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Owing to the hasty growth of communication technologies in the Underwater Internet of Things (UIoT), many researchers and industries focus on enhancing the existing technologies of UIoT systems for developing numerous applications such as oceanography, diver networks monitoring, deep-sea exploration and early warning systems. In a constrained UIoT environment, communication media such as acoustic, infrared (IR), visible light, radiofrequency (RF) and magnet induction (MI) are generally used to transmit information via digitally linked underwater devices. However, each medium has its technical limitations: for example, the acoustic medium has challenges such as narrow-channel bandwidth, low data rate, high cost, etc., and optical medium has challenges such as high absorption, scattering, long-distance data transmission, etc. Moreover, the malicious node can steal the underwater data by employing blackhole attacks, routing attacks, Sybil attacks, etc. Furthermore, due to heavyweight, the existing privacy and security mechanism of the terrestrial internet of things (IoT) cannot be applied directly to UIoT environment. Hence, this paper aims to provide a systematic review of recent trends, applications, communication technologies, challenges, security threats and privacy issues of UIoT system. Additionally, this paper highlights the methods of preventing the technical challenges and security attacks of the UIoT environment. Finally, this systematic review contributes much to the profit of researchers to analyze and improve the performance of services in UIoT applications.

Non-orthogonal multiple access (NOMA) has a key feature that the cell-center user (CCU) has prior information about the messages of the cell-edge user (CEU) in the same user-pair. It means that CCU can be used for retransmission when the CEU requests retransmission. As ultra-reliability and low-latency communication (URLLC) requires high-reliability constraints (e.g., 99.999%), using CCU for retransmission can be useful to satisfy the reliability constraint. In this study, to ensure the reliability of CEU, cooperative retransmission (CR) scheme for downlink NOMA systems is proposed. And the CR scheme is evaluated with Block error rate (BLER) considering reliability and with packet loss rate (PLR) in terms of reliability and latency constraints. And the evaluation results showed that the proposed CR scheme can satisfy the target BLER for URLLC low SNR compared to the conventional retransmission scheme, and showed the improved PLR compared to the conventional retransmission scheme in low SNRs.

Many companies are adapting cloud computing technology because moving to the cloud has an array of benefits. During decision-making, having processed for adopting cloud computing, the importance of risk management is progressively recognized. However, traditional risk management methods cannot be applied directly to cloud computing when data are transmitted and processed by external providers. When they are directly applied, risk management processes can fail by ignoring the distributed nature of cloud computing and leaving numerous risks unidentified. In order to fix this backdrop, this paper introduces a new risk management method, Enterprise Risk Management for Operationally Critical Threat, Asset, and Vulnerability Evaluation (ERMOCTAVE), which combines Enterprise Risk Management and Operationally Critical Threat, Asset, and Vulnerability Evaluation for mitigating risks that can arise with cloud computing. ERMOCTAVE is composed of two risk management methods by combining each component with another processes for comprehensive perception of risks. In order to explain ERMOCTAVE in detail, a case study scenario is presented where an Internet seller migrates some modules to Microsoft Azure cloud. The functionality comparison with ENISA and Microsoft cloud risk assessment shows that ERMOCTAVE has additional features, such as key objectives and strategies, critical assets, and risk measurement criteria.

In the last few decades, underwater communication systems have been widely used for the development of navy, military, business, and safety applications, etc. However, in underwater communication systems, there are several challenging issues, such as limitations in bandwidth, propagation delay, 3D topology, media access control, routing, resource utilization, and power constraints. Underwater communication systems work under severe channel conditions such as ambient noise, frequency selectivity, multi-path and Doppler shifts. In order to collect and transmit the data in effective ways, multi-media/multi-band-based adaptation layer technology is proposed in this paper. The underwater communication scenario comprises of Unmanned Underwater Vehicles (UUVs), Surface gateways, sensor nodes, etc. The transmission of data starts from sensor nodes to surface gateway in a hierarchical manner through multiple channels. In order to provide strong and reliable communication underwater, the adaptation layer uses a multi-band/multi-media approach for transferring data. Hence, in this paper, existing techniques for splitting the band such as Orthogonal Frequency-Division Multiple Access (OFDMA), Frequency-Division Multiple Access (FDMA), or Orthogonal Frequency-Division Multiplexing (OFDM) are used for splitting the frequency band, and the medium selection mechanism is proposed to carry the signal through different media such as Acoustic, Visible Light Communication (VLC), and Infrared (IR) signals in underwater. For the channel selection mechanism, two phases are involved: 1. Finding the distance of near and far nodes using Manhattan method, and 2. Medium selection and data transferring algorithm for choosing different media.

Beyond 6G services and applications demand high and efficient processing capacity due to the massive connectivity of users equipment (UEs). However, the high computational capability and energy consumption of UEs are limited, which becomes a main challenge to overcome. Multi-access edge computing (MEC) has recently been studied widely as it can potentially assist complex tasks executed at UEs. Furthermore, several techniques have been proposed to optimize task offloading among users. Thus, another challenge in MEC is emerging due to the fact that mobile users do not always have a line-of-sight (LoS) to the base station (BS) due to the blocking object. Therefore, it can affect users data rate and result in incremental energy consumption. This research introduces the concept of reconfigurable intelligence surfaces (RIS) to support multiple-input-single-output (MISO) base stations (BS) in both uplink (UL) and downlink (DL) using BCD algorithms. While previous studies concentrate on enhancing task offloading and neglecting inter-user interference, this study suggests an optimization approach for UL and DL data rates, as well as minimizing task offloading delays. The results indicate that optimizing task placement, phase shift, and precoding can reduce the duration of task offloading.

In this paper, the Selective Multiple Acknowledgement (SMA) method, based on Multiple Acknowledgement (MA), is proposed to efficiently reduce the amount of data transmission by redesigning the transmission frame structure and taking into consideration underwater transmission characteristics. The method is suited to integrated underwater system models, as the proposed method can handle the same amount of data in a much more compact frame structure without any appreciable loss of reliability. Herein, the performance of the proposed SMA method was analyzed and compared to those of the conventional Automatic Repeat-reQuest (ARQ), Block Acknowledgement (BA), block response, and MA methods. The efficiency of the underwater sensor network, which forms a large cluster and mostly contains uplink data, is expected to be improved by the proposed method.

In this paper, several MAC scheduling methods applicable to an underwater environment are proposed. Besides, a new marine communication system model was proposed to improve the reliability of the proposed SBMAC method. The scheme minimizes transmission of control frames except for data transmission and various transmission methods and ACK methods can be used together. Simulation models are set indices and analysis of the underwater environment is established to conduct reliable simulations. Consequently, the performance improvement of the proposed method is verified with respect to delay time, data transmission rate, memory utilization, energy efficiency, etc.

In this paper, a novel phase offset (PO)-aided index modulation (IM) for orbital angular momentum (OAM) communication, called OAM-PO-IM, is proposed to enhance capacity. The proposed system conveys two types of index information including an active mode combination (AMC) and misalignment of PO states. This method leverages the PO state induced by the selective activation of antenna elements within a uniform circular array (UCA). Specifically, a UCA is divided into multiple uniform circular subarrays (UCSAs) in the transmitter, and additional index bits are allocated according to the activation state of the UCSAs. In addition, the modified Bessel function (MBF) of the first kind is used to derive the channel model to allow a straightforward determination of the optimal AMC for the OAM-IM system. To detect index and symbol bits, the receiver provides a maximum likelihood (ML) detector and a new low-complexity ML detector using the log-likelihood ratio (LLR). The effectiveness of the proposed OAM-PO-IM is verified through comprehensive simulations that benchmark its performance against the existing OAM and OAM-IM in terms of sum capacity, bit error rate (BER), and energy efficiency. Compared with the OAM-IM, the proposed OAM-PO-IM provides a capacity gain of additional $\log _{2}{G}$ bps/Hz, where G denotes the number of UCSA. Furthermore, this scheme improves the gain by approximately 1 dB at a BER of $10^{-4}$ for active mode $L_{A}=2$ at 6 bps/Hz.

The concept of reconfigurable intelligent surface-assisted (RIS) for assisting non-orthogonal multiple access (NOMA) transmission, where the phases can be adjusted to decrease error rates and increase capacity, has been gaining popularity as a promising candidate for 6G communication and beyond. This paper considers RIS-NOMA downlink transmission under the Rician fading channel. A coordinate reflector interleaving (CRI) is proposed, where two groups of reflector elements are introduced, such as in-phase element and quadrature element groups. Therefore, it can reduce system complexity because of fewer successive interference cancellations (SIC) among users. As a result, a computer simulation shows that CRI-RIS-NOMA preserves a lower BER compared to conventional RIS-NOMA. Moreover, the superiority of CRI-RIS-NOMA over RIS-NOMA is that it can work at any power allocation for two users. This paper comprehensively studies theoretical derivation for 2 and 4 users to verify the computer-simulated BER. An upper-bound analysis of CRI-RIS-NOMA was also studied to observe the impact of RIS elements for high SNR cases.

In this paper, we propose divergence intensity (DI) and mode combinations for multiple orbital angular momentum (OAM) users to enhance the sum capacity. Generally, OAM multiplexing has beam divergence (BD) limiting the achievable link distance and degrading performance. The effective OAM channel model implies DI which is considered as intensity of OAM mode. In addition, the near–far mode combination is recommended to be sub-optimal compared with different mode combinations which types are sequential and uniform. The sub-optimal mode combination outperforms the other two mode combinations because channel gain shares the DI effect. The performance of the proposed scheme is derived and simulated in terms of normalized DI, capacity per user, and sum capacity.

In this article, wavelet Orthogonal Frequency Division Multiplexing (OFDM) based non-orthogonal-multiple-access (NOMA) combined with massive MIMO system for 6G network is proposed. For mMIMO transmissions, the suggested system could enhance the performance by utilizing wavelets and is able to compensate channel impairments for the transmitted signal. Performance measures include spectral efficiency (SE), symbol error rate (SER), and peak to average power ratio (PAPR). Simulation results prove that the proposed system outperforms the conventional fast Fourier transform (FFT) based NOMA systems.

Organizations are increasingly depending on their employees to contribute suggestions aimed at enhancing organizational processes, boosting overall efficiency, and fostering innovation. However, some factors might hinder employees from expressing their thoughts. While there is evidence suggesting an effect of supervisor social undermining behavior on employee voice, the impact on innovative types of voice, specifically promotive voice, remains uncertain. This study aims to explore the association between supervisor social undermining and employee promotive voice. Moreover, this research investigates how employee perceptions of procedural justice moderate this relationship, utilizing the Conservation of Resources theory. Data were collected from 115 highly skilled employees, and hierarchical regression analysis was employed to assess the proposed hypotheses. The findings suggest that when individuals encounter social undermining behavior from their supervisor, they are less inclined to engage in promotive voice behavior. Interestingly, the results indicate that this relationship becomes stronger when individuals possess higher perceptions of procedural justice. To the best of our knowledge, this study is the first to investigate the impact of supervisor social undermining on promotive voice while considering procedural justice as a moderator in this relationship. The findings of this study suggest several theoretical and practical implications and provide directions for future research.

In this paper, a spatial modulation aided uplink non-orthogonal multiple access (SM-NOMA) without successive interference cancellation (SIC) is proposed. The SIC-free SM-NOMA system is investigated under both perfect and imperfect channel state information (CSI). Moreover, on the receiver side, both SIC-based and SIC-free detection techniques are used to analyze the bit error rate (BER) performance of SM-NOMA. Finally, the performance of SIC-free SM-NOMA is evaluated and compared with the conventional NOMA, and SIC-based SM-NOMA. The results show that the SIC-free SM-NOMA outperforms conventional NOMA in terms of spectral efficiency, energy efficiency, and BER.

Trash or garbage is one of the most dangerous health and environmental problems that affect pollution. Pollution affects nature, human life, and wildlife. In this paper, we propose modern solutions for cleaning the environment of trash pollution by enforcing strict action against people who dump trash inappropriately on streets, outside the home, and in unnecessary places. Artificial Intelligence (AI), especially Deep Learning (DL), has been used to automate and solve issues in the world. We availed this as an excellent opportunity to develop a system that identifies trash using a deep convolutional neural network (CNN). This paper proposes a real-time garbage identification system based on a deep CNN architecture with eight distinct classes for the training dataset. After identifying the garbage, the CCTV camera captures a video of the individual placing the trash in the incorrect location and sends an alert notice to the relevant authority. [ABSTRACT FROM AUTHOR]