Recently, there has been increasing interest in the field of underwater wireless sensor networks (UWSNs), which is a basic source for the exploration of the ocean environment. A range of military and civilian applications is anticipated to assist UWSN. The UWSN is being developed by the extensive wireless sensor network (WSN) applications and wireless technologies. Therefore, in this paper, a review has been presented which unveils the existing challenges in the underwater environment. In this review, firstly, an introduction to UWSN is presented. After that, underwater localizations and the basics are presented. Secondly, the paper focuses on the architecture of UWSN and technologies used for underwater acoustic sensor network (UASN) localization. Various localization techniques are discussed in the paper classified by centralized and distributed localizations. They are further classified into estimated and prediction-based localizations. Also, various underwater localization algorithms are discussed, which are grouped by the algorithms based on range and range-free schemes. Finally, the paper focuses on the challenges existing in underwater localizations, underwater acoustic communications with conclusions.

Non-orthogonal multiple access (NOMA) is suggested as a radio access candidate for future wireless mobile networks. It utilizes the power domain for user multiplexing on the transmitter side and adopts a successive interference cancellation (SIC) as the baseline receiver scheme, considering the expected mobile device evolution in the near future. However, recent research focuses more on the performance evaluation of NOMA in context of assuming the perfect SIC at receiver side. In order to clarify the performance gap between the perfect and the practical SIC in NOMA schemes, and to examine the possibility of applying NOMA with practical SIC, this paper investigates the performance of NOMA applying multi-input multi-output (MIMO) technology with zero-forcing (ZF) and minimum mean square error (MMSE) SIC schemes. We propose an analysis on error effects of the practical SIC schemes for NOMA and in addition propose an interference-predicted minimum mean square error (IPMMSE) IC by modifying the MMSE weight factor using interference signals. According to the IPMMSE IC and analysis of IC error effect, we further suggest the remaining interference-predicted MMSE (RIPMMSE) IC to cancel the remaining interference. The simulation results show that by considering practical IC schemes, the bit error rate (BER) is degraded compared with conventional orthogonal multiple access (OMA). This validates that the proposed IC schemes, which can predict the interference signals, provide better performance compared to NOMA with conventional ZF and MMSE IC schemes.

For more than two decades, the issue of simultaneous localization and mapping (SLAM) has gained more attention from researchers and remains an influential topic in robotics. Currently, various algorithms of the mobile robot SLAM have been investigated. However, the probability-based mobile robot SLAM algorithm is often used in the unknown environment. In this paper, the authors proposed two main algorithms of localization. First is the linear Kalman Filter (KF) SLAM, which consists of five phases, such as (a) motionless robot with absolute measurement, (b) moving vehicle with absolute measurement, (c) motionless robot with relative measurement, (d) moving vehicle with relative measurement, and (e) moving vehicle with relative measurement while the robot location is not detected. The second localization algorithm is the SLAM with the Extended Kalman Filter (EKF). Finally, the proposed SLAM algorithms are tested by simulations to be efficient and viable. The simulation results show that the presented SLAM approaches can accurately locate the landmark and mobile robot.

As a crucial component of Internet‐of‐Thing (IoT), vehicular ad hoc networks (VANETs) have attracted increasing attentions from both academia and industry fields in recent years. With the extensive VANETs deployment in transportation systems of more and more countries, drivers’ driving experience can be drastically improved. In this case, the real‐time road information needs to be disseminated to the correlated vehicles. However, due to inherent wireless communicating characteristics of VANETs, authentication and group key management strategies are indispensable for security assurance. Furthermore, effective road message dissemination mechanism is of significance. In this paper, we address the above problems by developing a certificateless authentication and road message dissemination protocol. In our design, certificateless signature and the relevant feedback mechanism are adopted for authentication and group key distribution. Subsequently, message evaluating and ranking strategy is introduced. Security analysis shows that our protocol achieves desirable security properties. Additionally, performance analysis demonstrates that the proposed protocol is efficient compared with the state of the art.

Mobile robot localization has attracted substantial consideration from the scientists during the last two decades. Mobile robot localization is the basics of successful navigation in a mobile network. Localization plays a key role to attain a high accuracy in mobile robot localization and robustness in vehicular localization. For this purpose, a mobile robot localization technique is evaluated to accomplish a high accuracy. This paper provides the performance evaluation of three localization techniques named Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Particle Filter (PF). In this work, three localization techniques are proposed. The performance of these three localization techniques is evaluated and analyzed while considering various aspects of localization. These aspects include localization coverage, time consumption, and velocity. The abovementioned localization techniques present a good accuracy and sound performance compared to other techniques.

In this paper, a novel 2D direction of arrival (DOA) estimation approach based on the tensor technique is proposed for a conformal array in a massive multiple-input-multiple-output (MIMO) system under unknown mutual coupling. By placing sensors uniformly on the cylindrical surface, the received signal expression is formulated with the Khatri-Rao (KR) product. An unknown mutual coupling auto-suppression method based on the conformal array is investigated. Then, to utilize the multidimensional information of the received data, a third-order tensor is constructed based on the conformal array signal model, and the signal subspace is provided by higher-order singular value decomposition (HOSVD). Finally, the DOAs are estimated by conventional subspace-based algorithms. This approach provides improved DOA estimation performance owing to the utilization of the multidimensional information and the covariance tensor method, with lower SNR and fewer snapshots. The simulation results confirm that the proposed method outperforms the conventional method based on the vector model.