Positioning, coverage, and connectivity play important roles in next-generation wireless network applications. The coverage in a wireless sensor network (WSN) is a measure of how effectively a region of interest (ROI) is monitored and targets are detected by the sensor nodes. The random deployment of sensor nodes results in poor coverage in WSNs. Additionally, battery depletion at the sensor nodes creates coverage holes in the ROI and affects network coverage. To enhance the coverage, determining the optimal position of the sensor nodes in the ROI is essential. The objective of this study is to define the optimal locations of sensor nodes prior to their deployment in the given network terrain and to increase the coverage area using the proposed version of an enhanced particle swarm optimization (EPSO) algorithm for different frequency bands. The EPSO algorithm avoids the deployment of sensor nodes in close proximity to each other and ensures that every target is covered by at least one sensor node. It applies a probabilistic coverage model based on the Euclidean distances to detect the coverage holes in the initial deployment of sensor nodes and guarantees a higher coverage probability. Delaunay triangulation (DT) helps to enhance the coverage of a given network terrain in the presence of targets. The combination of EPSO and DT is applied to cover the holes and optimize the position of the remaining sensor nodes in the WSN. The fitness function of the EPSO algorithm yielded converged results with the average number of iterations of 78, 82, and 80 at 3.6 GHz, 26 GHz, and 38 GHz frequency bands, respectively. The results of the sensor deployment and coverage showed that the required coverage conditions were met with a communication radius of 4 m compared with 6–120 m with the existing works.

Optimal placement of sensor nodes is a challenging issue in localization applications because the Cramér-Rao lower bound (CRLB) of target nodes dependent on the sensor node geometry. Though there exists many localization algorithms and methods, localization using time of arrival (TOA) and time difference of arrival (TDOA) of wideband signals has potential features to support higher accuracy at lower complexity, these techniques become a promising choice for various applications including underwater communication, highly precise radar systems, and radio communication. However, multipath propagation (the combination of indirect path signals between target node and anchor nodes), lack of clock synchronization, computational complexity, high power consumption, interference, and noise pose major challenges that affect the localization accuracy. In this paper, a highly accurate and simplified versions of TOA, TDOA-based localization techniques are presented that suit the resource constraint applications of industrial internet of things (IIoT) and 6G communication systems. The proposed TOA, TDOA techniques are based on orthogonal frequency division multiplexing (OFDM) channel estimation that ensures reliable location estimations and is less susceptible to multipath effects. During TOA based location measurements, perfect synchronization is ensured between anchor nodes and target nodes. In case of TDOA based location measurements, though the target node is not synchronized with the anchor nodes still all the anchor nodes are synchronized. So, the synchronization error between the target node and all anchor nodes is the same. Therefore, the proposed TDOA measurements and the localization accuracy are independent of synchronization error. Simulations were conducted using fast Fourier transform (FFT) and MUSIC spectrum analysis methods at higher frequency bands under noisy environments and results are compared with the performance under ideal conditions. The results proved that both TOA and TDOA based localization values are very close to the corresponding ideal value conditions and immune to noisy environments. Overall, TDOA based localization outperforms TOA based localization technique.

Many of the techniques that are used in digital image and video processing were developed in the 1960s at Bell Laboratories. These techniques have applications in a variety of fields, including medical imaging, videophone, character recognition, satellite imagery, and wire-photo standards conversion. Additional applications include enhancement of photographs or vidoes. The early stages of image and video processing were developed with the intention of enhancing the overall quality of the image or video. For the purpose of enhancing the visual effect of humans, it is intended for human beings. When it comes to image and video processing, the input is an image of poor quality, and the output is an image and video of higher quality. Research on algorithms and applications of digital image and video processing is the primary purpose of this study, which aims to investigate these topics extensively. The methodology employed in this study is qualitative research technique. In accordance with the findings of this research, "Image Processing" refers to the process of analyzing images with the objective of determining the significance of objects and identifying them. Image analysts analyze data that has been remotely sensed and attempt to detect, identify, classify, measure, and evaluate the significance of physical and cultural objects, as well as their patterns and spatial relationships. One subcategory of signal processing is known as video processing, and it is distinguished by the fact that the signals that are input and output are video files or video streams. Technology such as television sets, videocassette recorders (VCRs), DVD players, and other devices all make use of video processing algorithms. The processing of images and videos is extremely useful in a variety of contexts.

This paper aims at system level hardware design aspects towards meeting the requirements of 6G use cases in terms of latency and link data rates. It mainly describes the radio frequency (RF) transceiver architectures, hardware components models, channel modelling, and optimization at THz bands (> 100 GHz) under non-ideal conditions. This work aimed at the imperfections of hardware in handling the candidate 6G orthogonal frequency division multiplexin`g (OFDM) signals. The imperfections include non-linearities of power amplifier (PA), phase noise, and filter characteristics that spreads the signal spectrum beyond the channel bandwidth. The impact of various design parameters and deployment options are illustrated by conducting system-level simulations. The system parameters are designed and configured according to international telecommunication union-radio (ITU-R) radio models while quantifying the impairments. The RF hardware imperfections are demonstrated, and the results proved the practical feasibility of such RF systems.