This article proposes a novel speed-based handover algorithm for mobility management between macrocells and femtocells in LTE networks. Existing handover decision algorithms are compared. The proposed algorithm uses a mobile's speed to determine whether to handover from a macrocell to a femtocell or vice versa. Simulation results show the performance of the proposed algorithm. The algorithm aims to guarantee efficient handovers between different cell types in a hierarchical LTE structure.

1. Most Viewed Articles inWireless
& Mobile Networks
International Journal of Wireless & Mobile
Networks (IJWMN)
ISSN: 0975-3834 [Online]; 0975-4679 [Print]
http://airccse.org/journal/ijwmn.html

2. FAULT DETECTION AND RECOVERY IN WIRELESS SENSOR
NETWORK USING CLUSTERING
Abolfazl Akbari1, Arash Dana2, Ahmad Khademzadeh3 and Neda Beikmahdavi4
1Dept. of Computer Engineering, Islamic Azad University Ayatollah Amoli Branch, Amol,
Iran
2Islamic Azad University, Central Tehran Branch, Tehran, Iran
3Iran Telecom Research Center, Tehran, Iran
4 Islamic Azad University Ayatollah Amoli Branch, Amol, Iran
ABSTRACT
Some WSN by a lot of immobile node and with the limited energy and without further charge
of energy. Whereas extension of many sensor nodes and their operation. Hence it is normal.
unactive nodes miss their communication in network, hence split the network. For avoidance
split of network, we proposed a fault recovery corrupted node and Self Healing is necessary.
In this Thesis, we design techniques to maintain the cluster structure in the event of failures
caused by energy-drained nodes. Initially, node with the maximum residual energy in a
cluster becomes cluster heed and node with the second maximum residual energy becomes
secondary cluster heed. Later on, selection of cluster heed and secondary cluster heed will be
based on available residual energy. We use Matlab software as simulation platform
quantities. like, energy consumption at cluster and number of clusters is computed in
evaluation of proposed algorithm. Eventually we evaluated and compare this proposed
method against previous method and we demonstrate our model is better optimization than
other method such as Venkataraman, in energy consumption rate.
KEYWORDS
Sensor Networks, clustering, fault detection, fault recovery.
Full Text: http://airccse.org/journal/jwmn/0211ijwmn12.pdf
Volume Link: http://airccse.org/journal/jwmn_current11.html

3. REFERENCES
[1] A. Bharathidasas, and V. Anand, “Sensor networks: An overview”, Technical report,
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[5] E. S. Biagioni and G. Sasaki, “Wireless sensor placement for reliable and efficient data
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[6] G. Gupta and M. Younis, “Load-Balanced Clustering in Wireless Sensor Networks”, in
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May 2003.
[7] J. Chen, S. Kher and A. Somani, “Distributed Fault Detection of Wireless Sensor
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[8] F. Koushanfar, M. Potkonjak, A. Sangiovanni- Vincentelli, “Fault Tolerance in Wireless
Ad-hoc Sensor Networks”, Proceedings of IEEE Sensors 2002, June, 2002.
[9] W. L. Lee, A. Datta, and R. Cardell-Oliver, “Network Management in Wireless Sensor
Networks”, to appear in Handbook on Mobile Ad Hoc and Pervasive Communications, edited
by M. K. Denko and L. T.Yang, American Scientific Publishers.
[10] G. Venkataraman, S. Emmanuel and S.Thambipillai, “Energy-efficient cluster-based
scheme for failure management in sensor networks” IET Commun, Volume 2, Issue 4, April
2008 Page(s):528 – 537
[11] L. Paradis and Q. Han, “A Survey of Fault Management in Wireless Sensor Networks”,
Journal of Network and Systems Management, vol. 15, no. 2, pp. 171-190, 2007.
[12] L. M. S. D. Souza, H. Vogt and M. Beigl, “A survey on fault tolerance in wireless sensor
networks”, 2007.
[13] W. L Lee, A.D., R. Cordell-Oliver, WinMS: Wireless Sensor Network-Management
System, An Adaptive Policy-Based Management for Wireless Sensor Networks. 2006.
[14] L. B. Ruiz, I. G.Siqueira, L. B. Oliveira, H. C. Wong, J.M. S. Nigeria, and A. A. F.
Loureiro. “Fault management in event-driven wireless sensor networks”, MSWiM’04,
October 4-6, 2004, Venezia, Italy
[15] G. Gupta and M. Younis; Fault tolerant clustering of wireless sensor networks;
WCNC’03, pp. 1579.1584.

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detection in sensor networks”, in Proceedings of the 24th Annual Joint Conference of the
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Miami, Fla, USA, March 2005
[17] C. Hsin and M.Liu, “Self-monitoring of Wireless Sensor Networks”, Computer
Communications, 2005. 29: p. 462-478
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Comput. Commun., 2002, 25, (14), pp. 1273-1282.
[19] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy-Efficient
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IEEE WCNC, New Orleans, USA,March 2003, vol. 3, p. 1579 – 1584
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anAmorphous Computer”, MIT AI Memo 1666, August 1999

5. BROWSER GAMES FOR ONLINE COMMUNITIES
Juha-Matti Vanhatupa
Department of Software Systems, Tampere University of Technology, Tampere, Finland
ABSTRACT
Games played directly inside the web browser have many benefits. Browser games do not
need software installation. Furthermore since the web has become the ultimate collaboration
environment, the games are available for numerous players that can play in collaborative
fashion. Through history online communities have birth alongside with browser games.
Nowadays online communities have achieved massive user numbers and those can be
important part of the browser game itself. This article targets at analyzing and categorizing of
browser games. We also discuss financial opportunities relating to browser games and
technologies used in those.
KEYWORDS
Browser Games, Game Analysis, Online Communities
Full Text: http://airccse.org/journal/jwmn/0203ijwmn03.pdf
Volume Link: http://airccse.org/journal/jwmn_current10.html

6. REFERENCES
[1] Facebook Social Utility, http://www.facebook.com/
[2] Travian Browser Game, http://www.travian.com/
[3] Hattrick Browser Game, http://www.hattrick.org/
[4] Vanhatupa Juha-Matti (2010) “Browser Games: The New Frontier of Social Gaming”, In
Proc of Second International Conference of Wireless & Mobile Networks. CCIS Vol. 84, pp.
349-355, Springer Berlin Heidenberg
[5] Barton Matt, (2008) Dungeons & Desktops, The History of Computer Role Playing
Games, A.K. Peters, pp. 37-43.
[6] Earth 2025 Browser Game, http://games.swirve.com/earth
[7] Facebook Statistics, http://www.facebook.com/press/info.php?statistics
[8] Mafia Wars Facebook application,
http://www.facebook.com/apps/application.php?id=10979261223
[9] Dogs of the Seas Browser Game, http://www.dogsoftheseas.com/
[10] DarkOrbit Browser Game, http://www.darkorbit.com/
[11] ForumWarz Browser Game, http://www.forumwarz.com/
[12] Stick Arena Browser Game, http://www.xgenstudios.com/play/stickarena
[13] Habbo Hotel Virtual World, http://www.habbo.com/
[14] Hattrick history, http://hattrick.org/Help/History.aspx
[15] Häsel Mathias, (2007) “Rich Internet Architectures for Browser-Based Multiplayer
Real-Time Games –Design and Implementation Issues of virtual-kicker.com”, In: Enokido,
T./Barolli, L./Takizawa, M. (Eds.), Network-Based Information Systems: First International
Conference, NBiS 2007. LNCS, vol. 4658, pp. 157-166, Berlin/Heidelberg: Springer-Verlag
[16] Mizanian Kiarash, Vasef Mehdi, Analoui Morteza, (2010) ”Bandwidth Modeling and
Estimation in Peer to Peer Networks”, International Journal of Computer Networks &
Communications (IJCNC), Vol. 2, No. 3.
[17] Klemm Alexander, Lindemann Christoph, Waldhorst Oliver P., (2003), “A Special-
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[18] Sharma Abhishek, Shi Hao, (2010) “Innovative Rated-Resource Peer-to-Peer Network”,
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[20] Facebook Advertising, http://www.facebook.com/advertising/
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7. [22] Magic: The Gathering collectible card game,
http://www.wizards.com/magic/multiverse/default.aspx
[23] Club Penguin Browser Game, http://www.clubpenguin.com/
[24] Walmsley Andrew, Kids’ Virtual Worlds are Maturing Nicely,
http://www.marketingmagazine.co.uk/news/756021/
[25] Schultheiss Daniel, (2007) “Long-term Motivations to Play MMOGs: A Longitudinal
Study on Motivations, Experience and Behavior”, In Proc of the DiGRA 2007 - Situated
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workshop on Network and system support for games.

8. A NOVEL APPROACH FOR MOBILITY MANAGEMENT IN LTE
FEMTOCELLS
1Pantha Ghosal, 2Shouman Barua, 3Ramprasad Subramanian, 4Shiqi Xing and 5Kumbesan
Sandrasegaran
1,2,3,4,5,6Centre for Real-time Information Networks
School of Computing and Communications, Faculty of Engineering and Information
Technology, University of Technology Sydney, Sydney, Australia
ABSTRACT
LTE is an emerging wireless data communication technology to provide broadband
ubiquitous Internet access. Femtocells are included in 3GPP since Release 8 to enhance the
indoor network coverage and capacity. The main challenge of mobility management in
hierarchical LTE structure is to guarantee efficient handover to or from/to/between
Femtocells. This paper focuses, on different types of Handover and comparison performance
between different decision algorithms. Furthermore, a speed based Handover algorithm for
macro-femto scenario is proposed with simulation results
KEYWORDS
Femtocell Access Point (FAP), Handover Hysteresis Margin (HMM), Reference Signal
Received Power (RSRP), Reference Signal Received Quality (RSRQ), Signal to Interference
Plus Noise Ratio (SINR, Evolved NodeB (eNB), User equipment (UE).
Full Text: http://airccse.org/journal/jwmn/6514ijwmn04.pdf
Volume Link: http://airccse.org/journal/jwmn_current14.html

9. REFERENCES
[1] L. Nuaymi, WiMAX: Technology for Broadband Wireless Access. Wiley, NewYork,
2008.
[2] E Dahlman, S Parkvall, J Skold, P Beming, 3G Evolution HSPA and LTE for Mobile
Broadband. Academia Press, USA, 2008.
[3] F. Capozzi, G. Piro, L. Grieco, G. Boggia, P. Camarda, "On Accurate simulations of LTE
femtocells using an open source simulator," in EURASIP Journal on Wireless
Communication and Networking, 2012.
[4] Onyeije Consulting LLC, Solving the capacity crunch (2011).
[5] T. Zahir, K. Arshad, A. Nakata, K. Moessner,“Interference Management in Femtocells,”
in Commun. Surveys & Tutorials, vol. 15, pp. 293-311, 2013.
[6] www.en.wikipedia.org/wiki/Fixed_mobile_convergence/.
[7] R. Bendlin, V. Chandrasekhar, C. Runhua, A. Ekpenyong, and E. Onggosanusi, "From
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in 45th Annu. Conf., Inform. Sci. and Syst. (CISS), Baltimore, MD, pp. 1-5, 2011.
[8] H. Mahmoud, I .Guvenc,” A comparative study of different deployment modes for
femtocell networks,” in IEEE Int. Symposium on Personal, Indoor and Mobile Radio
Commun. , Palo Alto, USA, pp. 1–5, 2009.
[9] D. Xenakis, N. Passas, L. Merakos, C. Verikoukis, “Mobility Management for Femtocells
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Commun. Surveys & Tutorials., vol. 16 pp. 2014.
[10] J. Moon, D. Cho, “Efficient handoff algorithm for inbound mobility in hierarchical
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[12] D. Lopez-Perez, A. Valcarce, A. Ladanyi, G. de la Roche, J. Zhang, “Intracell handover
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EURASIPJ. on Wirel. Com
[13] A. Ulvan, M. Ulvan, and R. Bestak, “The Enhancement of Handover Strategy by
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[14] A. Ulvan, R.Bestak, M.Ulvan,“Handover Scenario and Procedure in LTE-based
Femtocell Networks," UBICOMM 4th Intl. Conf. on mobile ubiquitous computing, system,
services and tech.Florance, Italy, 2010.

10. [15] H. Zhang, X. Wen, B. Wang, W. Zheng, Y. Sun, “A Novel Handover Mechanism
Between Femtocell and Macrocell for LTE Based Networks”, IEEE 2nd Internat. Conf. on
Comm. Softw. and Nets. 2010 (ICCSN), pp.228-231, Feb. 2010.
[16] D. Xenakis, N. Passas, and C. Verikoukis, “A Novel Handover Decision Policy for
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Conf. (ICC), pp.1352-1356, June 2012.
[17] D. Xenakis, N. Passas, C. Verikoukis, “An energy-centric handover decisionalgorithm
for the integrated LTE macrocell-femtocell network”, Comp. Comm., Elsevier, 2012
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2011.
[20] T. Camp, J. Boleng, and V. Davies, “A survey of mobility models for ad hoc network
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2002.
[21] R Subramanian, P Ghosal, S Barua, S Xing, S Cong, K Sandrasegaran,'' Survey of LTE
Downlink Schedulers Algorithm in Open Access Simulation Tolls NS-3 and LTE-Sim '',
Manuscript in International Journal of Wireless & Mobile Networks(IJWMN), November
2014.

11. SYSTEM LEVEL SIMULATION FOR TWO TIER MACRO-FEMTO
CELLULAR NETWORKS
1Shiqi Xing, 2 Pantha Ghosal, 3Shouman Barua, 4 Ramprasad Subramanian and 5Kumbesan
Sandrasegaran
Centre for Real-time Information Networks
School of Computing and Communications, Faculty of Engineering and Information
Technology, University of Technology Sydney, Sydney, Australia.
ABSTRACT
LTE is an emerging wireless communication technology to provide high- speed data service
for the mobile phones and data terminals. To improve indoor coverage and capacity
Femtocells are included in 3GPP since Release 8. There is no common simulation platform is
available for performance justification of LTEFemtocells. LTE-Sim is an object-oriented
open source simulator which incorporates a complete protocol stack can be used for
simulating two-tier macro-femto scenarios. To the best of our knowledge no paper provides
the guideline to perform system level simulation of Femtocell networks. Here, in this paper
Femtocells performance is evaluated in multi-Macrocells and multi-Femtocells environment
with interference from Microcells and Macrocell users along with the scripting.
KEYWORDS
Channel quality indicator (CQI), Femto Access Point (FAP), Macro eNodeB (MeNB),
Macrocell User Equepment (MUE), Moblity Management Entity(MME), Signal to
Interference Plus Noise Ratio(SINR), Physical Layer(PHY)
Full Text: http://airccse.org/journal/jwmn/6614ijwmn01.pdf
Volume Link: http://airccse.org/journal/jwmn_current14.html

12. REFERENCES
[1] L. Nuaymi, WiMAX: Technology for Broadband Wireless Access. Wiley, NewYork,
2008.
[2] E Dahlman, S Parkvall, J Skold, P Beming, 3G Evolution HSPA and LTE for Mobile
Broadband. Academia Press, USA, 2008.
[3] F. Capozzi, G. Piro, L. Grieco, G. Boggia, P. Camarda, "On Accurate simulations of LTE
femtocells using an open source simulator," in EURASIP Journal on Wireless
Communication and Networking, 2012.
[4] G Piro, L Grieco, G Boggia, F Capozzi, P Camarda,”Simulating LTE cellular systems: an
opensource framework, ” in Vehicular Technology, IEEE Trans. vol. 60, pp. 498-513, 2011.
[5] Raheem, Rand, Aboubaker Lasebae, and Jonathan Loo. "Performance Evaluation of LTE
Network via Using Fixed/Mobile Femtocells." Advanced Information Networking and
Applications Workshops (WAINA), 2014 28th International Conference on. IEEE, 2014.
[6] WCDMA for UMTS – HSPA Evolution and LTE, Fourth Edition. Edited by Harri Holma
and Antti Toskala © 2007 John Wiley & Sons, Ltd. ISBN: 978-0-470-31933-8
[7] D. Lopez-Perez, I. Guvenc, G. de la Roche, M. Kountouris, T. Q. S. Quek, and Z. Jie,
"Enhanced intercell interference coordination challenges in heterogeneous networks," IEEE
Wireless Commun., vol. 18, pp. 22-30, 2011.
[8] D. Xenakis, N. Passas, L. Merakos, C. Verikoukis, “Mobility Management for Femtocells
in LTEAdvanced: Key Aspects and Survey of Handover Decision Algorithms” in IEEE
Trans. Wireless Commun., vol. 18 pp. 2011.
[9] R. Bendlin, V. Chandrasekhar, C. Runhua, A. Ekpenyong, and E. Onggosanusi, "From
homogeneous to heterogeneous networks: A 3GPP Long Term Evolution rel. 8/9 case study,"
in 45th Annu. Conf., Inform. Sci. and Syst. (CISS), Baltimore, MD, pp. 1-5, 2011.
[10] H. Mahmoud, I .Guvenc,” A comparative study of different deployment modes for
femtocell networks,” in IEEE Int. Symposium on Personal, Indoor and Mobile Radio
Commun. , Palo Alto, USA, pp. 1–5, 2009.
[11] Siemens, R1-060135, “Interference Mitigation by Partial Frequency Reuse,” 3GPP RAN
WG1#42, London, UK, January 2006.
[12] T. Camp, J. Boleng, and V. Davies, “A survey of mobility models for ad hoc network
research,” Wireless Communications and Mobile Computing, vol. 2, pp. 483–502, Aug.
2002.
[13] F. Capozzi, G. Piro, L. Grieco, G. Boggia, P. Camarda, " A system-level simulation
framework for LTE Femtocell," in Proc. of International Conference on Simulation Tools and
Techniques(ICST), Desenzano, Italy, pp.1-3, 2012.
[14] http://www.infoutils.com/frequency-reuse-in-ofdma-based-ltewimax-system/

13. EXPLAINABLE AI FOR AUTONOMOUS NETWORK FUNCTIONS IN
WIRELESS AND MOBILE NETWORKS
Premnath K Narayanan1 and David K Harrison2
1LM Ericsson Ltd., SA OSS PDU OSS S&T Research & PCT, Athlone, Ireland
2School of Computing, Glasgow Caledonian University, Glasgow, United Kingdom
ABSTRACT
As the telecommunication network components and functions are getting commoditized, the
complexity in configuration and optimization increases. Several automation techniques are
evolving from traditional deterministic algorithms (pre-defined rulesets obtained from
experience accumulated by humans) that were heuristic-based to more cognitive and
stochastic-based algorithms. The aim of this paper is to introduce the seven layers in wireless
telecommunication networks that uses stochastic or AI algorithms, explain the need for
monitoring and possible potential biases in each layer of the stochastic algorithm stack and
finally conclude with evaluation methods, techniques for detecting false positive and false
negative proposals in autonomous network functions. The main subject of the paper is to
provide a background on the need of explainable AI for autonomous network functions. The
paper includes introduction of two models ANOBIA and INFEROBIA models that helps to
achieve explainable AI for autonomous network functions in wireless and mobile networks.
KEYWORDS
Explainable AI; Machine Learning; Artificial Intelligence; Precision; Recall; BIAS;
Variance; Algorithm and Mitigation methods
Full Text: https://aircconline.com/ijwmn/V12N3/12320ijwmn03.pdf
Volume Link: http://airccse.org/journal/jwmn_current20.html

14. REFERENCES
[1] Paulo Valente Klaine, Muhammad Ali Imran, OluwakayodeOnireti, Richard Demo
Souza, "A Survey of Machine Learning Techniques Applied to Self-Organizing Cellular
Networks," IEEE Communications Surveys and Tutorials, IEEE, Volume 19, issue 4, pp.
2392-2431, DOI: 10.1109/COMST.2017.2727878, 2017
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16. A Proposed SAFER Plus Security algorithm using Fast Walsh Hadamard
transform for Bluetooth Technology
D.Sharmila1, R.Neelaveni2
1(Research Scholar), Associate Professor, Bannari Amman Institute of Technology,
Sathyamangalam, Tamil Nadu-638401.
2 Asst.Prof. PSG College of Technology, Coimbatore.Tamil Nadu -638401.
ABSTRACT
In this paper, a modified SAFER plus algorithm is presented. Additionally, a comparison
with various security algorithms like pipelined AES, Triple DES, Elliptic curve Diffie
Hellman and the existing SAFER plus are done. Performance of the algorithms is evaluated
based on the data throughput, frequency and security level. The results show that the
modified SAFER plus algorithm has enhanced security compared to the existing algorithms.
KEYWORDS
Secure And Fast Encryption Routine, Triple Data Encryption Standard, Pipelined Advanced
Encryption Standard, Elliptic Curve Diffie Hellmann, Pseudo Hadamard Transform,
Encryption and Decryption.
Full Text: http://airccse.org/journal/jwmn/1109s6.pdf
Volume Link: http://airccse.org/journal/j3current.html

17. REFERENCES
[1] Paraskevas kitos, Nicolas sklavos, Kyriakos Papadomanolakis and Odysseas Koufopavlou
university of patras, Greece,” Hardware Implementation of Bluetooth Security” IEEE CS and
IEEE Communications Society - January to March 2003. pp. 21 to 29.
[2] Karen Scarfone John Padgette, “Guide to Bluetooth security “National Institute of
standards and technology Special Publication 800-121, U.S. Department of Commerce 43
pages.
[3] Vainio, Juha T. “Bluetooth Security,” Helsinki University of Technology, 25 May 2000
[4 ] Gyongsu Lee, ”Bluetooth Security Implementation based on Software Oriented
Hardware-Software Partition” IEEE journal 2005. pp. 2070-2074.
[5] Kardach, James, “Bluetooth Architecture Overview,” Intel Technology Journal, 2000
[6] Jyrki Oraskari, "Bluetooth versus wlan ieee 802.11x", Helsinki university of technology,
october, 2001.
[7] A. Laurie and B.Laurie. serious flaws in blue tooth security lead to disclosure of personal
data. http://bluestumbler.com.
[8] Brent A.Miller And Chatschik Bisdikian “Bluetooth revealed” – low price edition
[9] Wikipedia.org, “Bluetooth,” Wikipedia.org, 5 March 2005,
http://en.wikipedia.org/wiki/Bluetooth (21 February 2005)
[10] Vrije Universiteit Brussel, “Bluetooth security” phd thesis December 2004
[11] Keijo M.J. Haataja Licentiate Thesis January 2007 University of Kuopio
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19. IMPLEMENTATION OF APPLICATION FOR HUGE DATA FILE
TRANSFER
Taner Arsan, Fatih Günay and Elif Kaya
Department of Computer Engineering, Kadir Has University, Istanbul, Turkey
ABSTRACT
Nowadays big data transfers make people’s life difficult. During the big data transfer, people
waste so much time. Big data pool grows everyday by sharing data. People prefer to keep
their backups at the cloud systems rather than their computers. Furthermore considering the
safety of cloud systems, people prefer to keep their data at the cloud systems instead of their
computers. When backups getting too much size, their data transfer becomes nearly
impossible. It is obligated to transfer data with various algorithms for moving data from one
place to another. These algorithms constituted for transferring data faster and safer. In this
Project, an application has been developed to transfer of the huge files. Test results show its
efficiency and success.
KEYWORDS
Network Protocols, Resource Management in Networks, Internet and Web Applications,
Network Based Applications.
Full Text: http://airccse.org/journal/jwmn/6414ijwmn03.pdf
Volume Link: http://airccse.org/journal/jwmn_current14.html

20. REFERENCES
[1] Information Storage and Management Storing, Managing, and Protecting Digital
Information Edited by G. Somasundaram Alok Shrivastava, EMC Education Services, 27-29.
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21. COMPARING VARIOUS CHANNEL ESTIMATION TECHNIQUES
FOR OFDM SYSTEMS USING MATLAB
Raghad K. Mohammed
Department of Basic Sciences, College of Dentistry University of Baghdad, Baghdad, Iraq
ABSTRACT
This paper compares the performance of various channel estimation techniques for OFDM
systems over quasi-static channels using MATLab. It compares the performance of five
channel estimation techniques, these are: decision directed (DD), linear interpolation, second-
order interpolation, discrete Fourier transform (DFT) interpolation, minimum mean square
error (MMSE) interpolation. The performance is evaluated in terms of two widely-used
performance measures, namely, bit-error rate (BER) and the mean square error (MSE) for
different levels of signal-to-noise ratio (SNR). The OFDM model is explained and
implemented using MATLab to run different simulations. The simulation results demonstrate
that the DD channel estimation provides the lowest BER and MSE as compared to
interpolation techniques, at the cost of extra processing delay and comparatively sensitive to
channel variations between OFDM symbols. Also, the MMSE interpolation outperforms all
other interpolation techniques.
KEYWORDS
OFDM, pilot-based channel estimation, pilot allocation, direct decision, interpolation channel
estimation, LS, MMSE, MATLab
Full Text: https://aircconline.com/ijwmn/V11N3/11319ijwmn02.pdf
Volume Link: http://airccse.org/journal/jwmn_current19.html

22. REFERENCES
[1] Henrik Schulze and Christian Luders. Theory and Applications of OFDM and CDMA:
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[3] Mathuranathan Viswanathan. Digital Modulations using MATLab: Build Simulation
Models from Scratch. E-book, June, 2017.
[4] Srishtansh Pathak and Himanshu Sharma. Channel Estimation in OFDM Systems.
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[7] Christopher Cox. An Introduction to LTE: LTE, LTE-Advanced, SAE and 4G Mobile
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[8] Mehdi Alasti, Behnam Neekzad, Jie Hui, and Rath Vannithamby. Quality of Service in
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24. RIVERBED-BASED NETWORK MODELING FOR MULTI-BEAM
CONCURRENT TRANSMISSIONS
Ji Qi1, Xin Li1, Shivam Garg2, Fei Hu1, Sunil Kumar2
1Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa,
AL
2Department of Electrical and Computer Engineering, San Diego State University, San
Diego, CA
ABSTRACT
The paper presents a Riverbed simulator implementation with both routing and medium
access control (MAC) protocols for mobile ad-hoc network wireless networks with multi-
beam smart antennas (MBSAs). As one of the latest promising antenna techniques, MBSAs
can achieve concurrent transmissions / receptions in multiple directions/beams. Thus it can
significantly improve the network throughput. However, so far there is still no accurate
network simulator that can measure the MBSA-based routing/MAC protocol performance. In
this paper, we describe the simulation models with the implementation of MBSA antenna
model in physical layer, MAC layer, and routing layer protocols, all in Riverbed Modeler.
We will compare two routing scenarios, i.e., multi-hop diamond routing scenario and multi-
path pipe routing. We will analyze the network performance for those two scenarios and
illustrate the advantages of using MBSAs in wireless networks.
KEYWORDS
Multi-beam Smart Antennas (MBSAs), Medium Access Control (MAC), Multi-path routing,
Riverbed Modeler.
Full Text: https://aircconline.com/ijwmn/V9N6/9617ijwmn01.pdf
Volume Link: http://airccse.org/journal/jwmn_current17.html

25. REFERENCES
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27. VIRTUAL ARCHITECTURE AND ENERGYEFFICIENT ROUTING
PROTOCOLS FOR 3D WIRELESS SENSOR NETWORKS
Vianney Kengne Tchendji1, Jean Frédéric Myoupo2, Pauline Laure Fotso3 and Ulrich
Kenfack Zeukeng1
1Department of Mathematics and Computer Science, University of Dschang, Cameroon
2Lab-MIS, University of Picardie Jules Verne, 33 rue St Leu, 80039, Amiens, France
3Department of Computer Science, University of Yaounde 1, Cameroon
ABSTRACT
This paper proposes a virtual architecture for three-dimensional (3D) wireless sensor
networks (WSNs), a dynamic coordinate system, and a scalable energy-efficient training
protocol for collections of nodes deployed in the space that are initially anonymous,
asynchronous, and unaware of their initial location. The 3D WSNs considered comprise
massively deployed tiny energy-constrained commodity sensors and one or more sink nodes
that provide an interface to the outside world. The proposed architecture is a generalization of
a two-dimensional virtual architecture previously proposed in the literature, in which a
flexible and intuitive coordinate system is imposed onto the deployment area and the
anonymous nodes are partitioned into clusters where data can be gathered from the
environment and synthesized under local control. The architecture solves the hidden sensors
problem that occurs because of irregularities in rugged deployment areas or environments
containing buildings by training the network of nodes arbitrarily dispersed in the 3D space. In
addition, we derive two simple and energy-efficient routing protocols, respectively for dense
and sparse networks, based on the proposed dynamic coordinate system. They are used to
minimize the power expended in collecting and routing data to the sink node, thus increasing
the lifetime of the network.
KEYWORDS
Wireless Sensor Network, Self-organization, Training protocol, Energy-efficient Routing
Protocol.
Full Text: https://aircconline.com/ijwmn/V9N5/9517ijwmn07.pdf
Volume Link: http://airccse.org/journal/jwmn_current17.html

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