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					    International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
       Web Site: www.ijettcs.org Email: editor@ijettcs.org, editorijettcs@gmail.com
Volume 2, Issue 3, May – June 2013                                             ISSN 2278-6856




    Energy Conservation in Multiwireless Network
          System Using Genetic Algorithm
                                            Harjeet Kaur, Amandeep Kaur *
                      Research fellow, Department of Computer Science and Engineering, Sri Guru Granth
                                    Sahib World University, Fatehgarh Sahib, Punjab, INDIA

                         Assistant Professor, Department of Computer Science and Engineering, Sri Guru
                                Granth Sahib World University, Fatehgarh Sahib, Punjab, INDIA *

                                                                  one hundred gigahertz. This paper will give a brief
Abstract: The wireless communication antenna plays an             introduction to antenna principles and then discusses
important role both at transmitter and receiver. For design       various antenna types and their applications. Generally
considerations antenna parameters are designed depending          the antenna array consists of large number of radiating
upon range of propagation, input power to the transmitting        elements or sub-arrays. Due to large number of elements
antenna, and effective aperture of both transmitting and          presented in an array, there is always a possibility of
receiving. Antenna Array is formed by assembly of radiating       failure of one or more elements in the antenna array
elements in an electrical or geometrical configuration. In
                                                                  system. The failures of elements in the array destroy the
most cases the elements are identical. The antenna array is
one of the most important components to improve the system
                                                                  symmetry and may cause sharp variation in field intensity
capacity and spectral efficiency. The active antenna array is     across the array, distort the pattern in the form of
widely used in many applications like satellite                   increased sidelobe level. It is possible in case of active
communication, sonar, mobile communication etc. for signal        antennas to restore the radiation pattern with minimal
acquisition purpose. Failure of one or more elements in an        loss of quality without replacing the defective element by
antenna array degrades the radiation patterns. If the failed      controlling the excitations of the normal antenna
elements are detected properly then no corrective measure         elements of the array.
can be adopted. Detection of the failed elements is often a       1.1. Antenna. An antenna is a transducer between a
difficult process, particularly in large arrays especially when   guided wave and a radiated wave, or vice versa. The
the array is not physically accessible. In this paper, an         structure that "guides" the energy to the antenna is most
efficient method for detecting faulty element(s) in an antenna
                                                                  evident as a coaxial cable attached to the antenna. The
array, based on Genetic Algorithm (GA), is proposed. This
                                                                  radiated energy is characterized by the antenna's radiation
method uses a constrained optimal synthesis procedure to
regenerate the degraded radiation patterns.                       pattern.
Keywords— Genetic Algorithm, antenna array, radiation             1.2. Antenna pattern. The radiation pattern or antenna
pattern.                                                          pattern is the graphical representation of the radiation
                                                                  properties of the antenna as a function of space. That is,
                                                                  the antenna's pattern describes how the antenna radiates
1. INTRODUCTION                                                   energy out into space (or how it receives energy). It is
Antennas are a very important component of                        important to state that an antenna radiates energy in all
communication systems; improve the system capacity and            directions, at least to some extent, so the antenna pattern
spectral efficiency. The definition of an antenna                 is actually three-dimensional. It is common, however, to
according to IEEE standard 145-1983 is that it is a means         describe this 3D pattern with two planar patterns, called
for radiating and receiving the radio waves (or) in a broad       the principal plane patterns. These principal plane
way it is also defined as a transducer which converts             patterns can be obtained by making two slices through the
voltage and current on a transmission line into                   3D pattern through the maximum value of the pattern or
electromagnetic field in space. A receiving antenna               by direct measurement. It is these principal plane patterns
changes electromagnetic energy into electric or magnetic          that are commonly referred to as the antenna patterns.
energy. A transmitting antenna changes the energy from
electric or magnetic into electromagnetic energy. Current         1.3. Antenna performance measurement
flowing in the antenna induces the electric and magnetic
                                                                  To successfully design (or purchase) and then integrate an
fields. Antennas demonstrate a property known as
                                                                  antenna into a wireless device, a number of measurements
reciprocity, which means that an antenna will maintain
                                                                  must be made to quantify the antenna performance in the
the same characteristics regardless if it is transmitting or
                                                                  actual product.
receiving. Most antennas are resonant devices, which
operate efficiently over a relatively narrow frequency            1.4 Impedance and Antenna Bandwidth
band. Antennas have been used for over a century in a
variety of applications. They can transmit over a massive         As discussed above, antenna impedance is typically
range of frequencies, from a fraction of a kilohertz to over      measured as return loss or VSWR. The equipment used to

Volume 2, Issue 3 May – June 2013                                                                                 Page 414
   International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
       Web Site: www.ijettcs.org Email: editor@ijettcs.org, editorijettcs@gmail.com
Volume 2, Issue 3, May – June 2013                                             ISSN 2278-6856


measure this parameter is a Network Analyzer. The              2. RELATED WORK
impedance (and the bandwidth over which the impedance          Author              Year          Work done
is acceptable) must be measured with the antenna               Jung-Hoon     h     2012          Resynthesizing         the
installed in the device with all components installed. The     an,Sang-Ho Lim                    optimal beam pattern
impedance measurement often requires special fixtures          and    noh-Hoon                   from the distorted beam
and assemblies to allow access to the antenna terminals.       myung                             pattern      using      an
It is not uncommon that the antenna requires some small                                          adaptively       weighted
tuning adjustments when the device is finally fully                                              beam pattern mask
assembled.                                                                                       based on a genetic
1.5 Gain and Radiation Patterns                                                                  algorithm
                                                               Munish Rattan,      2012          The problem of antenna
Calibrated measurements of antenna gain and radiation          Manjeet Singh                     array failure has been
patterns are made in an Anechoic Chamber. The anechoic         Patterh, Narwant                  addressed using Firefly
environment eliminates all reflections and allows precise      S.Grewal                          Algorithm (FA) by
and repeatable measurements to be made. The device                                               controlling only the
under test is typically rotated 360 degrees in multiple                                          amplitude excitation of
orientations to determine the shape of the radiation                                             array elements
pattern from many different directions. Reference              Michal Vavrda       2011          It               describes
antennas are used as calibrated gain standards. As with                                          opportunities         and
impedance measurements, gain and radiation patterns                                              constraints            for
should be measured using a complete product.                                                     application        digital
                                                                                                 beamforming
1.6 Efficiency Measurements
                                                                                                 techniques and adaptive
As mentioned earlier, efficiency may be the single most                                          beamforming
important parameter to be measured, especially for an                                            techniques in wireless
embedded antenna which can have degraded efficiency                                              communications
due to its tight integration with the device. Efficiency can   S Y KIM and N       2009          The method uses an
be calculated from the calibrated gain and radiation           H Myung                           optimal beam pattern
pattern measurement but this can be a time-consuming                                             mask to synthesize the
effort. Within the last 10 years, a new type of efficiency                                       desired beam pattern
measurement tool has become available – sometime                                                 was introduced
referred to as a “3D Chamber”. The most common                 Yang and Stark      2001          In this paper vector
manufacturer of this tool is Satimo. The 3D Chamber                                              projection method for
uses a circular array of test antennas and a rotating table                                      recovery of reasonable
to quickly measure the total energy generated by the                                             antenna      performance
antenna under test. The resulting total efficiency                                               was proposed for as
measurement is accurate, repeatable and can be used to                                           many as 30% of the
compare various antenna topologies quickly.                                                      elements are inoperable
                                                               Rodriguez     and   2000          In this paper they
1.7 Introduction to TRM Antenna
                                                               Ares                              applied a GA for
Digital beam forming array antenna systems are installed
                                                                                                 recovering the pattern
outdoors for long periods of time. When a
                                                                                                 by      changing       the
transmitter/receiver module (TRM) error occurs, the
                                                                                                 excitation of some of the
beam pattern is distorted. In this case, re synthesizing the
                                                                                                 array elements, this
optimal beam pattern with all functioning TRMs, without
                                                                                                 approach is simple and
failed TRM, is preferable to TRM repair or replacement.
                                                                                                 useful, a faster and more
Algorithms for re synthesizing the optimal beam pattern
                                                                                                 accurate method is
from the distorted beam pattern using an adaptively
                                                                                                 required for practical
weighted beam pattern mask based on a genetic algorithm
                                                                                                 applications
has been already proposed. The proposed algorithm
allows improved re synthesis flexibility and accuracy and
increased calculation speed. Several beam patterns are         3 PROPOSED WORK
also examined utilizing the proposed algorithm. The            In TRM Antenna transmission using MIMO system
proposed TRM failure compensation algorithm provides a         reducing bit error rate has been challenge from decade. In
cost-effective and less time-consuming solution for            addition to this, if any receiving antenna get damaged, it
repairing the digital beam forming antenna systems.            is difficult for the routing table to generate a routing set
                                                               which is feasible without damaged antenna. Our basic
                                                               problem is to generate

Volume 2, Issue 3 May – June 2013                                                                               Page 415
   International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
       Web Site: www.ijettcs.org Email: editor@ijettcs.org, editorijettcs@gmail.com
Volume 2, Issue 3, May – June 2013                                             ISSN 2278-6856


4. OBJECTIVES                                                multivariate problems. GA is simple and are not limited
    1.) To study compensation of antenna array TRM           by restrictive assumptions about the search space. There
         failure to resynthesis the beam pattern using       are three phases in a typical genetic algorithm
         evolutionary techniques.                            optimization. These phases are (1) initiation, (2)
    2.) To study to re-synthesis the beam pattern when       reproduction and (3) generation replacement. Figure 1
         antennas are non-uniformly spaced                   shows a typical GA cycle. It starts with initiation
    3.) To study the compensation of antenna array           consisting of filling an initial population with a
         failure when multiple TRM error occurs.             predetermined number of encoded and randomly created
    4.) To generate a MIMO system for multiple               chromosomes which represent an individual prototype
         antennas.                                           solution. The reproduction phase consists of three genetic
    5.) To study the static routing concept.                 operations namely (1) selection (2) crossover and (3)
    6.) To generate dynamic routing using GA.                mutation. Genetic algorithms produce high quality
    7.) To compare it with other routing protocols.          results. The ability of GAs to produce high quality results
    8.) To conserve energy for multiple antennas using       lies in the fact that they combine the exploitation of past
         dynamic routing.                                    good solutions with exploration of new areas of search
                                                             space. Genetic algorithms are different from other
                                                             optimization and search procedures in four ways:
5. Methodology:                                                   1. Genetic algorithms with a coding of the parameter
To solve out the problem which we would be
                                                                       set, not on parameter themselves.
implementing a virtual node concept which would be
                                                                  2. Genetic algorithms search from a population of
activated if any of the receiving antenna is highly heated
                                                                       points, not a single point.
up. This virtual node will receive signal instead of that
                                                                  3. Genetic algorithms use objective function
heated antenna until and unless the heated antenna get
                                                                       information, not derivatives or other auxiliary
cooled. a dynamic routing table using GA. Using
                                                                       knowledge.
evolutionary techniques and find the best algorithm to
                                                                  4. Genetic Algorithms use probabilistic transition
obtain the desired beam pattern. SUPERNEK 2
                                                                       rules, not deterministic rules.
&MATLAB can be used in this software.

6. MIMO OVERVIEW
  MIMO systems use multiple antennas at both
transmitter and receiver, so both transmit and receive
diversity are applied to mitigate fading resulting from
signal fluctuations through the wireless channel. Based
on the degree at which the multiple data replicas are
faded independently, the system provides diversity gains
representing the difference in SNR at the output of the
diversity combiner compared to that of single branch
diversity at certain probability level. A MIMO system
consisting of N transmit antenna elements equal to eight,    To create next generation, new chromosomes called
and of M receive antenna elements equal to two was           offspring, are formed by either merging two chromosomes
modeled, accordingly diversity order of 16 can be            from the parent generation using a crossover operator or
achieved. Combining the multiple versions of the signals     modifying a chromosomes using a mutation operator. A
created by different diversity schemes is needed for         new generation is formed by selection of parents and
improving the performance. The paper applies maximal         offspring, according to the fitness value and rejecting
ratio combining (MRC) technique using maximum-               unfit chromosomes to keep the population size constant.
likelihood (ML) decoder to combine these M received          The genetic operations mimic the process of heredity of
signals to resonate on the most likely transmitted signal.   genes to create new offspring at each generation. Fitter
The sum of the received SNRs form these M different          chromosomes have a higher probability of being selected.
paths is the effective received SNR of the system with       Selection may be roulette wheel selection or tournament
diversity M. The receiver needs to demodulate all M          selection or may be of other types. After several iterations,
receive signals in case of MRC for a source with M           the algorithm converges and gives optimal or near-
independent signals in the receive antennas.                 optimal solutions. There are basically two kinds of
                                                             operations in genetic operations:
7. Genetic Algorithm                                                        Genetic operations: Crossover and
Genetic algorithm (GA) was develop by John Holland in                          Mutation
University of Michigan in 1960s and 1970s. The Genetic                      Evolution operation: Selection.
algorithm is an evolutionary search algorithm in which
solve the optimal solutions to multimodal and
Volume 2, Issue 3 May – June 2013                                                                             Page 416
    International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
       Web Site: www.ijettcs.org Email: editor@ijettcs.org, editorijettcs@gmail.com
Volume 2, Issue 3, May – June 2013                                             ISSN 2278-6856


8.   PARAMETER                          CORRECTION               •   Y. Yang and H. Stark, “Design of self-healing arrays
ALGORITHM                                                            using vector space projections”,IEEE Trans.
                                                                     Antennas Propag., vol. 49, no. 4, pp. 526–534, Apr.
                                                                     2001.

                                                                 •    J. A. Rodríguez, F. Ares, E. Moreno, and G.
                                                                     Franceschetti, “Genetic algorithm procedure for
                                                                     linear array failure correction,” Electron. Lett., vol.
                                                                     36, no. 3, pp. 196–198, Feb. 2000

                                                                 •    T. J. Peters, “A conjugate gradient based algorithm
                                                                     to minimize the sidelobe level of planar arrays with
                                                                     element failures,” IEEE Trans. Antennas Propag.,
                                                                     vol. 39, no. 10, pp. 1497–1504, Oct. 1991.

                                                                 •   A. Sharmila and Srigitha S. Nath,(2012)
                                                                     “Performance of MIMO Multi-Carrier CDMA with
                                                                     BPSK Modulation in Rayleigh Channel”, ICCCE ,
9. RESULT & CONCLUSION                                               12 & 13 April, 2012.
The results indicate that GA provides a more efficient and
accurate alternative to direct search methods to detect
failed elements in a large antenna array. In every case
investigated, it is found that a direct search over the entire
search space would have required a number of iterations
which is about one order more than what we achieved. As
expected, the difference in number of iterations required
for exhaustive search and GA based search increases
drastically i.e. GA becomes more and more efficient, with
increase in the volume of the search space. Maximum
benefit of the technique can be obtained for real life
problems involving very large arrays, since the possible
number of combinations of failed elements would have
been extremely large in those cases. A direct computation
in such cases would have been extremely time and
computation resource consuming.
References
•   Jung-HoonHan,Sang-Ho Lim and Noh-Hoon
    Myung,” Array Antenna TRM Failure Compensation
    Using Adaptively Weighted Beam Pattern Mask
    Based on Genetic Algorithm”,IEEE ANTENNAS
    AND         WIRELESS           PROPAGATION
    LETTERS,VOL.11,2012.

•   Narwant S. Grewal,Munish Rattan,Manjeet S.
    Patterh,” A LINEAR ANTENNA ARRAY FAILURE
    CORRECTION USING FIREFLY ALGORITHM”,
    Progress in electromagnetic ResearchM,Vol.27.241-
    254,2012.

•   Michal VAVRDA,” Digital beamforming in wireless
    communications”,   Brno      University      of
    Technology,2011

•   S. Y. Kim and N. H. Myung, “An optimal antenna
    pattern synthesis for active phased array SAR based
    on particle swarm optimization and adaptive
    weighting factor, “ Prog.      Electromagn. Res. C”,
    vol. 10, pp.129–142, 2009.


Volume 2, Issue 3 May – June 2013                                                                                Page 417

				
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posted:7/26/2013
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