EURASIP Journal on Wireless Communications and Networking最新文献

We propose an early-detection scheme to reduce communications latency based on sequential tests under finite blocklength regime for a fixed-rate transmission without any feedback channel. The proposed scheme processes observations sequentially to decide in favor of one of the candidate symbols. Such a process stops as soon as a decision rule is satisfied or waits for more samples under a given accuracy. We first provide the optimal achievable latency in additive white Gaussian noise channels for every channel code given a probability of block error. For example, for a rate $R=0.5$ and a blocklength of 500 symbols, we show that only $63\%$ of the symbol time is needed to reach an error rate equal to ${10}^{-5}$ . Then, we prove that if short messages can be transmitted in parallel Gaussian channels via a multi-carrier modulation, there exists an optimal low-latency strategy for every code. Next, we show how early detection can be effective with band-limited orthogonal frequency-division multiplexing signals while maintaining a given spectral efficiency by random coding or pre-coding random matrices. Finally, we show how the proposed early-detection scheme is effective in multi-hop systems.

Cognitive satellite communication (SatCom) is rapidly emerging as a promising technology to overcome the scarcity of the exclusive licensed band model in order to fulfill the increasing demand for high data rate services. The paper addresses power allocation methods for multi-operator multi-beam uplink satellite communication systems co-existing with a Ka-band terrestrial network, using cognitive radio paradigm. Such a scenario is especially challenging because of (i) the coexisting multiple SatCom operators over the cognitive band need to coordinate the use of their resources under limited inter-operator information exchange, and (ii) nonlinear onboard high power amplifier (HPA) which leads to nonlinear interference between users and beams. In order to tackle the first challenge, we propose distributed power allocation algorithms including the standard Alternate Direction Multiplier Method (ADMM); Regarding the HPA nonlinear impairment, we propose nonlinear-aware power allocation based on Signomial Programming. The proposed solutions outperform state-of-the-art in both cases.

When it comes to running and managing modern supply chains, 6G Internet of things (IoT) is of utmost importance. To provide IoT with security and automation, blockchain and machine learning are two upper-layer technology that can help. First, we propose to utilize blockchain in modern supply chains to ensure efficient collaboration between all parties. Second, we adopt multi-head attention (MHA)-based gated recurrent unit (GRU) to do inbound logistics task prediction. Finally, numerical results justify that multi-head attention-based GRU model has better fitting efficiency and prediction accuracy than its counterparts.

Physical layer security (PLS) has been proposed to afford an extra layer of security on top of the conventional cryptographic techniques. Unlike the conventional complexity-based cryptographic techniques at the upper layers, physical layer security exploits the characteristics of wireless channels, e.g., fading, noise, interference, etc., to enhance wireless security. It is proved that secure transmission can benefit from fading channels. Accordingly, numerous researchers have explored what fading can offer for physical layer security, especially the investigation of physical layer security over wiretap fading channels. Therefore, this paper aims at reviewing the existing and ongoing research works on this topic. More specifically, we present a classification of research works in terms of the four categories of fading models: (i) small-scale, (ii) large-scale, (iii) composite, and (iv) cascaded. To elaborate these fading models with a generic and flexible tool, three promising candidates, including the mixture gamma (MG), mixture of Gaussian (MoG), and Fox's H-function distributions, are comprehensively examined and compared. Their advantages and limitations are further demonstrated via security performance metrics, which are designed as vivid indicators to measure how perfect secrecy is ensured. Two clusters of secrecy metrics, namely (i) secrecy outage probability (SOP), and the lower bound of SOP; and (ii) the probability of nonzero secrecy capacity (PNZ), the intercept probability, average secrecy capacity (ASC), and ergodic secrecy capacity, are displayed and, respectively, deployed in passive and active eavesdropping scenarios. Apart from those, revisiting the secrecy enhancement techniques based on Wyner's wiretap model, the on-off transmission scheme, jamming approach, antenna selection, and security region are discussed.

In unmanned aerial vehicle (UAV)-assisted networks, UAV acts as an aerial base station which acquires the requested data via backhaul link and then serves ground users (GUs) through an access network. In this paper, we investigate an energy minimization problem with a limited power supply for both backhaul and access links. The difficulties for solving such a non-convex and combinatorial problem lie at the high computational complexity/time. In solution development, we consider the approaches from both actor-critic deep reinforcement learning (AC-DRL) and optimization perspectives. First, two offline non-learning algorithms, i.e., an optimal and a heuristic algorithms, based on piecewise linear approximation and relaxation are developed as benchmarks. Second, toward real-time decision-making, we improve the conventional AC-DRL and propose two learning schemes: AC-based user group scheduling and backhaul power allocation (ACGP), and joint AC-based user group scheduling and optimization-based backhaul power allocation (ACGOP). Numerical results show that the computation time of both ACGP and ACGOP is reduced tenfold to hundredfold compared to the offline approaches, and ACGOP is better than ACGP in energy savings. The results also verify the superiority of proposed learning solutions in terms of guaranteeing the feasibility and minimizing the system energy compared to the conventional AC-DRL.

With the acceleration of informatization and the coverage of wireless networks, homes, conferences, schools and other places have a higher pursuit of the wireless transmission capabilities of electronic devices. Wireless screen transmission technology is used more frequently in life, work and study. This article mainly discusses the practical application of network multimedia courseware in college basketball teaching. This article first elaborates the teaching plan of multimedia courseware, including teaching content, teacher guidance, student learning and multimedia courseware. Secondly, the multimedia courseware of basketball tactics basic teaching is completed by using Flash mx2004 plug-in. After that, it specifically introduces the process of how to transmit basketball teaching content through multimedia equipment to the video network for students to learn under the wireless network environment. It emphasizes that the "wireless multimedia communication" course is an important course in the electronic information subject. Finally, through the teaching experiment, the accuracy of the multimedia teaching method was tested, and the validity of the courseware content was tested by the empirical validity evaluation method. At the same time, after the teaching experiment, in order to test the two groups of students' mastery of the basic coordination theory of basketball tactics, the basic coordination theory of basketball tactics was tested. The experimental group had 22 students with a score of 90 or more, accounting for 27.5%, and the control group had 13 students with a score of 90 or more, accounting for 16.5%. The results show that wireless network multimedia computer-assisted teaching has a positive effect on improving students' interest in learning.

Private networks will play a key role in 5G and beyond to enable smart factories with the required better deployment, operation and flexible usage of available resource and infrastructure. 5G private networks will offer a lean and agile solution to effectively deploy and operate services with stringent and heterogeneous constraints in terms of reliability, latency, re-configurability and re-deployment of resources as well as issues related to governance and ownership of 5G components, and elements. In this paper, we present a novel approach to operator models, specifically targeting 5G and beyond private networks. We apply the proposed operator models to different network architecture options and to a selection of relevant use cases offering mixed private-public network operator governance and ownership. Moreover, several key enabling technologies have been identified for 5G private networks. Before the deployment, stakeholders should consider spectrum allocation and on-site channel measurements in order to fully understand the propagation characteristic of a given environment and to set up end-to-end system parameters. During the deployment, a monitoring tools will support to validate the deployment and to make sure that the end-to-end system meet the target KPI. Finally, some optimization can be made individually for service placement, network slicing and orchestration or jointly at radio access, multi-access edge computing or core network level.

The body area network is now the most challenging and most popular network for study and research. Communication about the body has undoubtedly taken its place due to a wide variety of applications in industry, health care, and everyday life in wireless network technologies. The body area network requires such smart antennas that can provide the best benefits and reduce interference with the same channel. The discovery of this type of antenna design is at the initiative of this research. In this work, to get a good variety, the emphasis is on examining different techniques. The ultra-wide band is designed, simulated, and manufactured because the ultra-wide band offers better performance compared to narrowband antennas. To analyze the specific absorption rate, we designed a multilayer model of human head and hand in the high-frequency structure simulator. In the final stage, we simulated our antennas designed with the head and hand model to calculate the results of the specific absorption rate. The analysis of the specific absorption rate for the head and hand was calculated by placing the antennas on the designed model.

Small- and medium-sized enterprises (SEMs) are the important part of economic society whose innovation activities are of great significance for building innovative country. In order to investigate how technological innovation (TI) and business model design (BMD) affect the business performance of SMEs, samples of 268 SMEs in the artificial intelligence industry and hierarchical regression models are used in the analysis. The results indicate that TI, BMD, and the matching of them have different effects on the innovation of SMEs of different sizes. These findings are helpful for enriching the theory of the fit between TI and BMD and providing theoretical guidance for the innovation activities in SEMs.