Gerardine Immaculate Mary2. Asst. Prof. (Sr.), School of Electronics Engineering. VIT University, Vellore, Pin: 632014, India. Abstract: Judicious deployment of ...
G.Pradeep Reddy et al. / International Journal of Engineering Science and Technology (IJEST)
OPTIMAL NODE PLACEMENT IN WIRELESS SENSOR NETWORKS G.Pradeep Reddy1 Asst. Professor, Lovely Honours School of Technology (ECE) Lovely Professional University, Jalandhar, Punjab, Pin: 144402, India.
Gerardine Immaculate Mary2 Asst. Prof. (Sr.), School of Electronics Engineering VIT Universit y, Vellore, Pin: 632014, India.
Abstract: Judicious deployment of fixed anchors (node with known positions) is to be considered in sensor networks which are used for monitoring and detecting a possible hazardous event in underground mines (such as fire, flammable, explosive, toxic gas); UWB is selected owing to its asset in ranging accuracy, preeminently in cluttered environments compared to other technology, and their ability to penetrate obstacles. It is therefore the signal of choice for many indoor ranging. This paper proposes a low complexity parameter to determine the optimal placement of sensor nodes, measurement results using ZigBeeTM specification are shown as proof of concept that precise channel profiles between different LOS and NLOS conditions can be identified with this combined strategy. Keywords: UWB channel profile identification; optimal sensor node placemen; IEEE 802.15.4a Channel Model. I.
Introduction
Sensor networks have been proposed for various applications due its ability for monitoring and detecting a possible hazardous event in underground mines such as fire, flammable, explosive, toxic gas; where judicious deployment of fixed anchors (node with known positions) is to be considered. In emergencies wireless communication may become vital for survival, for example, during a disaster such as a fire, rock falls, the conventional wired communication system may become unreliable, necessitating a wireless radio system. A wireless sensor network is composed of sensors which are deployed across a geographical area. Each sensor can be thought of as having two important modules. The first is the sensing module depending on the mission at hand (i.e., seismic, chemical, temperature, etc.). The second is the wireless communication module, which is used to communicate with the other sensors in ad-hoc fashion. One of the most promising applications for UWB is sensor networks, where a large number of sensor nodes communicate among each other, and with central nodes, with high reliability. The data rates for those applications are typically low (1Mbit/s), and the good ranging and geolocation capabilities of UWB are particularly useful. Recognizing these developments, the IEEE has established the standardization group 802.15.4a, which is currently in the process of developing a standard for these applications. Intuitively, to find the best receiver position in indoor environments where the sensors get the optimum signal to be detected, the following may be considered, either the position where best signal is received or average of all multipath signals received at a point or alternatively SNR may be used. Consider the following example; at two different receiver positions the received signal strength per unit measurement are as shown in the table1.
ISSN : 0975-5462
Vol. 3 No. 2 Feb 2011
1124
G.Pradeep Reddy et al. / International Journal of Engineering Science and Technology (IJEST)
Table1: Optimum receiver position using other measures like best signal strength and average value.
Position 1 50 25 35 30 10 Average = 50
Position 2 50 40 40 10 10 Average =50
If the best signal received is considered, best signals may be got at different positions of the receiver, and the better of the two cannot be identified. If average value of received signals is considered to find the best receiver position, the predicament is same, as shown in the table, where the average values of received signals at two receiver positions 1 and 2 are equal. If the SNR is considered to find the best receiver positions, the following are the limitations, first, it is difficult to estimate the SNR, secondly using only SNR of the received signal doesn’t account for the individual channel realizations. Thus the above methods will not give the optimised receiver position. The best receiver positions can be determined by using the kurtosis index. The kurtosis index captures both the statistics of individual channel realizations and SNR of the received signal. Thus receiver can be placed where the kurtosis index is maximum. In the above example, the two positions shown have different kurtosis indices, at position 1, κ =2.22 and at position 2, κ =1.27, so position 1 can be suggested as the best receiver position. The example can be extended to many such receiver positions and can be noted that in the case of considering only best signal strength or only best SNR measures, we may get many similar values to decide from, whereas using kurtosis index as the parameter, less number of similar values occur, making the decision of optimum receiver position easier. II.
Related Work Earlier, CDF (cumulative distribution function) was used to identify the indoor channels profiles, between LOS and NLOS. The CDF of the variable X is defined as the probability that X assumes any value smaller then x, i.e. P(X
