Mobile Base Stations Research Articles

Joint Computation Offloading and Data Caching Based on Cooperation of Mobile-Edge-Computing-Enabled Base Stations

Mobile terminal applications with high computing complexity and high time delay sensitivity are developing quite fast today, which aggravates the load of mobile cloud computing and storage and further leads to network congestion and service quality decline. Mobile edge computing (MEC) is a way of breaking through the limits of computing and storage resources of mobile cloud and alleviating the load of mobile cloud. Computing time costs and transmission time costs are considered to be the main issues for the mobile cloud when carrying out computing offloading and data caching. Therefore, an efficient resource management strategy, which could minimize the system delay, is proposed in this paper. The new scheme offloads reasonably computing tasks and caches the tasks’ data from the mobile cloud to mobile edge computing-enabled base stations. An intelligence algorithm, genetic algorithm, is being used to solve the global optimization problem which would cause transmission delay and computing resources occupation, and to determine the computing offloading and data caching probability. The simulation of the system using MATLAB is conducted in 8 different scenarios with different parameters. The results show that our new scheme improves the system computing speed and optimizes the user experience in all scenarios, compared with the scheme without data caching and the scheme without computing offloading and data caching.

BRNN-LSTM for Initial Access in Millimeter Wave Communications

The use of beamforming technology in standalone (SA) millimeter wave communications results in directional transmission and reception modes at the mobile station (MS) and base station (BS). This results in initial beam access challenges, since the MS and BS are now compelled to perform spatial search to determine the best beam directions that return highest signal levels. The high number of signal measurements here prolongs access times and latencies, as well as increasing power and energy consumption. Hence this paper proposes a first study on leveraging deep learning schemes to simplify the beam access procedure in standalone mmWave networks. The proposed scheme combines bidirectional recurrent neural network (BRNN) and long short-term memory (LSTM) to achieve fast initial access times. Namely, the scheme predicts the best beam index for use in the next time step once a MS accesses the network, e.g., transition from sleep to active (or idle) modes. The scheme eliminates the need for beam scanning, thereby achieving ultra-low access times and energy efficiencies as compared to existing methods.

Calculation apparatus for modeling the distribution of electromagnetic fields of different sources

The calculation apparatus acceptable for assumptions and simplifications and sufficient for errors of final results for modeling the propagation of electric, magnetic and electromagnetic fields spread over a certain area was proposed. It is shown that to model the propagation of ultra-low frequency electric and magnetic fields (monitors, uninterruptible power supplies, transformers, electric motors and generators) it is possible to consider these sources as dipole and dipole-quadrupole type sources. That is, the field of the local source can be considered as a combination of electric and magnetic dipoles. This makes it possible to delineate with sufficient accuracy the zones of exceeding the maximum allowable field strengths. The calculation apparatus used to determine the radiation intensities of civil aviation radar equipment was adapted to model the propagation of electromagnetic fields of very high and ultra-high frequencies. The calculations of coefficients that take into account the parameters of radiation patterns in the horizontal and vertical planes for the most common radiation sources are given. These ratios and corresponding coefficients can be used to determine the electromagnetic environment in the presence of many high-frequency sources (mobile communication base stations, navigation equipment, radio relay stations, etc.). The proposed approach allows to automate processes of designing the placement of electromagnetic, electronic and radio equipment in production areas and territories, as well as to assess the environmental impact at the stages of design work. This will make it possible to delineate the isolines of the limits of exceeding the maximum permissible levels of electric magnetic and electromagnetic fields for different frequency ranges and categories of equipment and to automatically determine the electromagnetic load at each point of the controlled space.

Genetic Algorithm Based Method for Signal Channel Allocation of Mobile Base Station Optimization

Signal frequency band allocation is a crucial task in mobile communication. In realistic, the frequency resources that can be used to realize communication are relatively scarce. There are signal frequency interference problems between adjacent base stations. Existing frequency band resource allocation method try to find the best allocation program by visiting every node to search local optimal allocation program for each station. However, existing method is computationally complex. In this paper, we propose a global optimization model and solving the problem based on genetic algorithm. Finally, we test on an example to demonstrate the effectiveness the proposed method.

Software Defined Internet of Vehicles for Automation and Orchestration

We are introducing an innovative networking approach to the Internet of Vehicles (IoV) for their automation and orchestration by redesigning the wireless edge framework. To this end, we propose to expand the Software Defined Networking (SDN) functionality from the edge network to the cars, i.e. equipping our vehicles with mobile base stations having SDN capabilities. By adopting such a novel approach, most of the impending IoV automation and orchestration challenges are ameliorated, which has been extremely difficult and non-trivial to tackle by using standard existing approaches. The three primary challenges identified in this context are a) the scalability of the network of connected autonomous vehicles, b) the desirable security of the IoV data networking, and c) the flexibility of quality of experience (QoE) perceived by the vehicles. To tackle the aforementioned three challenges, we design a policy-driven framework for a secure and efficient IoV networking paradigm and then investigate its performance via analytic modeling. More importantly, from the IoV data networking perspective, we design an intent-based flow offloading scheme to facilitate enhanced and adjustable QoE. Furthermore, we develop a rigorous analysis to quantify the efficiency of the proposed SDN-capable IoV data networking by modeling TCP connections over WiFi. Using mathematics as a tool for reasoning the three key challenges, our feasibility analysis is validated with extensive simulations. Finally, we provide new insights by deriving the stability conditions for the data flow dynamics of the proposed approach.

Dynamic Collaborative Charging Algorithm for Mobile and Static Nodes in Industrial Internet of Things

Industrial Internet of Things inevitably leads to the implementation of highly data-intensive devices, where the associated sensing nodes accelerate the energy consumption rate, which ultimately produces an energy bottleneck. To address this issue, this article proposes a <i>dynamic collaborative charging algorithm</i> that acts on both the mobile nodes and the static nodes in a sensing node network. The proposed scheme is to design a collaborative group of charging robots that can rendezvous with the sensing nodes. The group includes aerial charging vehicles (ACVs)&#x2014;able to charge the underpowered mobile nodes, and terrestrial charging vehicles (TCVs), which charge their targeted static nodes. The aim of this study is to optimize the charging effect and the energy cost in the rendezvous process. This approach consists of two subalgorithms: 1) a charging algorithm for mobile nodes (CAMNs) and 2) a charging algorithm for static nodes (CASNs). The CAMNs is designed so that each underpowered mobile node can be charged by a dedicated ACV. For this purpose, a deep learning model is trained to divide the underpowered mobile nodes into appropriate clusters, each of which is equipped with a mobile base station. The rendezvous process is then constructed as a mixed continuous/discrete optimization problem, which is solved by using the firefly algorithm. In addition, the CASNs ensures that the TCVs traverse their routes, charging static nodes as they proceed. This traversing process was formulated as a multiobjective optimization problem, solved by using genetic algorithm. Through various experiments and case studies, the results have demonstrated both the feasibility and the efficiency of the proposed algorithms.

Interference Cancellation Based Spectrum Sharing for Massive MIMO Communication Systems.

Cellular network operators are predicting an increase in space of more than 200 percent to carry the move and tremendous increase of total users in data traffic. The growing of investments in infrastructure such as a large number of small cells, particularly the technologies such as LTE-Advanced and 6G Technology, can assist in mitigating this challenge moderately. In this paper, we suggest a projection study in spectrum sharing of radar multi-input and multi-output, and mobile LTE multi-input multi-output communication systems near m base stations (BS). The radar multi-input multi-output and mobile LTE communication systems split different interference channels. The new approach based on radar projection signal detection has been proposed for free interference disturbance channel with radar multi-input multi-output and mobile LTE multi-input multi-output by using a new proposed interference cancellation algorithm. We chose the channel of interference with the best free channel, and the detected signal of radar was projected to null space. The goal is to remove all interferences from the radar multi-input multi-output and to cancel any disturbance sources from a chosen mobile Communication Base Station. The experimental results showed that the new approach performs very well and can optimize Spectrum Access.

A low-cost, mobile real-time kinematic geolocation service for engineering and research applications

Centimetre accurate geolocation service is beneficial to a wide range of applications, ranging from sports engineering, civil infrastructure, autonomous vehicles, surveying to digitisation of historically significant structures. Previously, these features were confined to prohibitively expensive commercial hardware, requiring technical knowledge and experience to operate. Continued technological advancements have seen the miniaturisation of electronics and antennas, coupled with an increase in the number and performance of global navigation satellite systems (GNSS) by various nations and organisations, providing global signal coverage. This paper demonstrates a low-cost, mobile, real-time kinematic (RTK) geolocation service for engineering and research applications, fabricated from components readily available from commercial suppliers. This solution, consisting of a mobile RTK base station and RTK rover, provides centimetre-accuracy performance up to a distance of 15 km away from the base station. Correction data is transmitted over the internet using free and open software solutions. The small footprint of both the RTK base station and RTK rover, provides versatile applications even in remote locations. The performance of the geolocation service is validated using field experiments, comparing measurements against state-of-the-art photogrammetry, light detection and ranging (LiDAR) and digital level measurement technologies. The authors encourage the adoption of the RTK geolocation solution based on the calibrated results.

Random access conflict resolution of preamble waiting list based Game-theory

With the development of mobile communication network, Internet of things and communication base station, super reliable transmission of communication signal and super anti-interference ability, mobile communication technology has been popularized in various industries, and a large number of products have emerged in communication technology and related applications. However, the increase in the number of products has caused a huge load to the mobile base station. The limited access resources of mobile base station also bring high access delay and high access conflict risk to access equipment. Random access is the first step of equipment access to mobile communication network. It can reasonably allocate access resources in the process of random access, which will effectively control the access conflict in the process of large-scale equipment access. Based on this, this paper proposes a solution to the random access conflict of packet preamble based on waiting queue list. The scheme introduces ACB(Access Class Barring) access factor for different types of access devices At the same time, the preamble resources are grouped to reduce the load of single base station. The access probability of different demand types of equipment is continuously balanced by game model, which reduces the access probability of non-demand equipment and improves the access probability of demand equipment. Considering the conflict of retransmission waiting time and retransmission success probability in random access process, and the waste of access resources in mobile communication system, a preamble waiting queue list mechanism is proposed. This mechanism can reduce the repeated access and retransmission waiting of access devices by reasonably scheduling them to a high idle waiting queue The resulting access delay improves the access efficiency of the device, reduces the resource idle degree of the mobile communication system, and improves the resource utilization rate.

A Dual stopband two-sided frequency selective surface for mobile shielding applications

A two-sided frequency selective surface (FSS) is proposed to shield two bands of the mobile frequencies (EGSM-900 and DCS-1800). The FSS consists of an array of square concentric-rings cells printed on both sides of the substrate to offer better shielding of the two mobile frequencies. The CST Microwave suit is used for the simulations. The equivalent circuit model for the two-sided FSS is analysed and the transmission frequency in terms of the two stop frequencies is estimated. The obtained shielding is better than 40 dB across the two bands. The proposed FSS can be used to reduce mobile radiation or to isolate halls from nearby mobile base stations. The bandwidth of the FSS cell can be increased by using ring pairs of unequal sizes on the two sides of the substrate.

Techno-Economic and Environmental Analysis for Off-Grid Mobile Base Stations Electrification with Hybrid Power System in Tanzania

Techno-Economic and Environmental Analysis for Off-Grid Mobile Base Stations Electrification with Hybrid Power System in Tanzania

A novel sizing method of a standalone photovoltaic system for powering a mobile network base station using a multi-objective wind driven optimization algorithm

A new multi-objective wind driven optimization algorithm is proposed to size a standalone photovoltaic system’s components to meet the load demand for a mobile network base station at a 1% loss of load probability or less with a minimum annual total life cost. To improve the sized model’s accuracy, a long short-term memory deep learning model is utilized to forecast the hourly performance of a photovoltaic module. The long-term memory model’s performance is compared with those obtained by a linear photovoltaic model and an artificial neural network model. The comparison is carried out based on the values of normalized root mean square error, normalized mean bias error, mean absolute percentage error, and the training and testing time. Accordingly, on the values obtained for these statistical errors, the long short-term memory model outperforms better than the linear model and the artificial neural network model based. In addition, a dynamic battery model is utilized to characterize the dynamic charging and discharging process. The findings show that the optimal number of the photovoltaic array and the capacity of the storage battery required to cover the load demand of a mobile network base station are 5.4 kWp and 2640 Ah/48 V, respectively. Besides, the annual total life cycle cost for the sized photovoltaic/battery configuration is 4028.33 AUD/year. The simulation time for the proposed method is 421.25 s. To generalize the sizing results for the mobile network base stations based on Sydney weather conditions, the photovoltaic array and storage battery ratios are calculated as 0.324 and 0.223, respectively. In addition, the cost of an energy unit generated by the optimized system is 0.254 AUD/kWh. Here, the results of the proposed method have been compared with those obtained by developed and recent benchmark published methods. The comparison outcomes show the effectiveness of the proposed method in terms of providing a high availability sized system at minimum cost within less simulation time than the other considered methods.

Practical Consistency of Ethernet-Based QoS with Performance Prediction of Heterogeneous Microwave Radio Relay Transport Network

Microwave line-of-sight radio relay (RR) systems are a constitutive part of a telecom operator transport network, as an alternative to optical transmission systems when the latter are not technically possible or rational to implement. Nowadays, RR links are quite often used in the access network for connecting mobile radio base stations, thus also enabling traffic aggregation, and so on. In this paper, we focus on a practical, real-life, five-section heterogeneous RR network, comprising classic synchronous digital hierarchy (SDH) and SDH new generation network (NGN) architecture, hybrid parallel and mutually independent transmission of native Ethernet and TDM services, and all-IP network parts. Specifically, the main task of this work is to answer whether such a diverse RR system could satisfy the quality norms for Ethernet-based services, meaning whether a tolerable RR unavailability will necessarily imply the according Ethernet quality of service (QoS) degradation. This question is addressed by the comprehensive in-service and out-of-service testing of an operational hybrid RR transmission system. After extensive practical testing and appropriate analysis of the achieved results, it came out that the impact of RR-level impairments that determine the performance prediction affected the Ethernet QoS to the extent that BER values increased to the acceptability threshold values. We believe that the preliminary results reported here could serve as a hint and a framework for a more comprehensive cross-layer test strategy in terms of both test diversity and repeating rate, which contemporary network operators need to implement in order to enable the appropriate quality of experience for users of their services.

Performance Evaluation of RF Energy Harvesting Circuit with DRA and Planar Antennas

In this study, a rectenna (antenna + rectifier) performance is compared with two different types of antennas; planar and DRA. The CST Microwave Studio and Advance Design System (ADS) is used to perform co-simulation. In this, first a .S2P is generated using two similar antennas keeping at a far-field distance in CST, afterward it is imported in ADS and tested with a typical rectifier circuit. Further, two experimental methods are performed in indoor and outdoor environments to validate the simulation results. In the indoor environment, a horn antenna excited with a signal generator is used as an RF power transmitter. In contrast, in the outdoor environment, the horn antenna is replaced with an ambient power source like a mobile base station. In both methods, at receiving side rectenna (antenna + rectifier) is kept in the far-field region. Here, both planar metallic and dielectric resonator antennas are use done after another with the rectifier circuit to test the rectenna system. From the simulation and experiments performed in indoor and outdoor environment method, it is confirmed that the rectenna system tenders the best performance with dielectric resonator antenna.

Novel Pattern-Diverse Millimeter-Wave Antenna With Broadband, High-Gain, Enhanced-Coverage for Energy-Efficient Unmanned Aerial Vehicle

In this paper, a novel pattern-diverse technique to enhance the coverage of the broadband high-gain millimeter-wave (mmW) antenna is proposed for Unmanned Aerial Vehicle (UAV) communications. It overcomes the limited coverage of a mmW antenna array, and the low radiation efficiency of a multi-beam mmW antenna array. This technique enables antenna to radiate two isolated beams with different tilted angles, which can effectively increase the UAV coverage without enlarging the antenna size or degrading radiation efficiency. For demonstration, an 8 × 8 antenna array is designed with the tilted beams of 11° and 23° for the coverage from 6° to 28°. Measured results indicate two beams have 40 dB isolation, 15.2% impedance bandwidth, up to 21.7 dB stable gain, and up to 74.2% radiation efficiency. Antenna coverage could be further enhanced by arraying the proposed antennas in a flat structure. Example is given to radiate 18 beams covering ±28° seamless 2D plane over 57-64 GHz. The size of the proposed array is smaller than that of a standard A4 page, which is suitable for UAV-mounted mobile base station (MBS).

RETRACTED ARTICLE: Enhancement of network lifetime by fuzzy based secure CH clustered routing protocol for mobile wireless sensor network

Mobile Wireless sensor network conveys an innovative archetype of real time systems by means of restricted computation, transmission, storage, and vigor resources utilized for massive range of appliances wherever traditional system is frequently infeasible. Sensor nodes are compactly organized in an aggressive atmosphere to observe, identify, and scrutinize physical occurrence and utilized significant quantity of energy during broadcasting information. It is unfeasible and occasionally impractical to change battery and to preserve wider network lifetime. So, duration of battery and energy preservation is an exigent complication. Exact ClusterHead determination is one of the concerns that can condense energy utilization considerably. Low-energy adaptive-clustering hierarchy (LEACH) is most prominent hierarchical routing technique, ClusterHead is nominated in alternation basis related on probabilistic threshold cost and CHs are permitted to transfer events to basestation. In proposed FCHIDS tactic, a Outstanding-ClusterHead is nominated among CHs in cluster that can transfer information to mobile basestation by deciding appropriate fuzzy factors outstanding battery power, basestation mobility, clusters centrality and intrusion detection system. Fuzzy assumption engine is utilized to decide Outstanding-ClusterHead. The consequences are from simulating NS-2 and illustrations shows that proposed FCHIDS tactic achieves upto 5% superior than LEACH technique in provisions with partial amount of nodes active, enhanced constancy, and improved lifetime. Consequently it achieves upto 5% reduction in initial node expires from network than LEACH technique.

Traffic data prediction of mobile communication base station based on wavelet neural network

With the wide application of new media, users require more and more mobile communication. In order to satisfy users’ high-quality experience and save resources, it is necessary to predict the traffic data of mobile communication base station, so that mobile communication base station can adjust the frequency load quantity according to the traffic fluctuation. From March 1 to April 9, 2018, this paper collects traffic data, selects 40, 000 sets of data, uses python to mine data, and predicts the traffic data of mobile communication base station by establishing wavelet neural network short-time traffic prediction model. The results show that the average accuracy of the short-term prediction model is 43. 15 and the root mean square error is 0. 0076.

An Insight into Deployments of Green Base Stations (GBSs) for an Environmentally Sustainable World

Data traffic and the number of mobile subscribers have increased significantly prompting cellular network operators to install additional mobile cellular base stations (BSs) to meet the increasing demand. This proliferation of BSs has resulted in consequential increase in energy consumption and Green House Gases (GHGs) emission. Several techniques have been deployed to reduce the energy consumption of the base station in what is called a green base station. This paper presents an insight into these approaches and highlights key challenges and potential research directions. It also highlights what environmental sustainability activist, regulators and government can do to incentivize green BSs concept in Nigeria.

Negative Refractive Index Shaped Lens for Mobile Base Station

Negative Refractive Index Shaped Lens for Mobile Base Station

Research on the Trend of UAV Communication Signal Indication System

In recent years, with the application of high-definition video coding and decoding technology, high-precision satellite navigation technology, mobile base station positioning technology and wireless UAV wireless communication technology, the performance indicators and application scope of UA have been significantly improved. Whether it is industrial applications or specific applications, drones play an important role. With the continuous improvement of technical indicators, UAV wireless transmission technology needs further exploration and development. Although there is a lot of research on UAVs, there are still some shortcomings. Based on the AD9361 + ZYNQ7045 platform, this paper has completed the design and implementation of the UAV wireless transmission system. Although there are various integrated UAV wireless solutions on the market, the UAV communication frequency can be allocated to non-fixed frequency points that still do not meet the requirements, such as frequency band L, frequency band S or frequency band C. The design proposed in this paper is that the adjustable radio frequency range is 70MHz to 6GHz, which is sufficient to meet the application requirements of multiple communication frequency points. The UAV wireless transmission system proposed in this paper has strong scalability, wide application range and high integration, which has special reference significance for the design of UAV wireless transmission system. This article uses the flight control algorithm and PID control to analyze the signal range of the UAV communication signal indicating system and explore the future development trend. Through the method in this article, the UAV communication signal increased by 15%.