conference on Optical Communication (ECOC), London, We.4.A.5.

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[20]. T. Mizuno, T. Kobayashi, H. Takara, A. Sano, H. Kawakami, T. Nakagawa, Y.Miyamoto, Y. Abe, T. Goh, M. Oguma, T. Sakamoto, Y. Sasaki, I. Ishida, K. Takenaga, S. Matsuo, K. Saitoh, and T. Morioka, (2014). “12-core 3- mode Dense Space Division Multiplexed Transmission over 40 km employing Multi-carrier Signals with Parallel MIMO Equalization”. Conference on Optical Fiber Communication (OFC), San Francisco, Th5B.2.

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

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Volume 6 Issue 1 November - January 2017

Distance Based Node Localization and Tracking of “Off-Road Vehicle Racing” With Gauss-Newton Algorithm

Rajdeep Singh Sohal* , Jaipreet Kaur**

* Assistant Professor, Department of Electronics and Communication Engineering, Guru Nanak Dev University Regional Campus, Fattu Dhinga, Punjab, India. ** Assistant Professor, Department of Electronics and Communication Engineering, Guru Nanak Dev University Regional Campus, Sathiala, Punjab, India

Sohal, R. S., and Kaur, J. (2017). Distance Based Node Localization and Tracking of “Off-Road Vehicle Racing” With Gauss-Newton Algorithm. i-manager’s Journal on Communication Engineering and Systems, 6(1), 1-8. https://doi.org/10.26634/jcs.6.1.10353

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A Proposed ACO Routing In Peer-To-Peer Networks

Hanafy Mahmoud Ali*

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

Ali, H. M. (2017). A Proposed ACO Routing In Peer-To-Peer Networks. i-manager’s Journal on Communication Engineering and Systems, 6(1), 9-21. https://doi.org/10.26634/jcs.6.1.10377

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Energy Efficient Relaying For Target Coverage In DenseWireless Sensor Networks

Abhilash C.N.* , S.H. Manjula**, K.R. Venugopal***

*-*** Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bangalore, India.

Abhilash C.N., Manjula, S.H., and Venugopal, K. R. (2017). Energy Efficient Relaying For Target Coverage In Dense Wireless Sensor Networks. i-manager’s Journal on Communication Engineering and Systems, 6(1), 22-31. https://doi.org/10.26634/jcs.6.1.10355

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Smart Antennas For Spectrum Sensing Using CognitiveRadio Networks

Veerendra Dakulagi* , MD. Bakhar**, Vani R.M.***

Veerendra, Bakhar, Md., and Vani R.M.(2017). Smart Antennas For Spectrum Sensing Using Cognitive Radio Networks. i-manager’s Journal on Communication Engineering and Systems, 6(1), 32-37. https://doi.org/10.26634/jcs.6.1.10357

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Integrated Dual Port Ultra-Wide Band/ReconfigurableAntenna For Cognitive Radio Application

Hemant Verma* , Sudhanshu Verma**

* PG Scholar, Department of Electronics and Communication Engineering, MMMUT, Gorakhpur, India. ** Assistant Professor, Department of Electronics and Communication Engineering, MMMUT, Gorakhpur, India.

Verma, H., and Verma, S. (2017). Integrated Dual Port Ultra-Wide Band/Reconfigurable Antenna For Cognitive Radio Application. i-manager’s Journal on Communication Engineering and Systems, 6(1), 38-41. https://doi.org/10.26634/jcs.6.1.10352

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Simulation Of Spatial Multiplicity Enhancement For DenseSpace Division Multiplexing: A Review

Nirmala Tirkey* , Vikas Sahu**, Sharad Mohan Shrivastava***, Anshu****, Aakash Joshi*****

Tirkey, N., Sahu, V., Shrivastava, S. M., Anshu and Joshi, A. (2017). Simulation Of Spatial Multiplicity Enhancement for Dense Space Division Multiplexing: A Review. i-manager’s Journal on Communication Engineering and Systems, 6(1), 42-48. https://doi.org/10.26634/jcs.6.1.10356

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Abhilash C.N.* , S.H. Manjula, K.R. Venugopal*

Veerendra Dakulagi* , MD. Bakhar, Vani R.M.*

* PG Scholar, Department of Electronics and Communication Engineering, MMMUT, Gorakhpur, India.

** Assistant Professor, Department of Electronics and Communication Engineering, MMMUT, Gorakhpur, India.

Nirmala Tirkey* , Vikas Sahu, Sharad Mohan Shrivastava, Anshu, Aakash Joshi