In an era of rapidly evolving technology, the pursuit of higher data rates, extremely low latency, and robust reliability is becoming increasingly crucial. Applications such as Industrial Internet of Things (IIoT) demand that transmitted messages meet stringent time constraints. Traditional ARQ-based schemes struggle to achieve the required performance in the presence of feedback delays or feedback losses. Unlike conventional ARQ approaches, which acknowledge only original packets, network coding can acknowledge multiple degrees of freedom (DOF), making the feedback mechanism a pivotal factor for reliability-delay tradeoffs. On the other hand, UDP protocol operates blindly without feedback acknowledgments (ACKs). Thus, the selection of code to provide ultra-reliable and low-latency communications (URLLCs) over lossy channels without feedback ACKs is tedious. However, network coding inherent robustness against packet erasure positions it as a promising candidate for reliable communication without feedback ACKs. In this survey, we delve into cutting-edge opportunistic network coding schemes that can deliver high data rates and low latency, even in the face of feedback limitations such as feedback delays, feedback losses, or complete feedback absence. We focus on how network coding-based approaches maintain effective communication over lossy networks, regardless of these feedback limitations. In the context of UDP environments (i.e., blind coding), we present the interplay of some essential elements that must be integrated into network coding to enable reliable transmission without feedback ACKs. Our expectation is that this paper will set the stage and raise the interest of readers willing to explore Network codings (NCs) in the direction of URLLC for mission-critical (IIoT) applications.

This article presents a compact, planar, and circularly polarized array antenna operating in the W-band (84.5–110 GHz), with all its prototypes fabricated using a low-cost, traditional, microwave printed circuit board composed of Rogers RT/duroid 5880 (εr = 2.2, tanδ = 0.009). The final design that was fabricated and measured was a 4 × 4 array antenna having an overall size of 9 mm × 20 mm × 0.254 mm that used series feeding to reduce its sidelobes. Measurements of the 4 × 4 patch antenna array showed approximately 6.9% 3-dB axial ratio bandwidth along with 15.2 dBi maximum right-hand circularly polarized (RHCP) antenna gain at 100 GHz. The array antenna yielded RHCP radiation characterized by a low profile, low cross-polarization levels (<−25 dB), low sidelobe levels (≤−10 dB), and high radiation efficiency (>91%). Additionally, a two-port MIMO antenna system was investigated by considering side-by-side and front-tofront configurations, both of which achieved good isolation and considerable envelope correlation coefficient and diversity gain values. Therefore, the proposed series array and MIMO antennas can be reasonable candidates for 6G applications of the sub-THz band (100– 110 GHz) in ultra-high-speed wireless and satellite communication systems.

Mobile Edge Computing has been widely recognized as a key enabler for new latency-sensitive applications on resource constrained mobile devices. The objective to offload a computationally intensive task to a cloud server is in general intended to reduce the system’s energy consumption and/or latency. In this paper, we attempt to examine how profitable computation offloading is from a service provider’s perspective. The joint optimization of radio and computing resources along with offloading decisions results in a mixed integer nonlinear optimization problem which belongs to the class of NP-hard problems. To counter this challenge, we decouple the offloading decision from the resource allocation problem. Initially, approximately optimal offloading decisions are determined using evolutionary algorithms such as genetic algorithms and binary particle swarm optimization algorithms. After several iterations of the evolutionary process to make offloading decisions, the optimal solution is ultimately obtained that performs resource allocation based on exact calculation of the profit value. For faster execution of the evolutionary algorithm, instead of using an optimization solver to find the exact solution, we use a novel approach to seeding the initial population and a regression-based machine learning method to predict the optimal resource allocation values to minimize the objective function evaluation time. According to the simulations performed as part of this study, the proposed evolutionary algorithms outperform existing spectral efficiency-based offloading algorithm in terms of profitability, with shorter execution times as well. The effects of resource availability and the parameters of the algorithm on the profitability of offloading are also examined.

Due to recent technological developments such as online navigation, augmented reality (AR), virtual reality (VR), and digital twins, and the high demand from users for various location-based services (LBS), research on location estimation techniques is being actively conducted. As a result, there is an increasing demand for effective localization technologies that can be used in places where the use of Global Positioning System (GPS) is limited, especially in indoor spaces with very large areas. In this paper, a new structure for an indoor localization system in which wireless fingerprinting and visual-based positioning are hierarchically combined—the so-called Fi-Vi system—is proposed. This scheme consists of two steps: fingerprint-based localization (FBL) followed by visual-based localization (VBL). In the first positioning step (i.e., the FBL stage), the entire area of a significantly broad range for localization is divided into multiple regions, the size and the number of which depend on the target accuracy of this step. Moreover, a machine-learning (ML) or deep-learning (DL) model trained on a Wi-Fi fingerprint radio map selects suitable candidate regions among these multiple regions. In the second positioning step (i.e., the VBL stage), the final location is precisely estimated through visual-based positioning based on the received information regarding the candidate regions. The FBL stage uses a sparse radio map (SRM) for fingerprinting, which can be constructed with relatively little effort and cost compared to radio maps used in conventional fingerprinting methods. As a result, it can be easily combined with existing visual-based positioning methods with almost negligible implementation complexity. Because of the hierarchical structure and SRM, the proposed scheme shows a significant performance improvement in terms of computational load and time required for indoor localization compared to the use of the existing visual-based indoor positioning method alone. In addition, it provides high accuracy and robustness even in a dynamically changing indoor wireless environment where conventional wireless fingerprinting methods show significant performance degradation. Finally, the performance analysis of the proposed scheme was performed using the UJIIndoorLoc dataset. Experiments and theoretical analysis have shown that when the estimation accuracy of the candidate region for the test dataset was achieved at about 99% through the FBL stage, the average computational amount of the VBL stage for the final position estimation was only about 16% of that in cases where the visual-based positioning method was used alone.

This paper examines the protocol structure of ATSC 3.0, the next-generation terrestrial broadcasting standard, and explains in-depth the technology of Real-Time Object Delivery over Unidirectional Transport (ROUTE) and MPEG Dynamic Adaptive Streaming over HTTP (DASH). Specifically, it considers both low and service signaling methodologies of ROUTE/DASH, that enable immersive media, stereoscopic 3D, and 360 virtual reality (VR), delivery in ATSC 3.0. Furthermore, this paper also provides the signaling examples to give readers new perspectives on immersive broadcasting through ROUTE/DASH in ATSC 3.0. In the era of COVID-19 pandemics, this kind of type, the ATSC 3.0 immersive media service method is expected to become an alternative to performance and media consumption in the future.

An open‐loop precoder, which does not require any feedback channel information, is proposed to enhance the performance of spatial multiplexing in transmit‐correlated multi‐input–multi‐output (MIMO) channels. Different from previous open‐loop precoders based only on the amplitude parameter of channel correlation, the proposed precoder, designed with both amplitude and phase parameters, is more suitable for practical environments. The proposed scheme performs better than previous schemes in MIMO channels with random phase correlation.