A 5G network is the key driving factor in development of vehicle-to-vehicle (V2V) communication technology, and V2V has recently attracted great interest. In network, users can choose different transmission modes power levels for communication, to guarantee their quality-of-service (QoS), high capacity vehicle-to-infrastructure (V2I) links ultra-reliability V2Vlinks. Aiming atV2V mode selection adaptation networks, a reinforcement learning (RL) framework based on slow fading parameters...

Reasonable design and effective detection of the random access preamble has become a challenging task due to unique characteristics mobile satellite communications. To tackle this challenge, we first universal long sequence structure by concatenating multiple short Zadoff-Chu sequences that are insensitive carrier frequency offset (CFO), then propose new principles parameter selection for ensure minimum utilization root independence cyclic shift on beam radius. further reduce complexity...

This letter presents a novel adaptive alternating direction method of multipliers with support/signal value detection for compressed sensing. The in our algorithm can achieve an efficient reconstruction by leveraging more information that goes beyond simple sparsity. Especially time-correlated signals large-scale problems, proposal performs better than conventional methods, since accurate signal could be estimated from prior knowledge during initialization. Simulation results show improve...

Mission-critical communication (MCC) is one of the main goals in 5G, which can leverage multiple device-to-device (D2D) connections to enhance reliability for mission-critical communication. In MCC, D2D users reuses non-orthogonal wireless resources cellular without a base station (BS). Meanwhile, will generate co-channel interference and hence affect their quality-of-service (QoS). To comprehensively improve user experience, we proposed novel approach, embraces resource allocation power...

Recently, information-centric wireless networks (ICWNs) have become a promising Internet architecture of the next generation, which allows network nodes to computing and caching capabilities adapt growing mobile data traffic in 5G high-speed communication networks. However, design ICWN is still faced with various challenges respect capacity traffic. Therefore, edge (MEC) device-to-device (D2D) communications can be employed aid offloading core This paper investigates optimal policy for...

As the Virtual Reality (VR) industry expands, need for automated GUI testing is growing rapidly. Large Language Models (LLMs), capable of retaining information long-term and analyzing both visual textual data, are emerging as a potential key to deciphering complexities VR's evolving user interfaces. In this paper, we conduct case study investigate capability using LLMs, particularly GPT-4o, field view (FOV) analysis in VR exploration testing. Specifically, validate that LLMs can identify...

With the rapid growth of multimedia message exchange and digital communication, big data has become a research hotspot in various fields. The storage transmission have high requirements for security. Images, covering highest proportion data, should be processed transmitted with Compressive sensing (CS) beneficial property encryption that image can recovered fewer samples than conventional approaches use. In recent years, CS been studied not only to reduce resource signal acquisition but also...

Cognitive radio (CR) is a critical technique to solve the conflict between explosive growth of traffic and severe spectrum scarcity. Reasonable resource allocation with CR can effectively achieve sharing co-channel interference (CCI) mitigation. In this paper, we propose joint channel selection power adaptation scheme for underlay cognitive network (CRN), maximizing data rate all secondary users (SUs) while guaranteeing quality service (QoS) primary (PUs). To exploit underlying topology...

This study presents the development of an AI text generation detection tool based on Transformer model, aiming to enhance accuracy and provide a reference for future research. The employs series preprocessing steps text, including Unicode normalization, conversion lowercase, removal non-alphabetic characters using regular expressions, addition spaces around punctuation marks. It also eliminates leading trailing spaces, replaces consecutive ellipses with single space, connects segments...

Research on characteristics of tsunami forces acting conical islands and cylindrical structures placed top a island, as well the generation mechanisms forces, is limited. The total force its are studied in cases with different initial water depths relative wave heights. results indicate that peak values positive negative which increase both heights, have almost same magnitude. submerged state island does not change variation trend peaks height. Then located at positions compared analyzed,...

Compressed sensing is a novel technology that exploits sparsity of signal to perform sampling below the Nyquist rate, and thus has great potential in low-complexity video compression applications, due significant reduction rate ( SR) computational complexity. However, most current work about compressive (CVS) focused on real-valued measurements without being quantized, not applicable engineering practices. Moreover, many circumstances, total number bits often constrained. Therefore, how...

Photon mapping (PM) has been widely regarded as an efficient solution for light transport simulation, including challenging caustics paths and many-bounce indirect lighting. The efficiency of PM comes from reusing traced photons. However, the handling photon gathering in existing algorithms is universally biased -- expected value their results does not necessarily agree with true rendering equation. We present a novel method to efficiently achieve unbiased mapping. Instead aggregating...

In this letter, the routing and wavelength assignment problem in all optical networks is considered. We improve Max-RWA model presented by R. M. Krishnaswamy K. N. Sivarajan (see ibid., vol.5, p.435-7, Oct. 2001) introducing limited-range conversions. Considering transmission performance, we propose a new optimization objective, which to establish maximum number of connections with least converters. The modified formulated as integer linear programming (ILP) problem, then solved using...

Satellite communication is expected to play a pivotal role in supporting the ubiquitous machine-to-machine (M2M) connection. Due its wide beam coverage, however, one of major challenges accommodate massive and concurrent M2M random access (RA) requests with guarantee human-to-human communications. To tackle this challenge, an enhanced spatial group-based RA scheme presented from viewpoint preamble design. By leveraging large-capacity set configured only single root Zadoff-Chu sequence...

With digitization and globalization in the era of 5G beyond, research on high-throughput satellites (HTS) to increase communication capacity improve flexibility is becoming essential. To achieve efficient resource utilization dynamic traffic demand matching, multi-dimensional management (MDRM) problem HTS system has been studied this paper. Since MDRM a non-convex mixed integer problem, we decompose it into two tractable sub-problems. First, beam-domain configuration formed enable on-demand...

To meet the communication services with diverse requirements, dynamic resource allocation has shown increasing importance. In this paper, we consider multi-slot and multi-user (MSMU-RA) in a downlink cellular scenario aim of maximizing system spectral efficiency while guaranteeing user fairness. We first model MSMU-RA problem as dual-sequence decision-making process, then solve it by novel Transformer-based deep reinforcement learning (TDRL) approach. Specifically, proposed TDRL approach can...

Compressed sensing is a novel technology that exploits sparsity of signal in transform domain to perform sampling below the Nyquist rate, and has great potential video coding applications for its low-complexity. However, traditional orthonormal basis cannot be adopted provide sparse enough representation compressed sensing. Therefore, how use temporal/spatial redundancy main challenge. In this paper, we propose dictionary generation scheme block-based By means motion estimation measurement...

Distributed compressed video sensing (DCVS), combining advantages of and distributed coding, is developed as a novel powerful system to get an encoder with low complexity. Nevertheless, it still unclear how explore the method achieve effective recovery through utilizing realistic signal characteristics much possible. Based on this, we present spatiotemporal dictionary learning (DL) based reconstruction for DCVS, where both DL model l1-analysis correlation constraints are included in...

Traditional spectral confocal signal processing methods have problems such as difficulty in accurately extracting the peak wavelength, nonlinear error polynomial fitting calibration of wavelength and position, high dependence on hardware equipment. In this paper, method LSTM neural network is introduced to achieve direct characterization from full spectrum position information by using its mapping capability. The experimental results show that measurement accuracy resolution new, best our...

Object selection is the basis of natural user–computer interaction (NUI) in a virtual environment (VE). Among three-dimensional object techniques employed reality (VR), bare hand-based finger clicking and ray-casting are two convenient approaches with high level acceptance. This study involved 14 participants, constructed laboratory VR, compared above finger-based terms aspects task performance, including success rate, total reaction time, operational deviation, accuracy, at different...