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Under-water wireless communication link has been a topic of higher interest due to an increase in various underwater operations. Such operations demand higher bandwidth with a fast velocity. This paper presents the experimental and FEM based simulations to investigate the radio waves based wireless link because of its higher magnitude in bandwidth and speed as compared to acoustic and optical technologies. Conduction current method is employed to transmit and receive the data in a conductive medium (Saltwater) with varying propagation heights. The investigations reveal that at the shallow water (less than the length of dipole, below sea level) produce significant surface waves (Airwaves) resulting in unidentified data reception. The height below sea level, more than the dipole length has resulted in the least BER as such it may be called an authentic data reception model.

In modern homes, energy consumption accounts for most of the economic aspects and environmental sustainability. Intelligent energy management and its control play an important role in energy supply and demand; and it will change behavior and environmental changes. For energy management and its control, a hybrid Internet of Things (IoT) and personal wireless network-based devices have been developed. In terms of the need-side-management approach, the use of energy can be intelligently controlled by the device for greater durability. In this study, electricity consumption and utilization are categorized accurately based on data collected from consumer behavior in energy consumption and utilization. First, the data cut through the device is used to identify and summarize the power consumption patterns hidden in the data. Second, the different linear mode algorithms extracted from the Schick-Lear Python library will be used for energy consumption and its intelligent power control. By analyzing different algorithms, the predictive score is found to be sufficiently efficient for the recurrence prediction, while the multi-step and lead-time technique proved to be suitable for multidimensional energy prediction. Results show that root squared mean error (RSME) performance of the predictive model increased by 35% in the lead time approach. Similarly, in per day approach it is 33% more efficient than the recursive model when residual energy forecasting is utilized.

Generating effective communication links in an offshore environment is a vital need for the oil and gas industry as well as the military domain. The highly conductive medium of the environment is yet the biggest hurdle to develop the channel. Focusing towards the challenges lies in underwater communication channel, this paper first presents an efficient transmitter and receiver design using the conduction current method. Subsequent to the design development, a comparative analysis is presented that can be used to model an optimum underwater communication channel through electromagnetic conduction. Effect of different channel characterization parameters is discussed such as conductivity, frequency and transmitter and receiver antenna separation. Through an efficient circuit design for transmitter and receiver, increasing frequencies increased the signal strength is proved. Further statistical analysis revealed that in the developed experimental setup, 100 kHz has a greater possibility in designing an efficient demodulation circuit design. The promising results have proved the possibilities in way forward for the technology.

Seabed Logging (SBL), a tool that uses Marine Controlled Source Electromagnetic (CSEM) method to specifically explorer and map conceivable hydrocarbon-bearing prospects. In spite of the fact that the CSEM technique has been utilized by the scholarly community forever three decades. The focal thought of SBL is the controlling of electromagnetic vitality in thin resistive layers inside conductive dregs. Regardless of whether it has been notable for quite a while that electromagnetic signs can engender from a conductive formation to another by means of resistive areas, for example, air or resistive parts of the lithosphere, the application to hydrocarbon investigation has not been created as of not long ago. This may be because of the vulnerability of getting any critical reaction from thin resistive layers, for example, hydrocarbon stores since electromagnetic vitality is profoundly lessened in conductive silt. In this way, amid the early improvement period of the SBL procedure, a scaled research experiment was performed to approve if a thin resistive layer (e.g. hydrocarbons) covered inside conductive media (e.g. dregs) could be remotely recognized by utilizing electric dipoles as sources and receivers. Information from this analysis were well contrasted with a forward modelling code. However, the analysis cant be applied in the stratified media with challenging sediments, oil and sea water is present. This research have presented the consequences of the main scaled SBL analysis by introducing the major contituents of the SBL surveys with respective forward modelling.

Controlled Source Electromagnetics (CSEM) is an innovative methodology in hydrocarbon exploration surveys that uses HED antenna to generate EM signals. The method enhances the decision-making process for drilling offshore oil fields while diminishing risk factors and uncertainties in the hydrocarbon mapping. Erroneous mapping may lead to losing huge resources due to false target drilling. To reduce such perils, enhancement of major peripherals involved in the method is crucial. Antennas being one of the most imperative components of CSEM, are subject to many challenges faced in the process of Seabed Logging (SBL) and yet have huge room for improvement. In this research, a mathematical expression is used to elect the right input levels that can be scaled to actual seabed environment. Based on the calculations, for the first time, a seabed environment is modeled in a lab scale tank containing sea water, over-burden layer, hydrocarbon reservoir and under-burden layer to study and enhance current limitations in the antenna system. The effect of increased transmitter surface area in this study reveals that the increment in area of electrodes by 66.67% is capable of increasing oil delineation by 103.11 %. Based on the outcomes, a prediction model is also generated for deriving the relation between the area of electrodes and oil delineation for the given scaled offshore environment.

The estimation of the noise power is a core issue in wireless communication systems. In broadcasting, every OFDM frame starts with a preamble symbol, which facilitates the noise power estimation. However, the performance of preamble-based noise estimation schemes worsens in fast-changing environments and cannot efficiently track the noise variation well. In order to track the noise variation symbol to symbol, pilot-based schemes would be more fruitful. Accordingly, in this paper, we propose a novel pilot-based noise power estimation scheme for OFDM systems that estimate the noise power for each data symbol. It makes use of the pilot subcarriers reserved for channel estimation in the data symbol. The proposed algorithm computes the circular correlation between received signal and comb type sub-pilot subsequence twice to generate the noise power. Compared with the conventional preamble-based scheme, the proposed pilot-based noise algorithm generates near-ideal accuracy at different values of signal-to-noise ratio (SNR). Without the additional overheads of the preamble, the scheme offers the significant saving of computation over a conventional time domain noise estimator.

In the presence of guard band sub-carriers, the existing correlation-based time-domain channel estimation schemes do not perform well and suffer from high computational complexity. Herein, we proposed an optimized time domain channel estimation scheme with high accuracy and low complexity. In proposed correlation error cancellation (CEC) solution, the larger part of actual channel estimation solution is estimated from no-guard band (without null sub-carriers) solution, which can be easily obtained by choosing appropriate pilot design. In order to estimate the complete actual solution, the correction term can be obtained from the difference in the actual transmitted pilot and the pilot used for no-guard-band solution. The theoretical analysis and simulation results show that the proposed CEC solution reduces the complexity up to 0(L2) in one-step of iteration and achieves accuracy close to Cramer Rao Bound (CRB).

Channel impairments degrade the performance of accurate data signal detection and decoding. The said problem becomes further severe in low SNR environment. As a result it reduces the performance of channel estimation. To alleviate this problem we develop a pilot based Pre FFT (time domain) channel estimation technique in the presence of Rayleigh fading channel. A novel time domain channel estimation technique is proposed that accurately measure the channel impulse response by using cross correlation between received signal and pilot carriers, especially at low SNR. In addition, the proposed technique enhances robustness in Orthogonal Frequency Division Multiplexing (OFDM) channel estimation by reducing Mean Square Error (MSE). Simulation results show that proposed method provides better accuracy in term of MSE over conventional techniques (LS and MMSE) that estimate the channel impulse response in frequency domain.