Jaffer M M* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 097 - 099
PROBABILITY ANALYSIS OF DETECTION RANGE OF WIRELESS ADHOC SENSOR NETWORK FOR RAYLEIGH FADING Jaffer M M
Ms.M.Anitha
Electronics and Communication Department Sir M Visvesvaraya Institute of Technology Bangalore, India jaffer.me@gmail.com
Keywords-component: Ad-Hoc network, Detection range, Rayleigh fading, Racian fading, Lognormal shadowing, Standard deviation.
I.
INTRODUCTION
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Target/event detection is one of the compelling applications of wireless sensor networks. Detection is of interest for habitat monitoring, security, surveillance and other defense applications. The goal of such an application is to determine whether a target/event is present or absent within the sensing field. There are two fundamental metrics of interest for such applications, the probability of missing an event and the probability of a false alarm. The goal is to keep these two metrics within pre-determined thresholds. The enhanced sensing range from cooperation comes at the cost of increased energy consumption from exchanging collaborative messages. Cooperative decision fusion and data fusion algorithms have been studied in [1, 2]. In the most efficient deterministic deployment which places the sensors on equilateral triangular grids, nearly 20% of the sensing region of each sensor is covered by other sensors [3]. Thus, the disk coverage model requires high sensor density while a large portion of the field is covered with high redundancy. Although the virtual sensor approach uses a smaller number of physical sensors to cover the area, it increases the energy consumption of these sensors for transmitting information for cooperative decision/data fusion. The coverage problem in sensor network has been
ISSN: 2230-7818
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studied under both the disk model and exposure model [4, 5]. They typically consider the coverage region of noncooperative sensors, i.e., only use exposure to the nearest sensor to characterize the coverage quality. The exposure with multiple sensors is studied in [6], where the minimal and maximal exposure path is considered. In [7, 8], Wang et al. introduce the information coverage concept and derive the cooperative sensing coverage for parameter estimation applications. By extensive literature survey we can make the conclusion that the reference paper [9] has done the analysis of the detection range for deterministic channel but there is a lack of analysis of detection range for fading medium which is more practical fading scenario than present one. In the present project work effect of Rayleigh fading, Racian fading and lognormal shadowing on detection range is analyzed and discussed. The remainder of the paper is organized as follows. In Section 2, the preliminary assumptions and model are provided. Analytical evaluation of mean communication range is presented in Section 3. Section 4 describes the numerical and simulation results. The paper is concluded in Section 5.
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Abstract—Detection range is one of important parameter of wireless Ad-Hoc networks which will judge the performance of wireless communication system. In order to make 100 percent efficient communication system, we must need to analyze the impact of fading medium on detection range. In present project work we are analyzing the impact of Lognormal, Rayleigh and Racian fading medium on detection range. We are also investing the effect of standard deviation of lognormal shadowing on detection range. We also present the simulation result with the help of MATLAB simulation tool. Complete numerical and simulated result will help to design more practical wireless AdHoc network
Telecommunication Communication Department Sir M Visvesvaraya Institute of Technology Bangalore, India anitha_m_padela@yahoo.com
II.
SYSTEM MODEL
We assume that there are N distributed sensors
si S
which are monitoring the sensing area, where S is the set of all sensors. We also assume that sensors know their own locations. Each sensor collects its sensor reading xi , i = 1. .
i
Assume there is a single target, which at any given time is either present or absent according to some distribution at a random location in the network. Depending on the hypothesis of whether the target is present or not , the sensor readings are given by . N.
Where is the received signal amplitude when target is present and is the background noise. We assume that the
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Jaffer M M* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 097 - 099
background noise is zero mean Gaussian with variance of . We also assume that the noise at different sensors, are independent to each other. III.
(13)
ANALYSIS OF DETECTION RANGE
3.1 Analysis of Detection Range of Lognormal Shadow Fading Channel
Where
(14)
For
(15)
From equation (13), (14) and (15) we can write
For Lognormal shadow fading we can write
(16) (3)
3.3 Analysis of Detection Range of Racian Fading Channel We have PDF of SNR given by [main]
Were
(17)
From equation (3) we can write (4) is given by
Were (5)
Let Threshold Probability be
and
Probability
at
is given by
(18)
On further simplification of equation (18) we can get
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is Average SNR at distance d probability that SNR (γ)
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So missing probability
Were
From equation (6) we can write
For
(7)
Let
(19) (20)
Let
(21)
From equation (19), (20) and (21) we can write
(8)
Let
=Z
(22)
(9)
4. NUMERICAL AND SIMULATION RESULT
(10)
The numerical and simulation results are obtained from the analytical model using MATLAB. The system parameters are selected as follows: K=10dB, Ptx =1mWatt, W=0.01mWatt,
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Hence from equation (8) we can write
Hence
3.2 Analysis of Detection Range of Rayleigh Fading Channel We have PDF of SNR given by [9]
=10dB. The parameters such as m, , , and are selected suitably. We choose a random number of nodes according to Poisson process and the nodes are placed over the simulation area according to a random uniform distribution.
(11)
Probability that SNR at d≤
is given by
(12) On further simplification we can write equation (12) as
ISSN: 2230-7818
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Jaffer M M* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 1, 097 - 099
project work can be extended to Nakagami Fading model which will give more practical scenario of fading medium. This project work can be even extended to MIMO, as well as diversity scheme to enhance the performance while overcoming the fading effect.
80 70 ptx =.1 ptx =.3 ptx=.5
DETECTION RANGE d
60
50 40
REFERENCES
30
20 10 2
2.5
3 3.5 4 ATTENUATION CONSTANT ALPHA
4.5
5
Figure 1 Rayleigh Fading
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250
rayleigh ptx = .1 rayleigh ptx = .3 racian ptx = .1 racian ptx = .3
100
50
2
2.5
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DETECTION RANGE d
200
150
3 3.5 4 ATTENUATION CONSTANT ALPHA
4.5
5
Figure 2 Comparisons of Rayleigh and Rician Fadings
5. CONCLUSION
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This project work studied several analysis of Detection Range for any wireless sensor node present in different fading scenario. This project work also analyzed the impact of several fading parameters on Detection Range to give a more practical result for any wireless node comprising detection range. This project work also has verified mathematical model with simulation tool using Mat-lab. The complete theoretical as well as simulative result give the insight of more practical wireless communication model which will help for future research work. The concerned
ISSN: 2230-7818
[1] R. Brooks, P. Ramanathan, and A. Sayeed, “Distributed target classification and tracking in sensor networks,” Proceedings of IEEE, vol. 91, no. 8, pp. 1163–1171, 2003. [2] F. Zhao, J. Liu, J. Liu, L. Guibas, and J. Reich, “Collaborative signal and information processing: An information directed approach,” Proceedings of the IEEE, vol. 91, no. 8. [3] R. Williams, “The Geometrical Foundation of Natural Structure: A Source Book of Design.” Dover Publications, 1979. [4] S. Meguerdichian, F. Koushanfar, M. Potkonjak, and M.Srivastava, “Coverage problems in wireless ad-hoc sensor network,” in Proceedings of IEEE INFOCOM, 2001. [5] D.Tian and N.D.Georganas, “A coverage-preserving node scheduling scheme for large wireless sensor networks,” in Proceedings of ACM WSNA, 2002. [6] G. Veltri, Q. Huang, G. Qu, and M. Potkonjak, “Minimal and maximal exposure path algorithms for wireless embedded sensor networks,” in Proceedings of ACM Sensys, 2003. [7] B. Wang, W. Wang, V. Srinivasan, and K. C. Chua, “Information coverage and its applications in sensor networks,” IEEE Communications Letters, vol. 9, no. 11, pp. 967–969, 2005. [8] B. Wang, K. C. Chua, V. Srinivasan, and W. Wang, “Scheduling sensor activity for point information coverage in wireless sensor networks,” in Proceedings of WiOpt, 2006. [9] A.V. Babu and Mukesh Kumar Singh, “Node isolation probability of wireless adhoc networks in Nakagami fading channel,” International journal of Computer Networks & Communications,Vol 2,March 2010
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