Cellular Base Stations Research Articles

Electromagnetic field in the environment - estimation methods and monitoring

The paper describes the current legal status related to electromagnetic field (EMF) measurements in the context of environmental protection. It also presents the assumptions and exemplary results obtained from the EMF National Monitoring System which, in the authors' opinion, could be more reliable and better adapted to the current state of affairs in the radiocommunication industry. A simplified method of estimating electromagnetic field intensity from various sources, including in particular cellular base stations, using their basic parameters, was described. The electromagnetic field monitoring system operating in Poland was described, and alternative monitoring methods were presented. The authors introduced their own concept of mobile monitoring, whose assumptions perfectly fit into the current realities and can be performed with the use of the current measurement equipment available to laboratories of the Voivodeship Inspectorates for Environmental Protection. The construction of the measurement system was presented, and its measurement verification was carried out. Measurement errors resulting from the use of weather-resistant casing and from placing the device on the roof of the vehicle were estimated, confirming that their impact on the measurement uncertainty budget tends to be negligible. Auxiliary software for mobile monitoring was presented, with the aid of which verification was made by carrying out monitoring measurements in the city of Wrocław. The results obtained during the monitoring measurements in real conditions confirmed that the proposed method provides reliable results, which are not burdened with significant errors and distortions resulting from the proposed measurement methodology or from the construction of the measurement system itself. The developed system does not require significant financial outlays and is a perfect complement to the stationary measurements currently performed within the Environmental Monitoring System. Med Pr. 2019;70(5):567-85.

Prediction Based Vehicular Caching: Where and What to Cache?

The explosive growth of user demands for mobile data puts forward higher requirements for existing network architecture. In this case, many novel technologies, such as edge computing, ultra-dense network (UND), are recently proposed to alleviate the network burden of cellular macro base stations (MBSs). However, their performance is limited by dynamic user requests and uncertain user mobility since they highly rely on the fixed infrastructure. Along with the advent of autonomous driving era, autonomous vehicles possess strong computing and communication ability, which provide a new idea to resolve the limitation of infrastructure based network architecture. In this paper, we exploit the performance of a vehicular caching scheme where the role of moving vehicles is changed from service consumers in traditional networks to service providers and service consumers. As such, a prediction based vehicular caching scheme is proposed. Specifically, an optimization problem is firstly formulated by exploring the relationship of caching vehicles and mobile users, in order to optimize the network energy efficiency. The nonconvex optimization problem is solved by decomposing it into a nonlinear programming problem. By applying the Lyapunov method and autoregressive neural network (ANN), an online caching decision algorithm is finally proposed to make caching decisions. Extensive simulations are conducted to evaluate the caching scheme in different scenarios. Results show that the vehicular caching scheme can obviously improve network energy efficiency with different requests, but the increment is reduced under the scenario of intensive requests. The comparison between online and offline caching also shows the necessity of online caching decision making due to its benefit in resource utilization where system gain is increased from 8.4% to 59.24%.

A Study on the Effects of Cellular Mobile Networks on People in Tikrit City Based on Power Density Measurements and Calculations

In this paper, the emitted electromagnetic waves (EMW) from different cellular mobile base stations (BSs) have been measured and calculated in order to study their effects on public health. Moreover, a comparison between the effect of radiated power from the BSs on people who live near them and those who live away has been made by using OpenSignal software and calculated theoretically. The values of power density for different cells were also calculated to compare them with the maximum permissible exposure limit-the acceptable range values of power density. The measurements were done in Tikrit City considering ten cells and various locations and distances. The results show that most of the power density and EMV for the tested cells are within the acceptable range. However, power density and EMV for two of tested cells have hurtful effects in the long term for people who live near the BSs.

A cellular base station antenna configuration for variable coverage

The field coverage offered by the base station antenna in GSM systems influences the reception and interference performances. The coverage can be varied by scanning the mainbeam direction or varying the shape of the radiation pattern. In cellular system applications, a simple technique is desirable to achieve this goal. A simple technique to vary the coverage of cellular base station is investigated. The technique uses two conventional antennas tilted by a certain angle and fed by the same signal but at variable amplitudes. It is demonstrated that the field across one half of the covered sector can be gradually increased while that at the other half is reduced by varying the excitations of the two antenna elements. This can be deployed in a simple electronic means in response to the changing scenario rather readjusting the direction of the base station antenna.

Delay-Minimization Nonorthogonal Multiple Access Enabled Multi-User Mobile Edge Computation Offloading

The significant advances of cellular systems and mobile Internet services have yielded a variety of computation intensive applications, resulting in great challenge to mobile terminals (MTs) with limited computation resources. Mobile edge computing, which enables MTs to offload their computation tasks to edge servers located at cellular base stations (BSs), has provided a promising approach to address this challenging issue. Considering the advantage of improving transmission efficiency provided by nonorthogonal multiple access (NOMA), we propose an NOMA-enabled computation offloading scheme, in which a group of MTs offload partial of their computation workloads to an edge server based on the NOMA transmission. After finishing all MTs’ offloaded computation workloads, the edge server sends the computation results back to the MTs based on NOMA. We aim at minimizing the overall delay for completing all MTs’ computation requirements, which is achieved by jointly optimizing the MTs’ offloaded computation workloads, and the uploading duration for the MTs to send their computation workloads to the BS, and the downloading-duration for the BS to send the computation results back to the MTs. Despite the nonconvexity of the joint optimization problem, we exploit its layered structure and propose an efficient algorithm to compute the optimal offloading solution. Numerical results are provided to validate the accuracy and efficiency of our proposed algorithm and show the performance advantage of our NOMA-enabled computation-offloading scheme.

Renewable Energy Assisted Sustainable and Environment Friendly Energy Cooperation in Cellular Networks

In this paper, an energy cost minimization framework is presented for a green cellular network. The proposed novel energy cooperation scheme ensures optimal energy cooperation among grid-connected green cellular base stations (BSs). The framework is both economical and environment-friendly where the energy is saved by cutting down on the grid energy and sharing surplus green energy among the BSs. The intended scenario requires knowledge of harvested energy as well as traffic awareness to determine energy demand of a BS and inter-BS connectivity for incorporating energy transfer. A realistic utility function is developed to minimize energy cost under various constraints which entail energy borrowing from neighboring BSs (offering their surplus energy which is cheaper than grid and diesel generator), thereby reducing the overall energy cost of the network. The proposed framework for energy cooperation has bilinear non-convex structure. We use McCormick envelopes to convexify the optimization problem and transform the bilinear non-convex optimization into a linear optimization problem. The numerical results verify the effectiveness of the proposed traffic aware sustainable and environmental friendly BS operation through energy cooperation.

Design and characterisation of HE11 dual-mode dielectric-loaded filter for cellular base station applications

ABSTRACTThis paper presents a dual-mode dielectric-loaded bandpass filter for cellular base station applications. The filter consists of a ceramic puck that is placed centrally on the base of a metallic housing. The resonator offers a size reduction ratio of approximately 7:1 compared with equivalent air-filled coaxial filters. The filter is designed at a resonant frequency of 2.05 GHz and bandwidth of 50 MHz. The spurious-free window (SFW) was 500 MHz from the fundamental frequency. A fourth order dual-mode bandpass filter is designed, fabricated, and tested to validate the proposed approach. A good agreement between the measurement and simulation results is demonstrated.

An Efficient Distributed Multi-hop Relay Supporting (EDMRS) MAC Protocol for Wireless Sensor Networks

Past few decade have seen an immense growth in demand for mobile access, which has in turn reflected in growth of wireless communication. However, maintaining quality of service in wireless networks has proved to be a challenge to the propagation use of this technology, even though it is cost-effective as compared to wired network technology. The use of multi input multi output (MIMO) systems overcomes the challenge to certain extent; as they contain multiple transmitter and receiver antennas and have been widely acknowledged for their QoS and transmit diversity. Though suited for cellular base stations, MIMO systems are not suited for small sized wireless nodes due their hardware complexity, cost, and increased power requirements. This is reason why MIMO systems have been substituted by cooperative communication; because they allow relays i.e. mobile or fixed nodes in a communication network, to share their resources and forward other node’s data to the destination node. The aim of this paper is to present an efficient multi-hop distributed relay supporting medium access control (MAC) protocol (EDMRS) that works in multi-hop environment and improves the energy efficiency and the life of relay nodes without compensating the throughput of the network. The protocol has been simulated using NS2 simulator. The proposed protocol is compared with energy efficient cooperative MAC protocol and legacy distributed coordination function on the basis of throughput, energy efficiency, transmission delay and end to end delay with various payload sizes. The results thus achieved are indicative of outperformance of the proposed protocol in comparison to other two protocols.

Planning UAV activities for efficient user coverage in disaster areas

Climate changes brought about by global warming as well as man-made environmental changes are often the cause of sever natural disasters. ICT, which is itself responsible for global warming due to its high carbon footprint, can play a role in alleviating the consequences of such hazards by providing reliable, resilient means of communication during a disaster crisis. In this paper, we explore the provision of wireless coverage through UAVs (Unmanned Aerial Vehicles) to complement, or replace, the traditional communication infrastructure. The use of UAVs is indeed crucial in emergency scenarios, as they allow for the quick and easy deployment of micro and pico cellular base stations where needed. We characterize the movements of UAVs and define an optimization problem to determine the best UAV coverage that maximizes the user throughput, while maintaining fairness across the different parts of the geographical area that has been affected by the disaster. To evaluate our strategy, we simulate a flooding in San Francisco and the car traffic resulting from people seeking safety on higher ground.

A Mobility-Aware Vehicular Caching Scheme in Content Centric Networks: Model and Optimization

Edge caching is being explored as a promising technology to alleviate the network burden of cellular networks by separating the computing functionalities away from cellular base stations. However, the service capability of existing caching scheme is limited by fixed edge infrastructure when facing the uncertainties of users' requests and locations. The vehicular caching, which uses the moving vehicles as cache carriers, is regard as an efficient method to solve the problem above. This paper studies the effectiveness of vehicular caching scheme in content centric networks by developing optimization model towards the minimization of network energy consumption. Particularly, we model the interactions between caching vehicles and mobile users as a 2-D Markov process, in order to characterize the network availability of mobile users. Based on the developed model, we propose an online vehicular caching design by optimizing network energy efficiency. Specifically, the problem of caching decision making is firstly formulated as a fractional optimization model, towards the optimal energy efficiency. Using nonlinear fractional programming technology and Lyapunov optimization theory, we derive the theoretical solution for the optimization model. An online caching algorithm to enable the optimal vehicular caching is developed based on the solution. Finally, extensive simulations are conducted to examine the performance of our proposal. By comparison, our online caching scheme outperforms the existing scheme in terms of energy efficiency, hit ratio, cache utilization, and system gain.

Cellular Base Station Assisted Indoor Positioning

In this paper, first, two methods of positioning an indoor receiver with transferred global navigation satellite system signals from cellular base stations are proposed. Then, a technique of fusing the position results produced by the two methods through Kalman filter is introduced; thus, the positioning accuracy is improved. To mitigate the near–far problem generated by signals from base stations and satellites, a pulse shaping scheme and the strategy of assigning pulse patterns to base stations are investigated.

UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks

Fifth generation wireless networks are expected to provide advanced capabilities and create new markets. Among the emerging markets, Internet of Things (IoT) use cases are standing out with the proliferation of a wide range of sensors that can be configured to continuously monitor and transmit data for intelligent processing and decision making. Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. To this end, we propose the utilization of unmanned aerial vehicles (UAVs) to collect data in dense wireless sensor networks using projection-based compressive data gathering (CDG) as a novel solution methodology. CDG is utilized to aggregate data en-route from a large set of sensor nodes to selected projection nodes acting as cluster heads (CHs) in order to reduce the number of needed transmissions leading to notable energy savings and extended network lifetime. The UAV transfers the gathered data from the CHs to a remote sink node, e.g., a 5G cellular base station, which avoids the need for long range transmissions or multihop communications among the sensors. Our problem definition aims at clustering the sensors, constructing an optimized forwarding tree per cluster, and gathering the data from selected CH nodes based on projection-based CDG with minimized UAV trajectory distance. We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. We demonstrate the superiority of the proposed approach and the designed algorithms via detailed performance results with analysis, comparisons, and insights.

ADAPTIVE CORRELATOR IN NON-EMITTING RADAR SYSTEMS

The paper discusses a new method of processing information in non‑emitting radar systems, whose work is based on the use of a signal from third‑party sources – television and radio broadcasting transmitters, as well as cellular base stations. An adaptive correlator for such radar stations is proposed. The method is based on the analysis of the autocorrelation function (ACF) of a transmitter signal and the adaptive formation of detection areas, based on the properties of the current ACF. Statistical quality parameters were introduced to evaluate the developed method and these parameters were estimated for the DVB‑T2 (Digital Video Broadcasting – Terrestrial) signal, in particular, the achievable characteristics by the side lobes of the lag time uncertainty function for such a signal are shown. It is noted that several adaptive correlators should be simultaneously implemented in non‑radiant radar. The results of processing real data confirm the effectiveness of the proposed method.

Ultra-Low Power Wake-up Radio for 5G IoT

5G Internet of Things (5G IoT), which is currently under development by 3GPP, paves the way for connecting diverse categories of devices to the IoT via cellular networks. For battery-powered low-cost IoT devices, wake-up radio (WuR) appears as an eminent technique for prolonging the lifetime of such devices, thanks to its outstanding energy consumption performance. However, only some small-size battery-powered IoT devices are able to transmit to a cellular IoT base station (BS) directly. In this article, we present W2B-IoT, a prototype implementation of a WuR-based twotier system, which bridges cellular IoT BS and WuR via a Bluetooth low energy (BLE)-enabled Android smartphone. Such a WuR-enabled IoT device features a current consumption of merely 390 nA and a response time of 95 ms for decoding a wake-up call.

Backup Battery Analysis and Allocation against Power Outage for Cellular Base Stations

Base stations have been widely deployed to satisfy the service coverage and explosive demand increase in today's cellular networks. Their reliability and availability heavily depend on the electrical power supply. Battery groups are installed as backup power in most of the base stations in case of power outages due to severe weathers or human-driven accidents, particularly in remote areas. The limited numbers and capacities of batteries, however, can hardly sustain a long power outage without a well-designed allocation strategy. As a result, the service interruption occurs along with an increasing maintenance cost. Meanwhile, a deep discharge of a battery in such case can also accelerate the battery degradation and eventually contribute to a higher battery replacement cost. In this paper, we closely examine the base station features and backup battery features from a 1.5-year dataset of a major cellular service provider, including 4,206 base stations distributed across 8,400 square kilometers and more than 1.5 billion records on base stations and battery statuses. Through exploiting the correlations between the battery working conditions and battery statuses, we build up a deep learning based model to estimate the remaining lifetime of backup batteries. We then develop BatAlloc , a battery allocation framework to address the mismatch between the battery supporting ability and diverse power outage incidents. We present an effective solution that minimizes both the service interruption time and the overall cost. Our real trace-driven experiments show that BatAlloc cuts down the average service interruption time from 4.7 hours to nearly zero with only 85 percent of the overall cost compared to the current practical allocation.

Analogue Wireless Beamforming Exploiting the Fiber-Nonlinearity of Radio Over Fiber-Based C-<roman>RANs</roman>

As a key technique of supporting the fixed backbone network, radio over fiber (RoF) systems transmit the radio frequency signals over optical fiber in order to take advantage of their large available bandwidth. In this context, optical fiber aided phased antenna array (PAA) based beamforming techniques have attracted substantial research interest with the goal of improving the cell-edge coverage of cellular base stations. In this paper, we conceive a novel optical fiber aided beamforming technique based on the fiber's nonlinearity to be applied in cloud radio access network (C-RAN). In our proposed technique, the PAA elements are fed by the phase-shifted signals introduced by our highly nonlinear fiber (HNLF) aided phase-shifting solution, which results in an angular beamsteering range of around 90 $^{\circ }$ . This can be exploited by sectorization in cellular networks to reduce the cochannel interference imposed. Furthermore, we exploit the proposed RoF-aided phase shifting technique in C-RAN, where our proposed system takes advantage of the centralized signal processing capability of the RoF system to conceive an all-optical processing based tunable beamforming system. While our flexible HNLF-aided phase-shifting process is confined to the central office of the C-RAN, the end users in the C-RAN cellular networks are capable of flexibly choosing the serving remote radio heads and employing diverse wireless transmission techniques. Through integrating our HNLF-aided phase-shifting design into the proposed C-RAN, we impose as little as 0.1 dB signal-to-noise ratio degradation compared to its traditional electronic counterpart, which requires extra phase-shifters.

Data Correlation-Aware Resource Management in Wireless Virtual Reality (VR): An Echo State Transfer Learning Approach

In this paper, the problem of wireless virtual reality (VR) resource management is investigated for a wireless VR network in which VR contents are sent by a cloud to cellular small base stations (SBSs). The SBSs will collect tracking data from the VR users, over the uplink, in order to generate the VR content and transmit it to the end-users using downlink cellular links. For this model, the data requested or transmitted by the users can exhibit correlation, since the VR users may engage in the same immersive virtual environment with different locations and orientations. As such, the proposed resource management framework can factor in such spatial data correlation, to better manage uplink and downlink traffic. This potential spatial data correlation can be factored into the resource allocation problem to reduce the traffic load in both uplink and downlink. In the downlink, the cloud can transmit 360 contents or specific visible contents that are extracted from the original 360 contents to the users according to the users' data correlation to reduce the backhaul traffic load. For uplink, each SBS can associate with the users that have similar tracking information so as to reduce the tracking data size. This data correlation-aware resource management problem is formulated as an optimization problem whose goal is to maximize the users' successful transmission probability, defined as the probability that the content transmission delay of each user satisfies an instantaneous VR delay target. To solve this problem, an echo state networks (ESNs) based transfer learning is introduced. By smartly transferring information on the SBS's utility, the proposed transfer-based ESN algorithm can quickly cope with changes in the wireless networking environment.

A Novel Theoretical Model for Cellular Base Station Radiation Prediction

A Novel Theoretical Model for Cellular Base Station Radiation Prediction

BROADBAND MICROSTRIP ANTENNA FOR 2G/3G/4G MOBILE BASE STATION APPLICATIONS

a staircase patch microstrip antenna with slots is proposed to cover the 2G/3G/4G cellular mobile base station bands, when the antenna is excited with a transmission line, creates several modes these modes are composite to obtain a large bandwidth. The proposed antenna operates in the band from 0.86 GHz to 4.78 GHz with an impedance bandwidth of 138%. The use of staircase patch antenna is to achieve more attractive performance such as wider bandwidth, better impedance matching and better radiation. Inserting different slots to the patch of the antenna to enhance the gain and return loss. The gain is obtained ranging from 2.18 dBi to 5.3 dBi. Good radiation efficiencies ranging from 70% to 97% is achieved.

Uplink achievable rate in underlay random access OFDM-based cognitive radio networks

This paper investigates the uplink achievable rate of secondary users (SUs) in underlay orthogonal frequency division multiplexing based cognitive radio networks, where the SUs randomly access the subcarriers of the primary network. In practice, the primary base stations (PBSs), such as cellular base stations, may not be placed close to each other to mitigate the interferences among them. In this regard, we model the spatial distribution of the PBSs as a β-Ginibre point process which captures the repulsive placement of the PBSs. It is assumed that in order to alleviate the interferences at the PBSs from the SUs, each SU controls its transmit power based on the average interference level at the closest PBS induced by the SU. We first analytically identify the characteristics of the transmit powers at the SUs. Then, tight approximations of the uplink achievable rate of the secondary network are provided in two different scenarios that assume either a decentralized or centralized allocation of the SUs’ subcarriers, respectively. The accuracy of our analytical results is validated by simulation results.