13) Abdul Salam
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This document discusses using diversity reception with multiple antennas to improve underground wireless communication. It proposes a lateral-direct-reflected (LDR) approach using three antennas to separately receive the lateral, direct, and reflected signal components. Software-defined radio experiments show maximum ratio combining (MRC) of the three signals can increase SNR by 3 times compared to a single antenna, reducing bit error rate from 10^-2 to 10^-5. The contributions include exploiting the spatial modularity of underground channels with multiple antennas and analyzing performance improvements from diversity reception techniques.
![IOUT Introduction
2
[1] I.F. Ayildiz, and E.P. Stuntebeck, "Wireless Underground Sensor Networks: Research Challenges," Ad Hoc Networks Journal (Elsevier), vol. 4, no. 6, pp. 669-686,
November 2006
[2] Z. Sun and I.F. Akyildiz. “Channel modeling and analysis for wireless networks in underground mines and road tunnels,” IEEE Transactions on
Communications, vol. 58, no. 6, pp. 1758–1768, June 2010.
[3] X. Dong, M. C. Vuran, and S. Irmak. “Autonomous Precision Agricultrue Through Integration of Wireless Underground Sensor Networks with Center Pivot
Irrigation Systems”. Ad Hoc Networks, 11(7):1975-1987, 2013.
[4] I. F. Akyildiz, Z. Sun, and M. C. Vuran, “Signal propagation techniques for wireless underground communication networks,” Physical Communication Journal
(Elsevier), vol. 2, no. 3, pp. 167–183, Sept. 2009.](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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13) Abdul Salam
- 1. Diversity Reception with Multiple Antennas in Underground Communications Abdul Salam Advisor: Dr. Mehmet C. Vuran
- 2. IOUT Introduction 2 [1] I.F. Ayildiz, and E.P. Stuntebeck, "Wireless Underground Sensor Networks: Research Challenges," Ad Hoc Networks Journal (Elsevier), vol. 4, no. 6, pp. 669-686, November 2006 [2] Z. Sun and I.F. Akyildiz. “Channel modeling and analysis for wireless networks in underground mines and road tunnels,” IEEE Transactions on Communications, vol. 58, no. 6, pp. 1758–1768, June 2010. [3] X. Dong, M. C. Vuran, and S. Irmak. “Autonomous Precision Agricultrue Through Integration of Wireless Underground Sensor Networks with Center Pivot Irrigation Systems”. Ad Hoc Networks, 11(7):1975-1987, 2013. [4] I. F. Akyildiz, Z. Sun, and M. C. Vuran, “Signal propagation techniques for wireless underground communication networks,” Physical Communication Journal (Elsevier), vol. 2, no. 3, pp. 167–183, Sept. 2009.
- 3. IOUT Applications 3 [1] I. F. Akyildiz and E. P. Stuntebeck, “Wireless underground sensor networks: research challenges,” Ad Hoc Networks (Elsevier), vol. 4, pp. 669–686, July 2006 [5] A. Salam, M.C. Vuran, and S. Irmak, “Towards IOUT in smart lighting: A statistical model of wireless underground channel,” to appear in Proc. 14th IEEE International Conference on Networking, Sensing and Control (IEEE ICNSC), Calabria, Italy, May 2017.
- 4. Challenges 0 50 100 150 200 Distance (m) -100 -80 -60 -40 PathLoss(dB) AG2UG UG2AG UG2UG 4 [6] M.C. Vuran, A. Salam, R. Wong, and S. Irmak, “Internet of Underground Things: Sensing and Communications on the Field for Precision Agriculture,” to appear in Proc. IEEE 4th World Forum on Internet of Things (WF-IOT), Singapore, Feb 2018.
- 5. 5 Signal at sender Signal at receiver LOS Path Multipaths 1. Delay Spread 2. Inter-Symbol Interference (ISI) Signal at sender Signal at receiver LOS Path Multipaths Multipaths are Bad in OTA Wireless OTA Channel
- 6. Multipaths are more Harmful in UG Wireless Eye diagram of a QPSK Signal with Severe ISI [9] A. Salam, M.C. Vuran, and S. Irmak, ``Pulses in the Soil: Impulse Response Analysis of Wireless Underground Channel,’’ in Proc. IEEE INFOCOM ‘16, San Francisco, CA, Apr. 2016. Caused by delay spread of the UG channel [9]
- 7. Lateral Wave Direct Wave Reflected Wave Transmitter Receiver SOIL AIR • Due to different speed of wave propagation in air and soil these components do not interfere with each other • Spatial modularity can be exploited with multiple antennas through diversity reception A. Salam, M.C. Vuran, and S. Irmak, ``Pulses in the Soil: Impulse Response Analysis of Wireless Underground Channel,’’ in Proc. IEEE INFOCOM ‘16, San Francisco, CA, Apr. 2016. Not Bad in UG Wireless … with Diversity Reception
- 8. Lateral-Direct-Reflected (LDR) – A SIMO Approach8 • Wireless Underground Channel Diversity Reception With Multiple Antennas • Omni-directional antenna at the transmitter • Three antennas at receiver; one each for lateral, direct and reflected component Lateral Wave Direct Wave Reflected Wave Transmitter L-Wave Antenna SOIL AIR R-Wave Antenna D-Wave Antenna
- 9. Optimum Maximum Ratio Combining (MRC-LDR) Three times SNR enhancement as compared to the SNR of a single antenna matched filter UG receiver 9 Lateral Wave Reflected Wave Direct Wave MRC
- 10. Adaptive Combining (AC-LDR) AC-LDR exploits this by adaptively switching and selecting the strongest L, or D-Wave: 10 L-Wave Antenna
- 11. BER Experiments - Software-defined Radio Testbed • GNU Radio and Ettus N210 USRPs • Dipole antennas buried at 20 cm depth at a distance of 50 cm in Silty clay loam soil • Transmitter-Receiver (TR) are synchronized by using a MIMO cable • Transmit power:10 dBm • The operation frequency range: 100MHz to 300MHz
- 12. Performance Comparison 12 MRC-LDR performs better as compared to AC-LDR and 3W- Rake At 25 dB, BER decreased from 10^-2 to 10^-5
- 13. Summary of the Contributions • Spatial modularity with multiple antennas • Lateral-Direct-Reflected (LDR) approach • Software-defined radio based field experiments • Performance analysis of different modulation schemes through simulations and experiments • BER under equalization, and diversity reception • 3 times increase in SNR • Improvement in BER from 10-1 to 10-5 13
Editor's Notes
- Most recently, the need for real-time in-situ information from agricultural fields have given rise to a new type of IoTs: Internet of underground Things (IOUT). IOUT represents autonomous devices that collect any relevant information about the Earth and are interconnected with communication and networking solutions that facilitate sending the information out of fields to the growers and decision mechanisms. IOUT provides seamless access of information collected from agricultural fields through the Internet. IOUT will not only include in-situ soil sensing capabilities (soil moisture, temperature, salinity, etc.), but will also provide the ability to communicate through plants and soil, and can provide real-time information about the environment (wind, rain, solar). When interconnected with existing machinery on the field (seeders, irrigation systems, combines), IOUT will enable complete autonomy on the field and pave the way for more efficient food production solutions. In, IOUTs nodes are buried underground, and these nodes can communicate with both underground and above ground nodes. These are many emerging applications of the IOUT. These are being used in precision agriculture, landslide detection, border control, pipeline monitoring.
- In, Wireless underground sensor networks nodes are buried underground, and these nodes can communicate with both underground and above ground nodes. These are many emerging applications of the wireless underground sensor networks. These are being used in precision agriculture, landslide detection, border control, pipeline monitoring.
- Multipath are bad in over the air channel. Causes delay spread as signal is dispersed over time. Multipaths also lead to inter-symbol interference. Dispersed signal can cause interference between with neghbour symbols leading to Inter Symbol Interference (ISI)
- MRC-LDR achieves the maximum gain Interference from the reflected components is still present Next, adaptive switching and selection to suppresses undesired interference
- Based on the proximity of the LDR receiver, either the D-wave or L-Wave component is dominant at the receiver. R-Wave is not considered because it is the weakest component and results in performance degradation
- Software defined radio for BER experiments