A kriging approach to predicting coverage in wireless networks

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.

The rapid development of artificial intelligence and modern communication technology provides a powerful opportunity to realize the transformation, upgrading and high-quality development of exhibition management. To solve the optimal coverage problem of wireless network in the exhibition area, a new generation of artificial intelligence algorithm is introduced to propose a novel method for solving the network coverage problem based on Harris Hawk optimization (HHO) algorithm. From the perspective of maximizing coverage and minimizing coverage redundancy, the multi-objective coverage optimization problem of wireless network nodes is optimally extracted into a function and solved using the improved HHO (IHHO) algorithm. Through the simulation of the wireless network coverage in the exhibition area, the experimental results show that the comprehensive evaluation index score of the optimization algorithm reaches 98.03%, which is higher than the traditional particle swarm optimizer (PSO) and the standard HHO. The proposed IHHO algorithm can be effectively applied to the network coverage problem and has a greater advantage over the traditional optimization methods in terms of improving node coverage, and has great practicality.

Development of gradient elution retention model in ion chromatography by using radial basis function artificial neural networks

Reconfigurable intelligent surface (RIS) technology is a smart way of controlling the radio signal propagation to improve the capacity and coverage of wireless networks. RIS tunes the phase shifts of the incident signals in a dynamic fashion. Channel modeling is an important aspect in RIS-based mmWave communication for the next-generation wireless networks. However, to achieve maximum benefit from RIS-assisted wireless systems, it is essential to provide accurate channel state information (CSI). But, it is very challenging to get accurate CSI because of large number of RIS elements, their passive nature, and the training overhead involved during the channel estimation. To overcome the higher training overhead, in this article we aimed to take advantage of the correlation and sparsity of channels in RIS-assisted channel estimation. The objective of this work is to propose a simplified channel model for the RIS-assisted physical channel of a massive multi-input-multi-output (mMIMO) wireless communication system and analyze its performance in terms of transmitted powers, MIMO configurations, and achievable bit rates. The simulated results proved that the strategic placement of RIS with optimal phase shifts and optimal MIMO configuration can enhance the maximum achievable rate. The achievable rates of the proposed channel modeling are compared with the existing state-of-the-art methods to prove its efficiency. Also, the combination of mMIMO technology along with RIS-assisted communication provides degrees of freedom in terms of signal coverage, energy consumption, and system complexity.

In the present world, the spectrum efficiency along with the capacity and coverage of wireless networks are being improved by wireless specialists. Wireless link performance could be enhanced and improved by using multiple antenna technology called Space time wireless technology. There exists some advancement in the present MIMO techniques which could further improve the overall wireless Local Area Network (LANs) and Wide Area Network (WANs). In Multipath fading performance gain is very important which could be achieved by using an efficient Space-Time Coding (STC) technique. This Space Time coding along with Alamouti Scheme is a very vibrant research topic. In the forthcoming generation of mobile communication there will be a need of high data rate, reliable communication link and vast multimedia capabilities, STBC is the one solution for these. This paper presents the Space-Time Block Codes (STBC) for wireless networks using Alamouti Scheme in which multiple antennas are being used at both transmitter and receiver. The simulations have been done in MATLAB.

Cooperative relays improve reliability and coverage in wireless networks by providing multiple paths for data transmission. Relaying will play an essential role in vehicular networks at higher frequency bands, where mobility and frequent signal blockages cause link outages. To ensure connectivity in a relay-aided vehicular network, the relay selection policy should be designed to efficiently find unblocked relays. Inspired by recent advances in beam management in mobile millimeter wave (mmWave) networks, this paper addresses the question: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">how can the best relay be selected with minimal overhead from beam management?</i> In this regard, we formulate a sequential decision problem to jointly optimize relay selection and beam management. We propose a joint relay selection and beam management policy based on deep reinforcement learning (DRL) using the Markov property of beam indices and beam measurements. The proposed DRL-based algorithm learns time-varying thresholds that adapt to the dynamic channel conditions and traffic patterns. Numerical experiments demonstrate that the proposed algorithm outperforms baselines without prior channel knowledge. Moreover, the DRL-based algorithm can maintain high spectral efficiency under fast-varying channels.

As crowdsourcing using sensor-enabled smartphones boosted the confluence of human mobility and ambient network information, it opens up more opportunities for many promising crowd-centric application systems. This paper considers a WiFi advisory system, where crowdsourcing technology is used to gather information of wireless networks for understanding wireless network capability better including the coverage, connectivity, and locations of wireless networks. Such a system will address two critical challenges: (1) no self-contained bootstrapping data and (2) device-dependent data processing. To address the first one issue, we design and implement an opportunistic sensing system for smartphones to collect wireless information along human mobility without human engagement. To address the second issue, we design a data aggregation algorithm to infer the locations of wireless networks based on crowdsourced data from several different smartphones. In addition, we also analyze the computation complexity of our data aggregation algorithm. Finally, we implement our wireless network monitoring infrastructure to study the spatial and temporal variation and patterns of wireless networks systematically.

The aim of the research presented in this article was to determine the value of the friction coefficient using a simple tribological test and to build an empirical model of friction with the use of radial basis function artifi-cial neural networks. The friction tests were carried out on a specially designed friction simulator that allows a sheet metal strip to be drawn between two fixed dies. The test materials were sheets of Ti-6Al-4V titanium alloy with a thickness of 0.5 mm. The friction tests were carried out with variable contact forces of counter-samples with rounded surfaces and in various lubrication conditions. Mineral oils and bio-degradable oils with the addition of boric acid (5 wt %) were tested. Based on the results of friction investigations, neural models of friction were built using RBF artificial neural networks. The good properties of the RBF network 2:2-35-1:1 were confirmed by a high value of the determination coefficient R2 = 0.9984 and a low value of the S.D. ratio equal to 0.0557. It was found that the COF value was the highest for the average values of both the nominal pressure and kinematic viscosity. Over the entire range of nominal pressures applied, SAE10W-40 engine oil ensured the most effective reduction of the COF. The COF value was the highest for the average values of both the nominal pressure and kinematic viscosity.

Unmanned aerial vehicles that abbreviates (UAVs) are flying platforms, known as drones, which have features such as mobility, adaptive altitude and flexibility. UAVs admit numerous applications that can be used as aerial base stations to enhance coverage, capacity, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. A Software Defined Network (SDN) Controller is the application that acts as a strategic control point in a software-defined network. It is the ’brain’ of the network. Controller manages flow control to the routers/switches ‘under’ (via southbound APIs), the business logic and applications ’above’ (via northbound APIs) to deploy intelligent networks. Wireless networking with software defined (SDWN) is the use of SDN conceptions in wireless networks by using a controller in the control plane. SDWN facilitates the creation of new adaptive mechanisms according to various applications and user requirements, such as mobility, handover, security and quality of service (QoS). In this paper, simulation work has been conducted to compare and investigate four SDN controllers (Pox, Ryu, Floodlight and OpenDaylight) in order to see which one is suitable to be used. Mininet-Wifi has been selected as the simulation tool to do the experiments and Python script for programming. The results obtained reveals that Ryu controller is the best selection in terms of latency and packet loss.

Radio resource management for user-relay assisted OFDMA-based wireless networks

The processes’ modeling is an important aspect in the industry since it allows to obtain high productivity with energy and material savings. The hybrid process electrochemical discharge machining (ECDM) is subject to uncertainty and inaccuracy levels in the parameters, so a viable option to model this process is through soft computing techniques such as fuzzy logic and artificial neural networks. In this work, we present three models using fuzzy logic, backpropagation network, and radial basis function network for the prediction of the material removal rate (MRR). The gap voltage (Vg), peak current (Ip), and frequency (f) were taken as input parameters. A 3-factor full factorial design was developed with 2 levels (23), two replicas, and four central points. The model with the higher accuracy according to experimental result was radial basis function artificial neural network with 97.25% of accuracy.

تعتمد أنظمة الاتصالات على إشارات أبراج الهاتف الخلوي التي تؤثر على جودة وكفاءة شبكات الاتصالات. في هذا البحث ، تم توضيح تغطية شبكة التنبؤ لشبكة 4G اللاسلكية للمشغل "A" في مدينة النزهة. الهدف الرئيسي أولاً هو الخروج بخرائط شبكة تنبؤية توضح جودة شبكات الاتصال في منطقة الدراسة وتحديد المناطق ذات التغطية الجيدة والسيئة ، من أجل الحفاظ على التغطية وتحسينها من خلال نقل الأبراج والهوائيات الخلوية ، وزيادة حجمها. الرقم ، أو من خلال تركيب أخرى جديدة في مناطق التغطية السيئة ، وهناك هدف آخر هو مقارنة هذا الناتج بكفاءة تغطية الشبكة الفعلية. في هذه الدراسة ، تم اعتماد برامج نظم المعلومات الجغرافية للتعامل مع البيانات المكانية والسمات وإدارتها ومعالجتها وتحليلها. تم استخدام امتدادات GIS لتصميم شبكات الاتصالات مثل برنامج Mentum-Planet الذي تم من خلاله حساب وتمثيل تغطية شبكة التنبؤ. تم جمع بيانات الأبراج والقطاعات الخلوية أولاً ثم معالجتها لإنشاء تنبؤ بشبكة تغطية 4G للمشغل "A" بناءً على نموذج الانتشار (Q9). تمت مقارنة النتائج لاحقًا بكفاءة الشبكة الناتجة عن اختبار القيادة. وجد أن قوة الإشارة كانت بين -95 و -75 ديسيبل. حوالي 24.2٪ و 75.8٪ من مساحة الدراسة لديها تغطية شبكية متوسطة وممتازة على التوالي. أظهر اختبار القيادة مناطق ضعف تغطية الشبكة موزعة في جميع أنحاء منطقة الدراسة. خلص هذا البحث إلى أن استخدام نظم المعلومات الجغرافية في الاتصالات يقلل من تكلفة ووقت التنفيذ. يوصى بشدة بتضمين ارتفاعات المباني في نموذج الانتشار لأنها تؤثر على انتشار موجات الاتصال ، وزيادة الأبراج الخلوية في مناطق التغطية السيئة ، وتعديل نموذج الانتشار لضمان جودة الخدمة والتغطية الفعالة.

This paper illustrates the fuzzy logic based approach to the control of a plant or a system, and discusses some of the possible shortcomings of the usual inference mechanisms. Radial basis function artificial neural networks have been shown to be effective in a number of applications, and have the advantage that network training is a very rapid process due to their structure. In fact, this is usually accomplished by the solution of a system of linear equations, a process for which fast and reliable algorithms are available. Radial basis function networks are shown to provide a means of constructing an ‘inference engine’ capable of handling a rule base in which plant state and control actions are specified in terms of fuzzy sets. The resulting inference mechanism is shown to avoid the phenomena of ‘rule overlap’ which can be a feature of fuzzy control algorithms. It is interesting to note that in this application of radial basis function networks, the usual problems on the number and location of centres do not arise. The paper concludes with a brief discussion of some experimental results achieved.

The wireless mesh network (WMN) is an economical low-power solution to provide wireless broadband access in intelligent transportation systems (ITSs). This paper investigates how to deploy access points (APs) to improve throughput and quality-of-service (QoS), when the multihop communication is used to extend the coverage of wireless ITS network. Frequency planning is suggested to improve the capacity with QoS provisioning and to make the system more scalable. To investigate the overall tradeoffs among QoS, throughput, and coverage, we develop an analytical model to evaluate throughput, frame delay, and jitter for the considered ITS WMN using the carrier-sense multiple-access (CSMA) medium access control (MAC) protocol. Then, we apply an optimization approach to determine the optimal separation distances between APs with the delay requirement. To provide a guideline for network planning, we compare the uniform-spacing and increasing-spacing AP deployment strategies. The uniform-spacing strategy is to make all the APs with the same separation distance. In the increasing-spacing strategy, the separation distances between APs are increased from the central AP to the outer APs. Because of the shorter separation distance, the AP closer to the central AP can deliver higher traffic. It is shown that the increasing-spacing strategy outperforms the uniform-spacing strategy in terms and a profit function, considering the capacity and the total cost for deploying APs.

随着高校数字化校园网络的广泛应用，校内机器增多，无线网络的覆盖，相应的IP地址分配也在不断增多，IP地址冲突现象与日俱增，在一定程度上影响了网络的正常运行。本文依据实践经验，从基础网络管理和网络技术入手，提出解决方案，为增强校园网网络管理和安全管理、提高维护效率提供参考。 With increasing applications of network digitalization and coverage of wireless network in the campus, relevant facilities and IP address distribution also increase. The IP address interference issue is affecting regular network operation. This paper is based on the practical experience to work out the solution for enhancing campus network management and security management, facilitating maintenance efficiency from basic network management and technology.