Research India Publications
International Journal of Applied Engineering
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(IJAER)
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Zaki Ahmad, Department of Mechanical Engineering, KFUPM,Box # 1748, Dhaharan 31261 Saudi Arabia
Area of research/interest: Advanced Materials, Corrosion and Corrosion protection
of materials, Surface Engineering.
Rajeev Ahuja, Physics Department,Uppsala University,Box 530, 751 21 Uppsala Sweden
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Shigeru Aoki, Department of Mechancial Engineering, Tokyo Metropolitan College of
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Osama Badr, Mechanical Engineering Department, Qatar University, P.O. Box 2713, Doha,Qatar
Sayavur I. Bakhtiyarov, New Mexico Institute of Mining and Technology, MechanicalEngineering Department, 122 Weir Hall, 801 Leroy Place, Socorro, NM 878014796, USA
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Fatma AbouChadi, Head of the Dept. of Electronics and Communications Engineering,Faculty of Engineering, Mansoura University, Egypt
ChingYao Chen, Dept. of Mechanical Engineering, National Yunlin University of Science & Technology,University Road, Touliu, Yunlin, Taiwan, 640 R.O.C.
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G.Q. Chen, Department of Mechanics and Engineering science, Peking University,Beijing 100871,China CFD(Computational fluid dynamics),energy and resources engineering,
and systems ecology.
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Engineering Kwame Nkrumah University of Science and Technology (KNUST) University,
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Dimitris Drikakis, Head of Aerospace Sciences Department, Cranfield University, School of Engineering, Cranfield, Befordshire, MK43 0AL, United Kingdom
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M.R. Eslami, Department of Mechanical Engineering, Amirkabir University of Technology,
Hafez Ave. Tehran, 15914 Iran
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A.S. AlHarthy, Department of Civil, Surveying and Environmental Engineering, University
of Newcastle, Callaghan, NSW 2308 Australia.
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F. Hayati, Dean, Faculty of engineering, Ajman university of Science & Technology
Network, Ajman, UAE
Annette BussmannHolder, MaxPlanckInstitute for Solid State Research, Heisenbergstr. 1, D70569 Stuttgart, Germany
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Naser S. AlHuniti, Mechanical Engineering Department, University of Jordan, Amman 11942, JORDAN
M.A.K. Jaradat, Department of Mechanical Engineering, Jordan
University of Science &Technology, Irbid 22110, Jordan
S.Z. Kassab, Mechanical Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, 21544 Egypt,
Area of Interest : Experimental Fluid Mechanics,Lubrication, Energy, Environment and Pollution.
M.Y. Khalil, Nuclear Engineering Department, Faculty of Engineering, Alexandria University,
Alexandria 21544 Egypt
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Bashar ElKhasawneh, Chairman, Industrial Engineering Department, JUST, P.O. Box 3030, Irbid 22110 Jordan
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Y.A. Khulief, Department of Mechanical Engineering, KFUPM Box 1767, Dhahran, 31261, KSA
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Kazuhiko Kudo, Laboratory of MicroEnergy Systems, Division of Human Mechanical Systems and Design, Graduate School of Engineering, Hokkaido University, Japan
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A. A. Mohamad, Director of Graduate Studies, Dept. of Mechanical and Manufacturing Engineering,
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A. A. Mowlavi, Physics Department, School of Sciences,Tarbiat Moallem University of Sabzever;P.O. box 397,Sabzevar, Iran.
Area of research/interest: Nuclear and Medical Physics.
Ihab Obaidat, Department of Physics, UAE University, PO Box 17551, AlAin, UAE
Area of research/interest: semiconductor band engineering and semiconductor interfaces.
H.M. Omar, Department of Aerospace Engineering, KFUPM, P.O. Box # 1794, Dhahran, 31261 Saudi Arabia
Industrial and Applied Control, Active Vibration Control, Intelligent
Control
and casting simulations, structural shape optimization, artificial intelligence techniques.
Huihe QIU, Department of Mechanical Engineering,The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon Hong Kong
Area of research/Interest: Transport phenomena in microscale multiphase flows,mciro sensors and actuators, optical diagnostics and instrumentation.
K. R. Rajagopal, Forsyth Chair Professor, Department of Mechanical Engineering,Texas A&M University, 3123 TAMU, College Station TX 778433123, U.S.A
D. Ramkrishna, Associate Head School of Chemical Engineering, Purdue University,
IN 479072100 USA transfer, Computational Fluid Dynamics modeling of combustion,
Design of combustion and heat transfer systems.
Ismail Shahin, Electrical and Computer Engineering Department, University
of Sharjah, P. O. Box 27272, Sharjah, United Arab Emirates
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Ashraf Shikdar, Department of Mechanical & Industrial Engineering, S.Q. University,P.O Box 33, AlKhod 123 Oman
Area of research/Interest: Ergonomics/ Human Factors, Worker performance, Occupational Health and Safety.
S.A. Soliman, Electrical Engineering Department, University of Qatar,
P. O. Box 2713 Doha Qatar
Area of research/Interest: Applications of State Estimation to Electric Power Systems, Fuzzy and Neural System Applications to Electric Power
Systems, Reactive Power Control.
Jinho Song, Thermalhydraulics and Reactor Safety Research Division,
Korea Atomic Energy Research Institute, P.O. Box, 105, Yusong, Taejon ,
305600, Korea
Area of research/Interest: Multiphase fluid mechanics and heat transfer, nuclear reactor safety,
and power plant operation and design.
H.H. ElTamaly, Chairman of electrical engineering Dept.,Faculty of Engineering, Elminia University, Egypt.
Area of research/Interest: Electrical power engineering, Photovoltaic
systems, wind energy systems, power electronics.
Bassam A. AbuNabah, Department of Aerospace Engineering and
Engineering Mechanics, College of Engineering, The University of Cincinnati, USA
Area of interest: Applied Mechanics, NonDestructive Testing Techniques, Residual Stresses.
B.M. Vaglieco, Istituto Motori, via G.Marconi, 880125 NaplesItaly
Area of research/Interest: Combustion process and pollutant formation in internal combustion engines and combustion diagnostics by optical techniques
Dimitri V. Val, Dept. of Structural Engineering and Const. Manag., Faculty of
Civil and Environmental Engineering, Technion Israel Institute of Technology,
Haifa 32000, Israel
Area of research/Interest: structural safety and reliability; analysis, design, and assessment of reinforced concrete and steel structures; probabilistic risk assessment and management.
GuoXiang Wang, Department of Mechanical Engineering, The University of Akron,
AkronOH 443253903 USA
Area of research/Interest: Heat and Mass Transfer, Materials Processing,Solidification Theory and Application.
Huimin Xie, Dept. of Engineering Mechanics, Tsinghua University, 100084 Beijing, China
Area of research/Interest: Experimental Mechanics, optical metrology.
Mohamed Younes, Mechanical Engineering Department, Faculty of Engineering, UAE University, P.O. Box 17555, AlAin, UAE
Area of research/Interest: Internal Combustion Engines Fuels, Internal Combustion Engines Cooling, CFD Simulation of Internal Combustion Engines.
Ahmed Sahin, Professor of Mechanical Engineering King Fahd University of Petroleum and Minerals Dhahran 31261, Saudi Arabia
Samir Medik, Associate Professor Mechanical Engineering Department King
Fahd University of Petroleum and Minerals PO Box 155, Dhahran, 31261, Saudi Arabia Meamer El Nakla, Mechanical Engineering Department King Fahd University of Petroleum and Minerals P.O. Box 323, Dhahran 31261, KSA
Adel Taha Mohamed Abbas, Associate Professor of Computer Aided Design & Manufacturing Mechanical Engineering Department, College of Engineering King Saud University Riyadh, Saudi Arabia, 11421,
Abdul Razak Rehmat, Associate Prof. Department of Polymer Engineering , Universiti Teknologi Malaysia ,Skudai, Johor, Malaysia
Prof. Abdullah M. AlShaalan, EE department College of Engineering
P.O. Box 800 King Saud University Riyadh11421 Kingdom of Saudi Arabia
Mir Iqbal Faheem , Professor & Head Dept. of Civil Engineering Deccan College of Engineering & Technology Darussalam, Near Nampally Hyderabad (AP)500001 India
M. Venkata Ramana , Microscopy and Nano Tech Laboratory Dept. of Metallurgical
and Materials Engineering Indian Institute of Technology Madras Chennai 600 036, India
Srinivas ManthaDean School of Engineering & Technology and Professor ECE Department, Centurion University of Technology and Management,
R. Sitapur, Uppalada, Paralakhemundi, Gajapati Dist, Orissa. 761 211 India.
Damodar Maity, Civil Engineering Department Indian Institute of Technology Associate Professor, Civil Engineering Department Indian Institute of Technology, Kharagpur, West Bengal, India 721302. West Bengal Kharagpur 721302 India Area of research/Interest:Damage Assessment of Structures; Seismic Resistant
of Structures; FluidStructure Interaction; Sloshing; Concrete Gravity Dam.
Sellakkutti Rajendran, School of Mechanical and Aerospace Engineering, Nanyang
Technological University Nanyang Avenue, Singapore
Area of Interest: Finite Element Method, Meshless Method, FEMeshree Methods,Mechanical Vibrations
Giriprasath Gururajan, Bartlesville Technology Center,ConocoPhillips Company Oklahoma, Bartlesville, USA.
Area of Interest: Polymer, Vibrational Spectroscopy, Electrospinning, Polymer characterization.
Marcos University Drive, San marcos, TX 78666, USA.
Mohammad Luqman, Chemical Engineering Department King Saud University
Chemical Engineering Department, Riyadh, Saudi Arabia
Area of Interest: Polymer Nanocomposites ,Polymer/Plastic, Ionomers,
Nanocomposites, Blends, Water Treatment, Plasticizers, Additives, Electroactive Materials, Smart Materials, Fuel Cell, Lithium Ion Battery, Sensors, Actuators, Artificial Muscles, Membranes, Conducting Polymer, Biocompatible,Drug Delivery.
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Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
Area of Interest: Sustainable Development, Soils, Foundations, Geomaterials,
Ground Improvement, Engineering Education, Leadership, Higher Education
Dr. P. Rathish Kumar, Civil Engineering Department, National Institute of Technology (NIT) Warangal506 004, Andhra Pradesh, India
Area of Interest: Alternate/New Building Materials, Recycling of concrete, Self
Compacting Concrete, Structural Dynamics, Earthquake Engineering, Structural Health Monitoring, Ferrocement and Fibrous Concretes.
Mohammad Valipour, Department of Irrigation and Drainage Engineering, College of Abureyhan, University of Tehran, Pakdasht, Tehran, Iran1675755936
Area of Interest: Surface and pressurized irrigation, Drainage engineering,
Relationship between energy and environment Agricultural water management, Mathematical and computer modeling and optimization Water resources, Hydrology, Hydrogeology, Hydrometeorology, Hydro informatics, Hydrodynamic Hydraulic, Fluid mechanics, Heat transfer in soil media of the Deparment, Manakula Vinayagar Institute of Technology, Kalitheerthalkuppam, Madagadipet, Puducherry, India
Area of Interest: Neural Networks, Image Processing, Artificial Intelligence, Data
Mining & Data Warehousing, Computer Networks
Dr. Kishorereddy, Associate Prof. Electrical Engineering, Adama Science & Technology University, Narayanapuram (v&p), Sathupally (MD), Khammam (DT), Andhra Pradesh, India
Area of Interest: electronics and communication, vlsi design, signal processing
Dr. Najm Obaid Salim Alghazali, Department of Civil Engineering, Babylon University, Hilla, Babylon, Iraq
Area of Interest: Hydraulic Structures, Hydraulics, Engineering Hydrology,
Groundwater Hydrology, Dams Engineering (Concrete, Earth, etc.), Water Resources Statistics, Dimensional Analysis, Hydraulics Modeling, Seepage under Hydraulic Structures, Water Storage Tanks, Simulation and Modeling, Irrigation, Optimization, General Water Resources Engineering, Numerical Methods and Finite Elements in Civil Engineering.
Dr. Shrikant Tiwari, Department of Computer Science & Engineering, Faculty of Engineering & Technology (FET), Shri Shankaracharya Technical Campus, Block No. 15/B, Street No. 29, Sector07, Bhilai Nagar, City: Bhilai, District: Durg, Chattisgrah, India
Area of Interest: Biometrics, Image Processing, Computer Vision, Computer
Graphics, Pattern Recognition
Thanjavur, Tamil Nadu, India
Area of Interest: Data Mining,VLSI Physical Design,Computer Networks, Embedded systems.
Sushant K. Singh, Doctoral Assistant, Earth and Environmental Studies Department, Montclair State University, New Jersey, USA, 1 Normal Avenue, Montclair State University , 358N ML, Montclair, 07043, New Jersey, USA
Area of Interest: Environmental pollution, Environmental management, Environmental toxicology, Environmental decisionmaking, Environmental policy, Waste management, and Sustainability Science.
Dr Umashankar S, School of Electrical Engineering, VIT University, Vellore, Tamilnadu, India
Area of Interest: Power electronics applications in wind and solar energy, electrical drives and control, smart grid and power quality
R. Manikandan, ICT Department, School of Computing,SASTRA Universtiy, Thanjavur, Tamil Nadu, India
Area of Interest: Data Mining,VLSI Physical Design,Computer Networks, Embedded systems
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International Journal of Applied Engineering
Research (IJAER)
Volume 9, Number 23 (2014)
C
ONTENTS
CBACCN: Constraint Based Community discovery Complex Networks pp. 1811518127
Soumita Seth , Debnath Bhattacharyya, Taihoon Kim
Association Itemsets Discovery Considering Strategic Importance: WAARM pp. 1812918139
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Analysis of the current state in order to maintain the function of the communication buildings for maintaining function in emergency
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Comparison of Ultrasonographic Architectural Properties of Muscles and Balance Ability Based on the Spasticity of Chronic Stroke Patients
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Algorithm for Reduction of System Order using Fast Rationalized Haar Transforms in Time Domain
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Simplification of High Order Transfer Function using General Block Pulse Functions andTransforms in Frequency Domain
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JoonHoon Park,RyumDuckOh
The Effect of Theme Based STEAM Activity Programs on Self Efficacy,Scientific Attitude, and Interest in Scientific Learning
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YoungTae Kong, SunChen Huh, HuiJu Hwang
The Implementation of STEAM Program about Pollution in Senior High School pp. 1824718254
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Structural Analysis of Class Satisfaction by Internet Protocol TV pp. 1825518261
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Acoustic Echo Cancellation Techniques for FarEnd Telephony Speech Recognition in BargeIn Situations
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Calvin Jeongheon Lee,Hye Jin Kum,Hyoungtaek Lim,Frank Biocca
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Modified Firefly Algorithm For Selective Harmonic Elimination In Single Phase Matrix Converter
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Anisha. K, Rathina Kumar.K
Cooperative Diversity Pathsselection Protocol WithmultiObjective Criterion In Wireless AdHoc Networks
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Implementation of a Sensor Web Service for Environmental Pollution Monitoring using Wireless Sensor Networks –A Test Bed Approach
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International Journal of Applied Engineering Research
ISSN 0973-4562 Volume 9, Number 23 (2014) pp. 22395-22407
© Research India Publications
http://www.ripublication.com
Cooperative Diversity Pathsselection Protocol
Withmulti-Objective Criterion In Wireless Ad-Hoc Networks
1
Nyoman Gunantara,
1Nyoman Putra Sastra,
2Gamantyo Hendrantoro
1
Department of Electrical Engineering
Universitas Udayana, Bali
2Department of Electrical Engineering
Institut Teknologi Sepuluh Nopember, Surabaya
Abstract
Relay selection plays a very important role in wireless ad hoc networks.
Wepropose a cooperative diversity protocol as simple and easy to understand
with multi-objective cross-layer criterion by considering the condition of
source-to-destination (S-D) linkand employing amplify-and-forward (AF)
relays. The proposed protocol guarantees full diversity based on scalarization
of the two-objective criterion with root mean square (rms) normalizationto
gain fairness. The two objectivesinclude signal-to-noise power ratio (SNR)
and load variance. Simulation results show that the proposed protocol
giveshigher SNR than a single-objective protocol that does not consider the
S-D link conditions. The proposed protocol results in an improvement of 3.03
dB in SNR and is likely to result in cooperative diversity configuration
involving two parallel relays. In addition, the load variance achieved by
applying the proposed algorithmindicates more evenly distributed traffic load.
Keywords:
relay selection, algorithm protocol, full diversity, amplify and
forward, multi-objective criterio, rms, scalarization, SNR, load variance.
Introduction
22396
Nyoman Gunantara
multi-input multi-output (MIMO) [2] systems. Consequently, cooperative diversity can
improve the transmission quality.
To implement cooperative diversity in wireless ad-hoc networks, it needs protocol
and criteria that must be met in communication from source to destination. For
example, the authors in [3] propose a simple protocol of cooperative diversity for
configuration consisting of source-to-destination and source-relay-destination paths.
With this protocol, problems arise when the signal from the source to destination can
not be received well due to bad quality of the radio link so that the direct transmission
fails. In this case, full diversity can not be achieved and the cooperative system
performance degrades. This problem can be mitigated by checking the performance of
the source-to-destination link prior to the cooperative diversity phase, so that the
system can be enhanced to achieve full diversity, which is explored in our paper.
Relay or path selection in cooperative diversity can be done depending on various
criteria. For instance, path selection in cooperative diversity can be done based on SNR
[4] - [7], outage probability [8] - [10], mutual information [11], and symbol error rate
[12]. However, these papersimplement cooperative diversity using single-objective
criterion. It is thought thatpath selection in cooperative diversity needs to consider a
combination of multiple criteria to achieve multiple goals simultaneously. Our paper
proposes a cooperative diversity protocol with cross-layer multi-objective criterion
involving prediction of the performance from the source to the destination in advance
so that the right decision on the configuration taken can be made and full diversity can
be achieved. Multi-objective criterion used areSNRand load variance. The first are
related to the physical layer, while the second is a network layer problem [13].
Path selection in multi-objective can be achieved by using Pareto and scalarization
methods. Based on the computation time, scalarization method takes less time to
perform simulation compared with Pareto method[14]. Therefore, the completion of a
multi-objective criterion in the protocol of cooperative diversity in this research
appliesscalarization method. In thescalarization method, each objective is weighted
and normalized. Normalization with priorityscale tends to separatethe primary objects
and ignore other objects[15]. In this paper, normalization is made to the root mean
square (rms) to provide fairness among theobjectives.
As previously stated, the best path pair in our study is obtained based on a criterion
consisting of twoobjectives, namely SNRand load variance. SNR values obtained with
proposed algorithm is found to provide improvement of 3.03 dB over the
single-objective protocol proposed in [3]. Our algorithm also guarantees full diversity of the
proposed protocol.
Section II of this paper describes the formulation of the three-objective problem.
Section III describes model of the ad-hoc network and protocols used in our study.
Section IV describes theparameters and simulation results and closed with conclusions
in SectionV.
Formulation of Multi-Objective Criterion
Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al.
22397
two criteria and scalarization for the combinationis explained below. There are five
possible outcomes of path selection, namely D only, R-D only, D and R-D,
S-R1-D and S-R2-D, and no connection. The possibilities of path selection results can be
seen in Fig. 1.
SNR
If transmission rate is desired, channel capacity of 2 is required for packets sent by
S to be successfully received in D. The requirement can be expressed as follows [16]:
2
≤
(1 +
,)
(1)
Equation (1) can also be written as follows:
,
> 2
−
1
(2)
Figure 1: Possibilities of Path Selection Results
If this condition is not fulfilled then the direct path of S-D is deemed not eligible,
or
,
< 2
−
1
(3)
The success of communication with S-D and S-R-D configuration with AF relay
channel capacity is determined by the value of the spectral efficiency
. Channel
capacity of the AF method can be calculated by the following equation:
22398
Nyoman Gunantara
=
log 1 +
,+
,=
log 1 +
,+
, ,
, ,
Based on equation (4), the channel capacity can reach the optimal value if the
value
,is also optimal. It can be concluded that to reach a value
,, it requiresthe
selected relay to provide the optimal value. The best relay is given by the optimal
value . Mathematically, it can be written as [3]:
∗
=
arg max
, ,, ,
(5)
where the sign *denotes the optimal value.
Load Variance
Load variance isthe variance of traffic loads of all nodes, which isinversely
proportional to the load balance or fairness [17].In ad-hoc wireless networks, load
balance is very important because some nodes may have a greater chance to become a
relay. In a path pair where node is used as a relay thenthe traffic load of node
becomes:
=
+
(6)
where
and
arethe own traffic load of and the traffic cominginto node ,
respectively.
After the load of each node is known then the load variance caused by the selection
of a pair ofdiversity pathscan be reviewed for all nodes in the path pair. The load
variance value can be determined by following equation [17]
=
1
−
1
(7)
Scalarization
Inscalarization method, all criteria are combined into a scalar form by givinga weight
to each objective. Minimizedfunction is given a negative sign, while the maximized
function is given a positive sign. In this research,every objectiveis normalized to their
own rms value to gain fairness.
Scalarization of the above twoobjectivesbecomes:
=
(
)
−
(8)
Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al.
22399
So, theoptimalrelaycan be calculatedby the following equation:
= arg max
(9)
System Model and Protocol
In this study, each node can act as a source (S), relay (R), and destination (D).
Properties of the system model are:
•
Each node uses a single antenna with omni-directional radiation.
•
AF relaysare used in cooperative communication.
•
The packet delivery is half-duplex.
•
Transmission isdivided into direct transmission phase and one or more phases
of cooperative transmission.
•
Source and relayshave equal transmit power
P
.
•
Distance power law is used for the path loss model with influence of
lognormal shadowing [14].
•
Thenoise is AWGN with
variance.
We assume that in this protocol each node alternately broadcasts information on
the received powersfrom other nodes and traffic load so that everyone knowsthe
received powers of each other in the form of a table. Communication protocol is
startedby the source broadcasting initiation packets. Decisions on the quality of S-D is
determined by equation (2),whereas the best relay selection is done through equation
(5). The protocol is the result of one of three possibilities, namely diversity, no
diversity, and no connection. The cooperative diversity protocol can be explained by
the flowchart in Fig. 2.
Pseudocodefor the flow chart can be divided into three parts: the mainprogram, the
one dual-hop procedure, and the two dual-hop procedure. Starting withthe packet
broadcast by S,the S-D performance is checked. If
,> 2
−
1
,then the one
dual-hopprocedure isexecuted. Otherwise, if
,< 2
−
1
then the two dual-hop procedure
is selected. This process can be seen in AlgorithmI.
If the decision is made that the S-D link quality is good, i.e.,
,> 2
−
1
, the route
of direct transmission and cooperative is formedthroug
1 = [ , ]
and
Algorithm I: Main program
Begin
S transmit
If
,> 2
−
1
Then
Procedure one dual-hop
Else If
,< 2
−
1
Then
Procedure two dual-hop
End
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Nyoman Gunantara
( , : ) = [ , , ]
for
= 1: ,
≠
,
≠
. After that, relay selection is done
based on multi-objective criterion in equation (10). The result is either diversity
through
ℎ
_
or no diversity through
1
. This process can be seen in
Algorithm II.
If the decision is made thatthe S-D quality is not sufficiently good, i.e.,
,<
2
−
1
, then the cooperative route is formed through
( , : ) = [ , , ]
for
= 1: ,
≠
,
≠
. After that,the second relay selection is done based on
multi-objective criterion in equation (10). The result can be diversity through
ℎ
_
, or
no diversity through
_
1, or no connection. This process can be seen in
Algorithm III.
Algorithm II: Procedure one dual-hop
Begin
//decision by
,> 2
−
1
//direct route
route1=[S,D]
//cooperative route
For i=1:N, i
≠
S, i
≠
D
route(i,:)=[S,I,D];
End
//multi-objective criterion
=
, ,,
+
,+ 1
=
1
−
1
//scalarization of multi-objective criterion
= arg max
⎛
(
)
−
⎠
//best 1 relay
If best1relay =1 Then
diversity
Else no_diversity
End
End
//diversity
[y,I]=sort(relay,’descend’)
selected_relay=relay(I(1),:)
path_pairs={[SD] selected_relay1}
//no diversity
Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al. 22401
Algorithm III: Procedure two dual-hop
Begin
//decision by
,< 2
−
1
//cooperative route
Fori=1:N, i
≠
S, i
≠
D
route(i,:)=[S,i,D];
End
//multi-objective criterion
=
, ,,
+
,+ 1
=
1
−
1
//scalarization of multi-objective criterion
= arg max
⎛
(
)
−
⎠
//best 2 relays
If best2relays = 2 Then
diversity
Else If best2relay=1 Then
no_diversity
Else
no_connection
End
End
End
//diversity
[y,I]=sort(relay,’descend’)
selected_relay1=relay(I(1),:)
selected_ relay2=relay(I(2),:)
path_pairs={selected_relay1selected_relay2}
//no diversity
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Numerical Results
Simulation parameters are adopted from the application of WLAN in ad-hoc wireless
networks as shown in Table I. The ad-hoc network model used consists of one source,
one destination, and multiple other nodes that are possible relays. All nodes are in an
open space with an area of 100m
×
100m. S broadcasts a data packet to D assisted by
other nodes. In this study, 30 nodes are defined each having the same opportunity tobe
a relay.
To simulate load variance calculation, it is assumed that besides the source sending
data to the destination there are five other nodes simultaneously transmit data to
theirrespectivedestinations. As a result, there are some nodes having a better chance to
be a relay because they have relatively lower traffic load. In our example, five pairs of
source and destination nodes use paths 4-12-31, 7-11-25, 10-19-23, 16-12-2, and
25-20-6. It is assumed that the sources, namely, node 4, 7, 10, 16, and 25 transmit data
respectively at 3, 8, 7, 2, and 11Mbps. While the other nodes are assumed to have
random load of 2, 7, 12, or 17.
*)
: Power receivedby Dfrom S is calculated by D and then fed
back to S
**)
: Computed by each possible relay R and further checked by
S.
***) : Computed from (9).
ߛ
௦,is calculated by each R and
checked by S, while
ߛ
,ௗis calculated by D and checked by
each R.
Figure 2:
Flow Chart of Cooperative Diversity Protocol
Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al. 22403
The optimal relay pair selected in this simulation are (1-19-32) and (1-21-32) with
SNR of 29.47 dB obtained using the proposed protocol was. The SNR obtained from
the single-objective protocolas in the paper [3], which does not consider the condition
of SD,is 27.53 dB, whereas the SNR for S-R-D configuration only is 25.03dB, and that
for S-D only is 13.27dB.Whereasthe load variance is 48.36 Mbps
2.The selectedpath
pair can be seen in Fig. 4.
Table 1: Parameters of Simulation
Parameter
: Value
Path loss exponent ,
∝
: 4
Standard
deviation
of
shadowing,
Figure 3: Ad Hoc Network Model
Simulationis performed 1000 times with a random position and load to every node
to determine the distribution of each objective and compareit to the single-objective
algorithm, the direct transmission (S-D) and the dual-hop (S-R-D).
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Nyoman Gunantara
Fig. 5. From Fig. 5, it can be explained that the SNR value from the proposed method
(marked "MO" in the figure) ranges from 21.01 to 47.05 dB.For comparison, the SNR
for the single objective protocol not considering to the S-D condition (marked "SO")
ranges from 18.09 to 40 dB.The median difference of SNR between the
proposedmulti-objective and the single-objective algorithm is 3.03 dB.For the S-R-D
path onlyconfiguration, the SNR ranges from10 to 34.01 dB.While for S-D path only,
the SNR ranges from-10 to 23.06 dB with the probability of SNR value above 0 dB
being 88.0 %.These results suggest that the proposed protocol produces the largest
SNR values among the others.
Figure 4:
Best Path Pairs
The CDF of load variance from the simulation is given in Fig. 6. The load variance
from the use of the proposed protocol ranges from39.23 to 51.17 Mbps
2. As a
comparison, load variancesare also shown for the single-objective protocol and for the
S-D path only configuration. Load variance produced by the single-objective
rangesbetween 38.52and 51.74 Mbps
2. While the value of load variance for the case
of S-D path only is fixeddue to the absence of changes in the traffic load on each
node. Fig. 6 shows the value of load variance with the proposed protocol issmaller
than that with the single-objective. It is because the traffic load resulting from the
proposed protocol is more evenlydistributed with the application of multi-objective
criterion than the traffic load of the nodes with a single objective protocol.
Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al.
22405
Figure 5: CDF of SNR
Figure 6: CDF of Load Variance
Conclusions
Based on the analysis of simulation results of the proposed cooperative diversity
protocol, several conclusions can be drawn. Firstly, the selection of the best path pair
can be done based on a multi-objective cross-layercriterion. In our case, there are two
objectives involved, namely, SNRand load variance by applying multi-objective
optimization with scalarization. Secondly, the SNR with the proposed algorithm that
considers the condition of the direct S-D link is higher than that resulting from the
single-objective algorithm that does not consider the condition of S-D. In this case,
SNR improvement of 3.03 dB is obtained. Lastly, load variance that results from the
proposed protocol is smaller than that resulting from the single objective protocol.
-20 -10 0 10 20 30 40 50 60
Load Variance (Mbps2)