Underground Environment Aware MIMO Design Using Transmit and Receive Beamforming in Internet of Underground Things

In underground (UG) multiple-input and multiple-output (MIMO), the transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagates to reach at the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes three path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three path interference channel and degrees of freedom (multiplexing gain of this MIMO channel requires careful modeling). Therefore, expressions are required derived the degrees of freedom of the UG MIMO interference channel. The underground receiver needs to perfectly cancel the interference from the three different components of the EM-waves propagating in the soil medium. This concept is based upon reducing the interference the undesired components to minimum at UG receiver using the receive beamforming. In this paper, underground environment aware MIMO using transmit and receive beamforming has been developed. The optimal transmit beamforming and receive combin- ing vectors under minimal inter-component interference constraint are derived. It is shown that UG MIMO performs best when all three component of the wireless UG channel are leveraged for beamforming. The environment aware UG MIMO technique leads to three-fold performance improvements and paves the wave for design and development of next generation sensor-guided irrigation systems in the field of digital agriculture

Current Advances in Internet of Underground Things

The latest developments in Internet of Underground Things are covered in this chapter. First, the IOUT Architecture is discussed followed by the explanation of the challenges being faced in this paradigm. Moreover, a comprehensive coverage of the different IOUT components is presented that includes communications, sensing, and system integration with the cloud. An in-depth coverage of the applications of the IOUT in various disciplines is also surveyed. These applications include areas such as decision agriculture, pipeline monitoring, border control, and oil wells

Underground Phased Arrays and Beamforming Applications

This chapter presents a framework for adaptive beamforming in underground communication. The wireless propagation is thoroughly analyzed to develop a model using the soil moisture as an input parameter to provide feedback mechanism while enhancing the system performance. The working of array element in the soil is analyzed. Moreover, the effect of soil texture and soil moisture on the resonant frequency and return loss is studied in detail. The wave refraction from the soil–air interface highly degrades the performance of the system. Furthermore, to beam steering is done to achieve high gain for lateral component improving the UG communication. The angle enhancing the lateral wave depends upon dielectric properties and usually ranges from 0∘ to 16∘. These dielectric properties change with the change in soil moisture and soil texture. It is shown from the experiments that optimal UG lateral angle is high at lower soil moisture readings and decreases with decrease in soil moisture. A planar structure of antenna array and different techniques for optimization are proposed for enhanced soil moisture adaptive beamforming. UG channel impulse response is studied from the beamforming aspect to identify the components of EM waves propagating through the soil. An optimum steering method for beamforming is presented which adapts to the changing values of soil moisture. Finally, the limitations of UG beamforming are presented along with the motivation to use it

Soil Moisture and Permittivity Estimation

The soil moisture and permittivity estimation is vital for the success of the variable rate approaches in the field of the decision agriculture. In this chapter, the development of a novel permittivity estimation and soil moisture sensing approach is presented. The empirical setup and experimental methodology for the power delay measurements used in model are introduced. Moreover, the performance analysis is explained that includes the model validation and error analysis. The transfer functions are reported as well for soil moisture and permittivity estimation. Furthermore, the potential applications of the developed approach in different disciplines are also examined

Wireless Underground Channel Modeling

A comprehensive treatment of wireless underground channel modeling is presented in this chapter. The impacts of the soil on bandwidth and path loss are analyzed. A mechanism for the UG channel sounding and multipath characteristics analysis is discussed. Moreover, novel time-domain impulse response model for WUC is reviewed with the explanation of model parameters and statistics. Furthermore, different types of the through-the-soil wireless communications are surveyed. Finally, the chapter concludes with discussion of the UG wireless statistical model and path loss model for through-the-soil wireless communications in decision agriculture. The model presented in this chapter is also validated with empirical data

Signals in the Soil: Underground Antennas

Antenna is a major design component of Internet of Underground Things (IOUT) communication system. The use of antenna, in IOUT, differs from traditional communication in that it is buried in the soil. Therefore, one of the main challenges, in IOUT applications, is to establish a reliable communication. To that end, there is a need of designing an underground-specific antenna. Three major factors that can impact the performance of a buried antenna are: (1) effect of high soil permittivity changes the wavelength of EM waves, (2) variations in soil moisture with time affecting the permittivity of the soil, and (3) difference in how EM waves propagate during aboveground (AG) and underground (UG) communications. For the third challenge above, it is to be noted that lateral waves are dominant component in EM during UG2UG communication and suffer lowest attenuation as compared to other, direct and reflected, components. Therefore, antennas used for over-the-air (OTA) communication will not be suitable for UG communication because of impedance mismatch. This chapter focuses on developing a theoretical model for understanding the impact of soil on antenna by conducting experiments in different soil types (silty clay loam, sandy, and silt loam soil) and indoor testbed. The purpose of the model is to predict UG antenna resonance for designing efficient communication system for IOUT. Based on the model a wideband planar antenna is designed considering soil dispersion and soil–air interface reflection effect which improves the communication range five times from the antennas designed only for the wavelength change in soil. Furthermore, it also focuses on developing an impedance model to study the effect of changing wavelength in underground communication. It is also discussed how soil–air interface and soil properties effect the return loss of dipole antenna

Signals in the Soil: An Introduction to Wireless Underground Communications

In this chapter, wireless underground (UG) communications are introduced. A detailed overview of WUC is given. A comprehensive review of research challenges in WUC is presented. The evolution of underground wireless is also discussed. Moreover, different component of UG communications is wireless. The WUC system architecture is explained with a detailed discussion of the anatomy of an underground mote. The examples of UG wireless communication systems are explored. Furthermore, the differences of UG wireless and over-the-air wireless are debated. Different types of wireless underground channel (e.g., In-Soil, Soil-to-Air, and Air-to-Soil) are reported as well

Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

Increased Mortality in Metal-on-Metal versus Non-Metal-on-Metal Primary Total Hip Arthroplasty at 10 Years and Longer Follow-Up: A Systematic Review and Meta-Analysis

Analysis and Stochastic