MITS5003 Wireless Communication: WSN Implementation for VicStock

This case study provides a comprehensive analysis of a Wireless Sensor Network (WSN) implementation for VicStock's MaffraStock farm in Gippsland. It begins by selecting the LoRaWAN frequency band (915-928 MHz) due to its unlicensed nature and proceeds to calculate the required channel capacity for both sensing devices to the control center and the control center to the ISP. The analysis includes calculating thermal and total noise levels, determining signal power received at the control center, and assessing the bandwidth requirements for both individual sensing devices and multiplexed channels using FDM. Furthermore, the study calculates the maximum free space loss and determines the required transmission signal strength, considering signal power losses due to attenuation and fading. The study concludes by suggesting functionalities for a cloud application to effectively utilize sensor data in the agriculture sector and proposes how IoT platforms can aid in WSN implementation, highlighting the potential for improved decision-making and efficiency in livestock management.

Wireless Communication
Name:
Professor:
Date:

a. Select a suitable frequency band for WSN and give reasons for your selection.
Answer:
The best frequency band selected for WSN is LoRaWAN frequency band (Australia
915-928 MHz). This is because this frequency is unlicensed radio spectrum. That means
we will not incur the cost of paying for the frequency band.
b. Calculate the channel capacity (minimum data rate) required for:
I. One sensing device to control center channel.
Answer:
Minimum bit rate=bandwidth∗log2 (1+ SNR )=13∗106∗log2 (1+19 )=56185065.23 bps
II. Control center to ISP channel.
Answer:
Minimum bit rate=n∗bandwidth∗log2 ( 1+ SNR )=2500∗13∗106∗log2 ( 1+19 )=1405 Gbps
c. c) For both the channel types calculate the following noise levels experienced:
I. Thermal noise.
Answer:
thermal noise= √ 4 RKfT = √ 4∗1.38∗10−23∗( 20+273 )∗13∗106∗8∗103 =41.01 μV
II. Total noise experienced
Answer:
total noise= 100
5 ∗41.01∗10−6 =82.03 μV
d. It is expected to maintain SNR of 63 at the control center for sensor signals.
i. Calculate the signal power received at control center from one sensing device.
Answer:

Prx =Ptx Gtx Grx ( c
4 πDf )2
=1∗10∗100∗
( 3∗108
4∗3.142∗1500∗13∗106 )2
=0.01499 watts
ii. Calculate the bandwidth of the sensing device to control center channel.
Answer:
Bandwidth=n*bandwidth of a single sensing device=2500*5=12500bps.
iii. What will be the bandwidth of the multiplexed channel if FDM scheme is used?
Answer:
bandwidth=2500∗13∗106=32.5 Ghz
e. Calculate the maximum free space loss experienced by the signals sent from sensors.
(Assume control Centre is located exactly at the center of the landscape)
Answer:
FSPL=20 log ( d ) +20 log ( f ) +20 log ( 4 π
c )−¿−Gr
¿ 20 log ( 1500 ) +20 log ( 13∗106 ) +20 log ( 4 π
3∗108 )−10−100=¿−51.76 dB ¿
f. Determine the required transmission signal strength if other impairments such as
attenuation and fading causes loss of 30% in signal power during the propagation from
sensors to the control Centre.
Answer:
transmission signal strength=output power +losses−antenna gain=¿63dBm+51.76dBm-
10.5dBm=104.26dBm
g. With your general knowledge in agriculture sector and business suggest functionalities
for the cloud application to effectively use sensor data.
Answer:

Weather and climate prediction from the temperature and humidity data collected.
Goods and services flow in business and also demand and supply distribution in the
economy.
h. Suggest how IoT platforms can help the implementation of WSN. (Research in google to
find answer for this)
Answer:
Sensors and actuators embedded in physical objects from roadways to pacemakers are
linked through wired and wireless networks, i.e using same IP protocal that connects the
internet. These will facilitate huge transmission of volumes of data flow for computer
analysis hence help in implementation of WSN.
References

[1] J. D. Boerman, J. T. Bernhard, "Performance study of pattern reconfigurable antennas in
MIMO communication systems", Transactions on Antennas and Propag, vol. 56, no. 1,
pp. 231-236, January 2008.
[2] L. Moustakas, H. U. Baranger, L. Balents, A. M. Sengupta, S. H. Simon, "Communication
through a diffusive medium coherence and capacity", science, vol. 287, no. 5451, pp.
287-290, January. 2010.
[3] B. Gershman, N. D. Sidiropolous, "Space-time Processing for MIMO Communications Eds."
in West Sussex, U. K. Wiley, 2015.
[4] C. Waldschmidt, T. Fugen, W. Wiesbeck, "Spiral and dipole antennas for indoor MIMO-
systems," IEEE Antennas Wireless Propag. Lett, vol. 1, no. 1, pp. 176-178, 2012.
[5] M. S. Sharawi, M. A. Jan, D. N. Alo, "Four-shaped 2×2 multi-standard compact Multiple-
Input-Multiple-Output antenna system for long term evolution mobile handsets", IET
Microw. Antennas Propel, vol. 6, pp. 685-696, 2012.
[6] T. C. Tang, K.H. Lin, "MIMO antenna design in thin film integrated passive device", IEEE
Trans on Components Packaging and Manufacturing Technology, vol. 4, no. 4, April
2014.
[7] R. Suga, H. Nakano, Y. Hirachi, J. Hirokawa, M. Ando, "Cost effective 60 GHz antenna
package with end-fire radiation for wireless file transfer system", IEEE Trans. Microw.
Theory Tech, vol. 58, no. 12, pp. 3989-3995, December 2010.
[8] Biglieri, E. (2010). MIMO wireless communications. Cambridge: Cambridge University
Press.