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 1 Issue 3 October - December 2012

Research Paper

PAPR Reduction of STBC MIMO- OFDM Systems Using Adaptive Active Constellation Extension

K Srinivasa Rao* , B. Prabhakara Rao**

* Electronics and Communication Engineering, G.V.P College of Engineering for Women, Visakhapatnam, A.P, India.

** Electronics and Communication Engineering, J.N.T University, Kakinada, A.P, India.

Rao, K.S., and Prabakararao, B. (2012). PAPR Reduction of STBC MIMO-OFDM Systems Using Adaptive Active Constellation Extension. i-manager’s Journal on Wireless Communication Networks, 1(3), 1-7. https://doi.org/10.26634/jwcn.1.3.2048

Abstract

In this paper Adaptive Active Constellation (A-ACE) is analyzed for Peak to Average Power Ratio (PAPR) reduction of OFDM Systems with spectral diversity of Space time Block Coding (STBC). To support large system capacity with robustness to multipath fading, OFDM and MIMO have been combined as MIMO-OFDM. To overcome the disadvantage of low clipping ratio problem in clipping based-Active Constellation Extension (CB-ACE) technique for PAPR reduction in OFDM systems, we analyzed ACE algorithm with adaptive clipping control to STBC MIMO-OFDM systems. Simulation results demonstrate that the algorithm can reach the minimum PAPR for severely low clipping ratios, and the performance of this algorithm is superior to the performance of the ACE method in the single antenna OFDM system.

References

[1]. Wu, Y. and Zou, W.Y. (1995). “Orthogonal frequency division multiplexing: A multi-carrier modulation scheme", IEEE Trans. Consumer Electronics, 41(3), pp. 392- 399.

[2]. Hwang, T., Yang, C., Wu, G., Li, S. and Lee, G.Y. (2009). “OFDM and its Wireless Application: A Survey", IEEE Trans. Vehicular Technology, 58(4), pp. 1673-1694 (March).

[3]. Changiz Rezaei, S.S. and Pakravan, M.R (2006). ”Performance analysis of per tone equalization in DMTbased systems", Scientia Iranica, 13(4), pp. 355-363 .

[4]. Zhefeng Li and Xiang-Gen Xia (2008). “ PAPR Reduction for Space-Time-Frequency Coded MIMO-OFDM Systems using Chu sequence”, IEEE Transaction on Wireless Communications, Vol 7, No. 4.

[5]. Jing Gao, Jinkuan Wang and Yun Wang (2007). “A Low Complexity PAPR Reduction technique for STBC MIMOOFDM System”, Proceedings of International Conference on Wireless Communications, and mobile computing, Shanghai, September, PP. 109-112.

[6]. Seung Hee Han, JaeHong Lee, (2005). “An Overview: Peak-to-Average Power Ratio Reduction Techniques for Multicarrier Transmission ” IEEE wireless Communications.

[7]. Tao Jiang and Yiyan Wu, (2008). “An Overview: Peakto- Average Power Ratio Reduction Techniques for OFDM Signals”, IEEE Transactions on Broadcasting, vol. 54, No. 2, June, pp. 257-267.'

[8]. R. O'Neill and L.N. Lopes, (1995). “Envelope Variations and Spectral Splatter in Clipped Multicarrier Signals”, Proceedings of International Symposium on Personal, Indoor and Mobile Radio Communications, Toronto, Ont., Canada, September, Vol.1, pp. 71–75.

[9]. Jun Hou, Jianhua Ge and Jing Li, (2010). “Peak-to- Average Power Ratio Reduction of OFDM Signals using PTS Scheme with Low Computational Complexity”, IEEE Transactions on Broadcasting, Vol.57, No.1, September pp. 143-148.

[10]. Yung-Lyul Lee, Young-Hwan You, Won-Gi Jong-Ho Paik and Hyoung-Kyu Song (2003). “Peak-to-Average Power Ratio Reduction in MIMO OFDM System using Selective mapping”, IEEE Communications Letters, Vol.7, No.12, December, pp.575-577.

[11]. Theodoros Tsiligkaridis and Douglass L. Jones, (2010). “PAPR Reduction Performance by Active Constellatioin Extension for Diversity MIMO-OFDM Systems”, Journal of Electrical and Computer Engineering, Vol. Article ID 930368, 2010.

[12]. Tan, M., Latinovic, Z., & Bar-Ness, Y (2005). STBC MIMO-OFDM peak-to-average power ratio reduction by cross-antenna rotation and inversion. IEEE Communication Letters, 9(7), 592-594.

[13]. B.S. Krongold and D. L. Jones, (2003). “PAPR Reduction in OFDM via the Active constellation extension”, IEEE Trnansactions on Broadcasting, Vol. 49, No. 3, pp. 258- 268.

[14]. L. Wang and C. Tellambura, (2006). “An adaptivescaling algorithm for OFDM PAR reduction using active constellation extension,” in Proc. IEEE Veh. Technology Conf., Sep. pp. 1–5.

[15]. E. Van der Ouderaa, J. Schoukens, and J. Renneboog, (1988). “Peak factor minimization using a time-frequency domain swapping algorithm,” IEEE Trans. Instrum. Meas., Vol. 37, No. 1, pp. 145–147, Mar.

[16]. Kitaek Bae, G. Andrews, and Edward J. Powers, (2010). “Adaptive Active Constellation Extension Algorithm for Peak-to-Average Ratio Reduction in OFDM” IEEE Communications letters, Vol. 14, No. 1, January.

[17]. Mahmoud Ferdosizadeh Naeiny, Farokh Marvasti, (2011). ” PAPR reduction of space-frequency coded OFDM systems using Active Constellation Extension”, Int. J. Electron. Commun. (AEÜ) 65 873– 878.

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Research Paper

OVSF Code Assignment for Wideband Code Division Multiple Access (WCDMA) in FPGA

P. Kavipriya* , C. Gomathi**

* Research Scholar, Sathyabama University, Chennai, India.

** Professor & Head, SRM University, Chennai, India.

Kavipriya, P., and Gomathy, C. (2012). OVSF Code Assignment For Wideband Code Division Multiple Access (WCDMA) in FPGA, i-manager’s Journal on Wireless Communication Networks. 1(3), 8-13. https://doi.org/10.26634/jwcn.1.3.2049

Abstract

This paper describes the wideband Direct Sequence Code Division Multiple Access (WCDMA) wireless transmitter design using Field Programmable Gate Array (FPGA), which has been adopted in many wireless access technologies. Four separate blocks have been designed using digital approach to form the transmitter circuit diagram using the oscillator, the OVSF-code generator, the Parity Check, and the BPSK modulator. The WCDMA air interface was initially designed to support a wide variety of services with different QoS requirements having a maximum bit rate of 2 Mb/s. In order to satisfy the future service and application needs several technical enhancements are being studied and standardized for WCDMA in 3GPP. Wideband code division multiple access (WCDMA) uses orthogonal variable spreading factor (OVSF) codes to support diversified data transmission rates and quality of service (QoS). In this paper, we propose a improved OVSF code assignment to support QoS for WCDMA.The Synopsys software has been used for the design synthesis and simulation; the Very High Speed Integrated Circuit Hardware Description Language (VHDL) program was used for coding and FPGA for compiling and downloading the simulation. The WCDMA wireless transmitter was designed to transmit with data rates up to 2 Mbps. The transmitted signals were carried with a 40 MHz carrier frequency.

References

[1] T. Minn and K.-Y. Siu, (2000). “Dynamic assignment of orthogonal variable- spreading-factor codes in W-CDMA,” IEEE J. Sel.Areas Commun., Vol. 18, No. 8, pp. 1429–1440, Aug.

[2] Y.-C. Tseng and C.-M. Chao, “Code placement and replacement strategies for wideband CDMA OVSF code tree management,” IEEE Trans. Mobile Comput., Vol. 1, No. 4, pp. 293–302, Oct.–Dec. 2002.

[3] W.T. Chen, Y.P. Wu, and H.C. Hsiao, “A novel code assignment scheme for W-CDMA systems,” in Proc. IEEE VTC—Fall, Atlantic City, NJ, 2001, pp. 1182–1186.

[4] R. Assarut, K. Kawanishi, U. Yamamoto, Y. Onozato, and M. Masahiko, “Region division assignment of orthogonal variable-spreading-factor codes in W-CDMA,” in Proc. IEEE VTC—Fall, Atlantic City, NJ, 2001, pp. 1884–1888.

[5] F. Shueh and W.S.E. Chen, “Code assignment for IMT- 2000 on forward radio link,” in Proc. IEEE VTC—Spring, Rhodes, Greece, 2001, pp. 906–910.

[6] F. Adachi, M. Sawahashi, and K. Okawa, “Treestructured generation of orthogonal spreading codes with different lengths for forward link of DS- CDMA mobile radio,” Electron. Lett., Vol. 33, No. 1, pp. 27–28, Jan. 1997.

[7] C.-M. Chao, Y.-C. Tseng, and L.-C. Wang. “Dynamic bandwidth allocation for multimedia traffic with rate guarantee and fair access in WCDMA systems”, IEEE Trans. on Mobile Computing, Vol. 4, issue 5, pp. 420-429, Sept. 2005.

[8] Dian Gong, Yusong Yan and Jianhua Lu. “Dynamic code assignment for OVSF code system”, Global telecommunications conferences 2005, Vol. 5, pp. 2865- 2869, Dec. 2005.

[9] Min-Xiou Chen, Ren-Hung Hwang. “Efficient OVSF code as- signment and reassignment strategies in UMTS”, IEEE Trans. on Mobile Computing, Vol. 5, No. 7, July 2006.

[10] Shuming Guo, Jianhua Peng, Jiangxing Wu. “A reassignment code allocation scheme for multirate services on OVSF CDMA cellular networks”, International conferences on wireless com- munications, networking and mobile computing, pp. 965-969, Sept. 2007.

[11] Yuh - Ren Tsai, Li-Cheng Lin. “Quality-based OVSF code assignment and reassignment strategies for WCDMA system”, IEEE Trans. on Vehicular Technology, Vol. 58, No. 2, February 2009.

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Research Paper

Tomorrow’s EARTHNET – Connecting Earth to Mars using WRP (Wireless Routing Protocol).

Dhivya*

Karpaga Vinayaga College of Engineering and Technology, Tamil Nadu, India.

Dhivya, S.B. (2012). Tomorrow's Earthnet – Connecting Earth to Mars using WRP, i-manager’s Journal on Wireless Communication Networks. 1(3), 14-19. https://doi.org/10.26634/jwcn.1.3.2050

Abstract

The Interplanetary Internet is a next-generation space network architecture proposed by NASA which aims to establish a communication infrastructure in deep space and connect planets and satellites etc. The vision of future space exploration includes missions to deep space that require communication among planets, moons, satellites, asteroids, robotic spacecrafts, and crewed vehicles. These missions produce significant amount of scientific data to be delivered to the Earth. IPN Internet is an often disconnected and store-and-forward ‘network of Internet’ based on a wireless backbone with huge delays and error prone links. The first application of IPN Internet may be the “Mars network” which is now being developed to facilitate the exploration of Mars. In this paper, with concern to establishing the paths among the nodes, rovers and in order to transfer data with an efficient and scalable manner Wireless Routing Protocol (WRP) which uses the Bellman Ford algorithm to calculate paths is implemented with simulation results. Because of the mobile nature of the nodes this protocol introduces mechanisms which reduce route loops and ensure reliable message exchange.

References

[1]. Mukherjee, Joyeeta, "Routing over the Interplanetary Internet" (2012). Computer Science and Engineering: Theses, Dissertations, and Student Research. Paper 42.

[2]. InterPlaNetary Internet: state-of-the-art and research challenges Ian F. Akyildiz, B. Akan , Chao Chen, Jian Fang, Weilian Su Broadband and Wireless Networking Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

[3]. Classification of Ad Hoc Routing Protocols Petteri Kuosmanen Finnish Defence Forces Naval Academy.

[4]. “Bellman-Ford Algorithm”, Snezhana Gocheva-Ilieva, snow@uni-plovdiv.bg

[5]. “Technologies Interplanetary Network and Information Systems”, Directorate Jet Propulsion Laboratory California Institute of Technology Core Technologies for Space Conference, November 28, 2001.

[6]. TP-Planet: A Reliable Transport Protocol for InterPlaNetary Internet O¨ zgu¨r B. Akan, Student Member, IEEE, Jian Fang, and Ian F. Akyildiz, Fellow, IEEE.

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Research Paper

Application of Wireless Sensor Network through Efficient and Secure Routing Protocol

S. Ganesh* , R. Amutha**

* Research Scholar, Sathyabama University, Chennai, India.

** Professor, Faculty of Electronics & Communication Engineering, SSN College of Engineering, Chennai, India.

Ganesh, S., and Amutha, R. (2012). Application Of Wireless Sensor Network Through Efficient And Secure Routing Protocol, i-manager’s Journal on Wireless Communication Networks. 1(3), 20-34. https://doi.org/10.26634/jwcn.1.3.2051

Abstract

A sensor network is an infrastructure comprised of sensing (measuring), computing, and communication elements that gives an administrator the ability to instrument, observe, and react to events and phenomena in a specified environment. Patients who have survived cardiac attack or other physiological problems are at a higher risk of sudden cardiac death. Many of these patients are living at home without any kind of cardiac monitoring systems. By using a wearable monitoring system for detection of ECG systole,Diastole,Flux,Bodyemperature,Weight,Accelerometer Latitude and Longitudinal location, it is possible to alert healthcare professional to the patient’s condition so that the necessary action for an emergency rescue can occur. A special purpose sensor network here, designed to operate autonomously to connect varies medical sensors placed on the human body. In this system, we effectively monitors the patients physiological status such as ECG, Body temperature, systole, diastole, Heartbeat, flex, Accelerometer and successfully processed in the transmitter kit, which is attached in the patients body. Effectively transmits the data from the transmitter kit through a GPRS to the receiver which is located in the hospital server.

References

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[5]. Gaddam, A., &Mukhopadhyay, S.C. Gupta, G.S. Elder Care Based on Cognitive Sensor Network. IEEE Sensors J. 2011, 11, 574-581.

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[7]. Malan, D.; Jones, T.F.; Welsh, M.; Moulton, & S. CodeBlue: An Ad-Hoc Sensor Network Infrastructure for Emergency Medical Care. In Proceedings of the MobiSys 2004 Workshop on Applications of Mobile Embedded Systems (WAMES 2004), Boston, MA, USA, 6–9 June 2004.

[8]. Dimitriou, T.; & Loannis, K. Security Issues in Biomedical Wireless Sensor Networks. In Proceedings of 1st International Symposium on Applied Sciences on Biomedical and Communication Technologies (ISABEL'08), Aalborg, Denmark, 25–28 October 2008.

[9]. Muhammad, K.R.R.S.; Lee, H.; Lee, S.; & Lee, Y.K. BARI+: A Biometric Based Distributed Key Management Approach for Wireless Body Area Networks. Sensors 2010, 10, 3911- 3933.

[10]. Alonso, J.V.; Matencio, P.L.; Castano, F.J.G.; Hellin, H.N.; Guirao, P.J.B.; Martinez, F.J.P.; Alvarez, R.P.M.; Jimenez, D.G.; Castineira, F.G.; & Fernandez, R.D. Ambient Intelligence Systems for Personalized Sport Training. Sensors 2010, 10, 2359-2385.

[11]. Chen, B.R.; Peterson, G.; Mainland, G.; Welsh, & M. LiveNet: Using Passive Monitoring to Reconstruct Sensor Network Dynamics. In Proceedings of the 4th IEEE International Conference on Distributed Computing in Sensor System (DCOSS'08), Santorini Island, Greece, 11–14 June 2008.

[12]. Halteren, A.V.; Bults, R.; Wac, K.; Konstantas, D.; Widya, I.; Dokovsky, N.; Koprinkon, G.; Jones, V.; & Jerzog, R. Mobile Patient Monitoring: The MobiHealth System. J. Inform. Tech. Healthcare 2004, 2, 365-373.

[13]. Wood, A.; Virone, G.; Doan, T.; Cao, Q.; Selavo, L.; Wu, Y.; Fang, L.; He, Z.; Lin, S.; Stankovic, & J. ALARM-NET: Wireless Sensor Networks for Assisted-Living and Residential Monitoring; Technical Report CS-2006-01; Department of Computer Science, University of Virginia: Charlottesville, VA, USA, 2006. Sensors 2012.

[14]. Ng, J.W.P.; Lo, B.P.L.; Wells, O.; Sloman, M.; Peters, N.; Darzi, A.; Toumazou, C.; & Yang, G.-Z. Ubiquitous Monitoring Environment for Wearable and Implantable Sensors (UbiMon). In Proceedings of 6th International Conference on Ubiquitous Computing (UbiComp'04), Nottingham, UK, 7–14 September 2004.

[15]. Fischer, M.; Lim, Y.Y.; Lawernce, E.; Ganguli, & L.K. ReMoteCase: Health Monitoring with Streaming Video. In Proceedings of 7th International Conference on Mobile Business, Barcelona, Spain, 7–8 July 2008; pp. 280-286.

[16]. Chakravorty, R. A Programmable Service Architecture for Mobile Medical Care. In Proceedings of 4th Annual IEEE International Conference on Pervasive Computing and Communication Workshop (PERSOMW'06), Pisa, Italy, 13–17 March 2006.

[17]. Rajasekaran, M.P.; Radhakrishnan, S.; & Subbaraj, P. Sensor Grid Applications in Patient Monitoring. Future Generat. Comput. Syst. 2010, 26, 569-575.

[18]. Montgomery, K.; Mundt, C.; Thonier, G.; Tellier, A.; Udoh, U.; Barker, V.; Ricks, R.; Giovangrandi, L.; Davies, P.; Cagle, Y.; Swain, J.; Hines, J.; & Kovacs, G. Lifeguard—A Personal Physiological Monitor for Extreme Environments. In Proceedings of the 26th Annual International Conference of the IEEE EMBS, San Francisco, CA, USA, 1–5 September 2004; pp. 2192-2195.

[19]. Gao, T.; Massey, T.; Selavo, L.; Crawford, D.; Chen, B.R.; Lorincz, K.; Shnayder, V.; Hauenstein, L.; Dabiri, F.; Jeng, J.; Chanmugam, A.; White, D.; Sarrafzadeh, M.; & Welsh, M. (2007) The Advanced Health and Disaster Aid Network: A Light-Weight Wireless Medical System for Triage. IEEE Trans. Biomed. Circ. Syst. , 1, 203-216.

[20]. Jiang, S.; Cao, Y.; Iyengar, S.; Kuryloski, P.; Jafari, R.; Xue, Y.; Bajcsy, R.; Wicker, S.; & CareNet. (2008). An Integrated Wireless Sensor Networking Environment for Remote Healthcare. In Proceedings of 8th International Conference on Body Area Networks, Brussels, Belgium, 13–15 March.

[21]. Mahmoud, A.S.; Sheltami, T.R.; & Amara, M.H.A. (2006). Wireless Sensor Network Implementation for Mobile Patient. In Proceedings of International Conference on Grid and Cooperative Computing, Manama, Bahrain, 20–22 March.

[22]. Farella, E.; Pieracci, A.; Brunelli, D.; Benini, L.; Ricco, B.; & Acquaviva, A. (2005). Design and Implementation of WiMoCA Node for a Body Area Wireless Sensor Network. In Proceedings of System Communication, Montreal, QC, Canada, 14–17 August; pp. 342-347.

[23]. Nee, O.; Hein, A.; Gorath, T.; Hulsmann, N.; Laleci, G.B.; Yuksel, M.; Olduz, M.; Tasyurt, I.; Orhan, U.; Dogac, A.; Fruntelata, A.; Ghiorghe, S.; Ludwig, & R. SAPHIRE. (2008) Intelligent Healthcare Monitoring Based on Semantic Interoperability Platform: Pilot Applications. IET Commun, 2, 192-201.

[24]. Han, D.; Lee, M.; Park, S. (2009) THE-MUSS: Mobile u- Health Service System. Biomed. Eng. Syst. Tech., 25, 377-389.

[25]. Koch, S.; & Hagglund, M (2009). Health Informatics and the Delivery of Care to Older People. Maturitas, 63, 195-199.

[26]. Chung, W.Y.; Yan, C.; & Shin, K.A. (2007). Cell Phone Based Health Monitoring System with Self Analysis Processing Using Wireless Sensor Network Technology. In Proceedings of 29th Annual International Conference on the IEEE EMBS, Lyon, France, 23–26 August. Sensors 2012, 1287

[27]. Gravina, R.; Guerrieri, A.; Fortino, G.; Bellifemine, F. Giannantonio, R.; & Sgroi, M. Development of Body Sensor Network Application Using SPINE. In Proceedings of IEEE International Conference on Systems, Man and Cybernetics (SMC 2008), Singapore, 12–15 October 2008.

[28]. Lorincz, K.; Chen, B.; Challen, G.W.; Chowdhury, A.R.; Patel, S.; Bonato, P.; & Welsh, M. Mercurty: A Wearable Sensor Network Platform for High-Fidelity Motion Analysis. In Proceedings of 7th ACM Conference on Embedded Networked Sensor Systems (SenSys'09), Berkeley, CA, USA, 4–6 November 2009.

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Research Paper

Energy Conservation In Wireless Sensor Networks Using Node Reputation Ranking

P. Jai Balaji* , S. Anandamurugan**

* PG student, Computer Science Engineering, Kongu Engineering College, Erode, India.

** Assistant Professor, Information Technology, Kongu Engineering College, Erode, India

Balaji, P.J., and Anandamurugan, S. (2012). Energy Conservation in Wireless Sensor Networks Using Node Reputation Ranking, i-manager’s Journal on Wireless Communication Networks, 1(3), 35-40. https://doi.org/10.26634/jwcn.1.3.2052

Abstract

Heavy traffic load at certain locations in Wireless sensor networks generates hot spots which leads the nodes to deplete energy resources quickly and degrade network services. The Cluster head (CH) have the additional responsibility in collecting and transmitting information. As distance to sink decreases, relay load on CH gets increased. In order to balance traffic load and energy consumption, CH role is rotated across all nodes. Based on the hop distance to data sink, equalization of node lifetime and reduced energy consumption levels, suitable cluster size is determined by the existing distributed energy efficient clustering algorithm. Here, end to end energy consumption is calculated by the energy efficient multi-hop data collection protocol. Mobile sensor node cannot be arbitrarily chosen as CH and fluctuation in hot spot region is high and mainly sensor node’s unwillingness to serve the network as the CH are the drawbacks. The proposed scheme Mobility Aware cluster head selection calculates node reputation to have better cluster head in the hot spots of WSN. Based on node reputation and mobility rate, node ranking is calculated and the clustering efficiency can be measured in terms of cooperativeness and mobility of sensor nodes. However, certain sensor nodes have high mobility and certain nodes will be unwilling to serve the network. The proposal presents Mobility Aware Reputation Node Ranking (MARNR) technique to improve the efficiency of clustering at hot spot regions. MARNR identifies the senor nodes mobility rate.

References

[1]. Bandyopadhyay, S., and Coyle, E.J. (2003, March). An energy efficient hierarchical clustering algorithm for wireless sensor networks. In Proceedings INFOCOM, pp. 1713–1723.

[2]. Matta, I., Smaragdakis, G., and Bestavros, A. (2004, August) SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. SANPA

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[6]. Perillo, M., Cheng, Z., and Heinzelman, W. (2005). An analysis of strategies for mitigating the sensor network hot spot problem. In Proceedings Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services,pp. 474–478.

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[9]. Ye, M., Li, C., Chen, G., and Wu, J. (2005 April). EECS: an energy efficient clustering scheme in wireless sensor networks. In Proceedings IPCCC, pp. 535–540.

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

Current Issue Vol. 13 Issue 1

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Volume 1 Issue 3 October - December 2012

PAPR Reduction of STBC MIMO- OFDM Systems Using Adaptive Active Constellation Extension

K Srinivasa Rao* , B. Prabhakara Rao**

* Electronics and Communication Engineering, G.V.P College of Engineering for Women, Visakhapatnam, A.P, India. ** Electronics and Communication Engineering, J.N.T University, Kakinada, A.P, India.

Rao, K.S., and Prabakararao, B. (2012). PAPR Reduction of STBC MIMO-OFDM Systems Using Adaptive Active Constellation Extension. i-manager’s Journal on Wireless Communication Networks, 1(3), 1-7. https://doi.org/10.26634/jwcn.1.3.2048

Abstract

References

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OVSF Code Assignment for Wideband Code Division Multiple Access (WCDMA) in FPGA

P. Kavipriya* , C. Gomathi**

* Research Scholar, Sathyabama University, Chennai, India. ** Professor & Head, SRM University, Chennai, India.

Kavipriya, P., and Gomathy, C. (2012). OVSF Code Assignment For Wideband Code Division Multiple Access (WCDMA) in FPGA, i-manager’s Journal on Wireless Communication Networks. 1(3), 8-13. https://doi.org/10.26634/jwcn.1.3.2049

Abstract

References

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Tomorrow’s EARTHNET – Connecting Earth to Mars using WRP (Wireless Routing Protocol).

Dhivya*

Karpaga Vinayaga College of Engineering and Technology, Tamil Nadu, India.

Dhivya, S.B. (2012). Tomorrow's Earthnet – Connecting Earth to Mars using WRP, i-manager’s Journal on Wireless Communication Networks. 1(3), 14-19. https://doi.org/10.26634/jwcn.1.3.2050

Abstract

References

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Application of Wireless Sensor Network through Efficient and Secure Routing Protocol

S. Ganesh* , R. Amutha**

* Research Scholar, Sathyabama University, Chennai, India. ** Professor, Faculty of Electronics & Communication Engineering, SSN College of Engineering, Chennai, India.

Ganesh, S., and Amutha, R. (2012). Application Of Wireless Sensor Network Through Efficient And Secure Routing Protocol, i-manager’s Journal on Wireless Communication Networks. 1(3), 20-34. https://doi.org/10.26634/jwcn.1.3.2051

Abstract

References

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Energy Conservation In Wireless Sensor Networks Using Node Reputation Ranking

P. Jai Balaji* , S. Anandamurugan**

* PG student, Computer Science Engineering, Kongu Engineering College, Erode, India. ** Assistant Professor, Information Technology, Kongu Engineering College, Erode, India

Balaji, P.J., and Anandamurugan, S. (2012). Energy Conservation in Wireless Sensor Networks Using Node Reputation Ranking, i-manager’s Journal on Wireless Communication Networks, 1(3), 35-40. https://doi.org/10.26634/jwcn.1.3.2052

Abstract

References

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* Electronics and Communication Engineering, G.V.P College of Engineering for Women, Visakhapatnam, A.P, India.

** Electronics and Communication Engineering, J.N.T University, Kakinada, A.P, India.

* Research Scholar, Sathyabama University, Chennai, India.

** Professor & Head, SRM University, Chennai, India.

* Research Scholar, Sathyabama University, Chennai, India.

** Professor, Faculty of Electronics & Communication Engineering, SSN College of Engineering, Chennai, India.

* PG student, Computer Science Engineering, Kongu Engineering College, Erode, India.

** Assistant Professor, Information Technology, Kongu Engineering College, Erode, India