Long Term Evolution Base Station Research Articles

Multipath tracking with LTE signals for accurate TOA estimation in the application of indoor positioning

ABSTRACT Indoor positioning with high accuracy plays an important role in different application scenarios. As a widely used mobile communication signal, the Long-Term Evolution (LTE) network can be well received in indoor and outdoor environments. This article studies a method of using different reference signals in the LTE downlink for carrier phase time of arrival (TOA) estimation. Specifically, a solution is proposed and a multipath tracking Software Defined Receiver (SDR) is developed for indoor positioning. With our SDR indoor positioning system, the pilot signals of the LTE signals are firstly obtained by the coarse synchronization and demodulation. Then, with the assistance of the pilot signals, the time delay acquisition, the multipath estimating delay lock loop (MEDLL) algorithm, and the multipath anomaly detection are sequentially carried out to obtain navigation observations of received signals. Furthermore, to compare the performance of different pilot signals, the Secondary Synchronous Signals (SSS) and Cell Reference Signals (CRS) are used as pilot signals for carrier phase-based TOA estimation, respectively. Finally, to quantify the accuracy of our multipath tracking SDR, indoor field tests are carried out in a conference environment, where an LTE base station is installed for commercial use. Our test results based on CRS show that, in the static test scenarios, the TOA accuracy measured by the 1-σ error interval is about 0.5 m, while in the mobile environment, the probability of range accuracy within 1.0 m is 95%.

Simultaneous LTE Signal Propagation Modelling and Base Station Positioning Based on Multiple Virtual Locations.

In the Long Term Evolution (LTE) system, the Signal Propagation Model (SPM) and the location information of the base stations are required for positioning a smartphone. To this end, this paper proposes a technique for estimating the SPM and the location of the base station at the same time using location-based Reference Signal Received Power (RSRP) information acquired in a limited area. In the proposed technique, multiple Virtual Locations (VLs) for a base station are set within the service area. Signal propagation modelling is performed based on the assumptions that a base station is in each VL and the RSRP measurements are obtained from the corresponding base station. The residuals between the outputs of the estimated SPM and the RSRP measurements are then calculated. The VL with the minimum sum of the squared residuals is determined as the location of the base station. At the same time, the SPM estimated based on the corresponding VL is selected as the SPM of the base station. As a result of the experiment in Seoul, it was confirmed that the positions of seven base stations were estimated with an average accuracy of 40.2 m.

Solar radio emission as a disturbance of radiomobile networks

This paper analyses the effects of solar radio emissions in the radiomobile context, for the first time leveraging massive European Telecommunications Standards Institute (ETSI) 3rd Generation Partnership Program (3GPP) Minimization of Drive Test (MDT) radio measures produced by 4G LTE (Long Term Evolution) terminals and by 4G LTE Base Station cells. A method to study solar noise effects starting from radiomobile 3GPP standard MDT measures is illustrated and correlated with the excellent 10.7 cm (2800 MHz) indicator of solar activity (National Research Council Canada). The effects of solar disturbance on the LTE radio access network for mobile services are analysed, and possible countermeasures are presented from the perspective of radiomobile network evolution to 5G and 6G.

A Pedestrian Indoor Navigation System Using Deep-Learning-Aided Cellular Signals and ZUPT-Aided Foot-Mounted IMUs

A signal-sensor-based indoor pedestrian navigation system is developed. The proposed system: 1) utilizes a foot-mounted inertial navigation system (INS), in which the accumulated errors are mitigated via a zero velocity update (ZUPT) approach; 2) exploits opportunistically cellular long-term evolution (LTE) signals in a deep neural network (DNN)-based synthetic aperture navigation (SAN) framework, in which the pedestrian’s motion is utilized to suppress multipath-induced errors. The proposed DNN-SAN-LTE-ZUPT-INS (DUALS) indoor pedestrian navigation system utilizes the complementary the desirable characteristics of both subsystems, coupled via two architectures: (a) loosely-coupled and (b) tightly-coupled. This paper designs and assesses both architectures experimentally in an indoor environment. The experimental study demonstrates a pedestrian traversing a trajectory of 600 m in 14 minutes, including a stationary period, straight segments, up/down the stairs, and riding in an elevator, while receiving signals from 4 LTE base stations (also known as evolved node Bs (eNodeBs)). The proposed tightly-coupled DUALS system exhibited a three-dimensional (3-D) position root mean-squared error (RMSE) of 1.34 m, outperforming the loosely-coupled DUALS, ZUPT-aided INS, and LTE-DNN-SAN, which achieved a position RMSE of 1.38, 1.49, and 1.97 m, respectively.

Evaluating Smartphone Accuracy for RSSI Measurements

Smartphones are affordable devices nowadays, capable of embedding a large variety of sensors such as magnetometers or orientation sensors, but also the hardware needed to connect them to most wireless communication technologies such as Wi-Fi, Bluetooth, or cellular networks. Therefore, they are handy devices able to perform received signal strength indicator (RSSI) measurements for a wide variety of applications such as cellular coverage maps, indoor localization, or proximity tracking. However, to the best of our knowledge, the accuracy of such measurements has never been rigorously assessed. The goals of this article are to assess the accuracy of the RSSI measurements made with a commercial off-the-shelf (COTS) smartphone in a variety of conditions and how possible inaccuracies can be corrected. We primarily focus on the long-term evolution (LTE) RSSI, but we also extend our results to the Bluetooth RSSI. In this article, we build a controlled experimental setup based on commodity hardware and on open-source software. We evaluate the granularity and limitations of the Android application programming interface (API) that returns the RSSI. We explore how reliable the measurements in a controlled environment with a mono-polarized antenna are. We show that the orientation of the smartphone, the position or orientation of the source, and the transmission power have a significant impact on the accuracy of the measurements. We introduce several correction techniques based on radiation matrix manipulations and on machine learning in order to improve measurement accuracy to less than 5-dBm RMSE, when compared to a professional equipment. We also explore the reliability of measurements made in an outdoor realistic environment. We show that although transmission diversity available in LTE base stations significantly improves the measured RSSI regardless of the smartphone orientation, the Bluetooth RSSI remains largely sensitive to the smartphone orientation.

SkyCore

The advances in unmanned aerial vehicle (UAV) technology have empowered mobile operators to deploy LTE (long-term evolution) base stations (BSs) on UAVs and provide on-demand, adaptive connectivity to hotspot venues as well as emergency scenarios. However, today's evolved packet core (EPC) that orchestrates LTE's radio access network (RAN) faces fundamental limitations in catering to such a challenging, wireless, and mobile UAV environment, particularly in the presence of multiple BSs (UAVs). In this work, we argue for and propose an alternate, radical edge EPC design, called SkyCore that pushes the EPC functionality to the extreme edge of the core network---collapses the EPC into a single, lightweight, self-contained entity that is colocated with each of the UAV BS. SkyCore incorporates elements that are designed to address the unique challenges facing such a distributed design in the UAV environment, namely the resource constraints of UAV platforms, and the distributed management of pronounced UAV and UE mobility. We build and deploy a fully functional version of SkyCore on a two-UAV LTE network and showcase its (i) ability to interoperate with commercial LTE BSs as well as smartphones, (ii) support for both hotspot and stand-alone multi-UAV deployments, and (iii) superior control and data plane performance compared to other EPC variants in this environment.

An Accurate and Real-Time Commercial Indoor Localization System in LTE Networks

In this paper, a commercial high-accuracy, low-cost and real-time indoor building-level localization system is proposed, which is applicable for locating the Minimization of Drive-Tests (MDT) data in the long-term-evolution (LTE) cellular communication network system. The system utilizes MDT data containing Global Navigation Satellite Systems (GNSS) information which is easy to collect and low cost to assist indoor localization, instead of using indoor drive test (DT) data which needs high manual collection and maintenance costs. In order to compensate for the loss of location accuracy, this paper innovatively divide the online process into two phases: indoor and outdoor (IO) identification phase and indoor localization phase. A real-time and precise GMM-based unsupervised algorithm is applied to identifying if the non-GNSS MDT data is in indoor environment in IO identification phase. Then, a multi-class classification algorithm based on Bayesian classifier is used to locate indoor MDT data to the specific building. The results of experiments conducted in an in-service LTE network using more than 100 LTE base stations demonstrate that the proposed technique yields a IO identification accuracy of 90% and an indoor location accuracy of 49.3m(@67%) respectively, which provides at least 30.2% enhancement in location accuracy compared to traditional technology without DT fingerprint database. This proposed indoor localization technique is applicable in network optimization and Operation and Maintenance (O&M) to assist communication service providers to reduce their operating expense (OPEX) by locating those MDT data without GNSS information.

Estimation of Electromagnetic Compatibility Between DVB-T/DVB-T2 and 4G/5G in the 700 MHz Band for Co-Channel Case

Abstract The 694–790 MHz band (700 MHz) known also as the second digital dividend was allocated to the mobile radiocommunication service on a primary basis in Region 1 and identified to International Mobile Telecommunications by the World Radiocommunication Conference 2012 (WRC-12). The designation of mobile service in Europe and other countries of Region 1 in 700 MHz band was obtained after the World Radiocommunication Conference 2015 (WRC-15). Administrations of Region 1 will be able to plan and use these frequencies for mobile networks, including IMT. The goal of this study is to estimate the electromagnetic compatibility of Digital Video Broadcasting – Terrestrial (DVB-T/DVB-T2) and LTE (Long Term Evolution) technology operating both in 700 MHz band. The study assumes frequency division duplex (FDD) channel arrangement of 703–733 MHz (for uplink) and of 758–788 MHz (for downlink). The model contains two parts: a DVB-T/DVB-T2 system and LTE mobile broadband network. Co-channel scenario is considered in this paper, and possible impact of DVB-T/DVB-T2 on LTE base stations (receivers) is also investigated. The Monte Carlo simulations within SEAMCAT software and the Minimum Coupling Loss (MCL) method are used for interference investigation. The coordination trigger field strength value predetermined by GE06 Agreement is also used in this study. The Monte Carlo method presents more relaxed electromagnetic compatibility scenario in comparison with the MCL method. For SEAMCAT simulations, ITU-R P.1546-5 radio propagation model is used. The obtained results present the required minimum separation distance between DVB-T/DVB-T2 and LTE networks in the 694–790 MHz in order to provide the necessary performance of LTE mobile network.

Multi-Band Time of Arrival Estimation for Long Term Evolution (LTE) Signals

This paper presents a method for estimating the time of arrival (ToA) of long term evolution (LTE) signals received on multiple separate transmission bands by the same base station (BS) mast. By exploiting the overall bandwidth occupied by the different signals and the correlation between the corresponding channel impulse responses, a higher precision is achieved with respect to the usually adopted single-band approach whenever the time-correlation among the bands is sufficiently high. The ToA estimation is carried out by generalizing the space-alternating generalized expectation-maximization (SAGE) algorithm to the multi-band context, proving that the availability of multiple bands provides a reduced standard deviation for the estimated ToA, with a limited increase of the computational cost. The main analyzed issue consists in the management of the asynchrony between transmitters belonging to distinct cellular operators, which is addressed by developing a suitable method to combine the contributions provided by the different bands. The method is validated by simulations in dual- and tri-band scenarios, and is further applied to real dual-band signals measured through a portable setup and experimentally acquired from an LTE BS mast covering multiple cells.

IDFT-VFDM for Supplementary Uplink and LTE-NR Co-Existence

During the first phase of the deployment of new radio (NR) networks, base station (BS) and user equipment (UE) are expected to operate alongside the pre-existing long-term evolution (LTE) networks. This paper proposes a solution to be adopted by NR UE to perform an uplink transmission towards NR BS over the same time and frequency resources as the legacy LTE system, which would extend the uplink coverage when operating at the supplementary uplink band. In order to guarantee the absence of interference towards LTE BS, we design a new waveform termed as inverse discrete Fourier transform-based Vandermonde-subspace frequency division multiplexing (IDFT-VFDM) with the following important features. On one hand, an NR UE communicating with an NR BS through IDFT-VFDM would not generate any interference at the legacy LTE BS, regardless of the number of antennas present at both ends of the interference channel. On the other hand, an IDFT-VFDM signal can always be designed to occupy the same signal bandwidth as a legacy single-carrier frequency division multiple access signal for LTE uplink transmission. Numerical results demonstrate the merit of IDFT-VFDM and confirm its potential as a candidate solution to achieve LTE-NR co-existence in multi-antenna multi-user scenarios.

An Efficient Neural Network-Based Prediction Scheme for Heterogeneous Networks

In mobile wireless networks, the challenge of providing full mobility without affecting the quality of service (QoS) is becoming essential. These challenges can be overcome using handover prediction. The process of determining the next station which mobile user desires to transfer its data connection can be termed as handover prediction. A new proposed prediction scheme is presented in this article dependent on scanning all signal quality between the mobile user and all neighboring stations in the surrounding areas. Additionally, the proposed scheme efficiency is enhanced essentially for minimizing the redundant handover (unnecessary handovers) numbers. Both WLAN and long term evolution (LTE) networks are used in the proposed scheme which is evaluated using various scenarios with several numbers and locations of mobile users and with different numbers and locations of WLAN access point and LTE base station, all randomly. The proposed prediction scheme achieves a success rate of up to 99% in several scenarios consistent with LTE-WLAN architecture. To understand the network characteristics for enhancing efficiency and increasing the handover successful percentage especially with mobile station high speeds, a neural network model is used. Using the trained network, it can predict the next target station for heterogeneous network handover points. The proposed neural network-based scheme added a significant improvement in the accuracy ratio compared to the existing schemes using only the received signal strength (RSS) as a parameter in predicting the next station. It achieves a remarkable improvement in successful percentage ratio up to 5% compared with using only RSS.

An Accuracy and Real-Time Commercial Localization System in LTE Networks

In this paper, an ARTLoc (accuracy and real-time commercial localization) system is proposed, which is applicable for positioning the Minimization of Drive-Tests(MDT) data in the long-term-evolution(LTE) cellular communication network system. This system utilizes a collaborative filtering algorithm to ensure the robustness and accuracy of the fingerprint database when both base station position and GPS MDT data are abnormal in commercial communication service provider(CSP) MDT localization scene. Then, a fast matching KNN algorithm including coarse matching and fine matching is proposed to improve the location efficiency and reduce the location cost under the premise of ensuring high location accuracy. The results of experiments conducted in an in-service LTE network using more than 1000 LTE base station demonstrate that the proposed technique yields a location accuracy of 65.7 meters(@67%) with DT data and 62.1 meters(@67%) with massive GPS MDT data(over 10 million), which provides at least 184.2% and 145.2% enhancement in accuracy respectively compared to the traditional technology. In addition, our system provides a more than 7 times improvement in location efficiency compared to traditional technology. This proposed localization technique is applicable in network optimization and Operation and Maintenance(O&M) to assist CSP to reduce their operating expense(OPEX) by positioning those MDT data without GPS location.

Feasibility Analysis of LTE-Based UAS Navigation in Deep Urban Areas and DSRC Augmentation.

The current autonomous navigation of unmanned aircraft systems (UAS) heavily depends on Global Navigation Satellite Systems (GNSS). However, in challenging environments, such as deep urban areas, GNSS signals can be easily interrupted, so that UAS may lose navigation capability at any instant. For urban positioning and navigation, Long Term Evolution (LTE) has been considered a promising signal of opportunity due to its dense network in urban areas, and there has recently been great advancement in LTE positioning technology. However, the current LTE positioning accuracy is found to be insufficient for safe UAS navigation in deep urban areas. This paper evaluates the positioning performance of the current network of LTE base stations in a selected deep urban area and investigates the effectiveness of LTE augmentations using dedicated short range communication (DSRC) transceivers through the optimization of the ground LTE/DSRC network and cooperative positioning among UAS. The analysis results based on simulation using an urban canyon model and signal line of sight propagations show that the addition of four or five DSRC transceivers to the existing LTE base station network could provide better than 4–6 m horizontal positioning accuracy (95%) in the selected urban canyon at a position of 150 ft above the ground, while a dense LTE network alone may result in a 15–20 m horizontal positioning error. Additionally, the simulation results of cooperative positioning with inter-UAS ranging measurements in the DSRC augmented LTE network were shown to provide horizontal positioning accuracy better than 1 m in most flight space, assuming negligible time-synchronization errors in inter-UAS ranging measurements.

Wideband Dual-Polarized Multiple Beam-Forming Antenna Arrays

Wideband multibeam antenna arrays based on three-beam Butler matrices are presented in this paper. The proposed beam-forming arrays are particularly suited to increasing the capacity of 4G long-term evolution (LTE) base stations. Although dual-polarized arrays are widely used in LTE base stations, analog beam-forming arrays have not been realized before, due to the huge challenge of achieving wide operating bandwidth and stable array patterns. To tackle these problems, for the first time, we present a novel wideband multiple beam-forming antenna array based on Butler matrices. The described beam-forming networks produce three beams but the methods are applicable to larger networks. The essential part of the beam-forming array is a wideband three-beam Butler matrix, which comprises quadrature couplers and fixed wideband phase shifters. Wideband quadrature and phase shifters are developed using striplines, which provide the required power levels and phase differences at the outputs. To achieve the correct beamwidth and to obtain the required level of crossover between adjacent beams, beam-forming networks consisting of augmented three-beam Butler matrices using power dividers are presented to expand the number of output ports from three to five or six. Dual-polarized, three-beam antenna arrays with five and six elements covering LTE band are developed. Prototypes comprising beam-forming networks and arrays are tested according to LTE base station specification. The test results show close agreement with the simulation ones and compliance with LTE requirements. The designs presented are applicable to a wide range of wideband multibeam arrays.

Throughput and Delay Analysis of LWA With Bursty Traffic and Randomized Flow Splitting

We investigate the effect of bursty traffic in a long term evolution (LTE) and Wi-Fi aggregation (LWA)-enabled network. The LTE base station routes packets of the same IP flow through the LTE and Wi-Fi links independently. We motivate the use of superposition coding at the LWA-mode Wi-Fi access point (AP) so that it can serve LWA users and Wi-Fi users simultaneously. A random access protocol is applied in such system, which allows the native-mode AP to access the channel with probabilities that depend on the queue size of the LWA-mode AP to avoid impeding the performance of the LWA-enabled network. We analyze the throughput of the native Wi-Fi network and the delay experienced by the LWA users, accounting for the native-mode AP access probability, the traffic flow splitting between LTE and Wi-Fi, and the operating mode of the LWA user with both LTE and Wi-Fi interfaces. Our results show some fundamental tradeoffs in the throughput and delay behavior of LWA-enabled networks, which provide meaningful insight into the operation of such aggregated systems.

LWA Rate Adaption by Enhanced Event-Triggered Reporting

Unlicensed spectrum has been utilized to open up additional capacity to support long-term evolution (LTE) service. LTE and wireless local area network (WLAN) Aggregation (LWA) is a perfect solution that satisfies this need. In 2017, Taiwan has deployed the first commercial LWA service. The deployed LWA network reuses and is nicely merged with the existing individual LTE and WLAN networks. To provide appropriate WLAN transmission bandwidth, the user equipment periodically measures the WLAN quality and reports the results to the eNB (the LTE base station). The eNB then decides if the transmission rate should be adapted. We investigate the performance of periodical reporting and then propose the enhanced event-triggered reporting to improve the performance of WLAN transmission rate adaption. We suggest how to select appropriate frequency to minimize the network traffic of periodical reporting. We also show that enhanced event-triggered reporting outperforms periodical reporting. Our solution utilizes the standard 3GPP protocols and does not modify the mobile phone's software.

Hybrid power supply solutions for off-grid green wireless networks

ABSTRACTIncreasing deployment of cellular networks across the globe is pushing the energy consumption in cellular networks at an exceptional rate. The integration of renewable energy (RE) harvesting technology into future mobile networks has the potential to positively cope with environmental contamination and ensure self-energy sustainability as a means to decrease fossil fuel consumption. Diesel generator (DG) in conjunction with on-site RE harvester has emerged as an economic and extent efficient option where commercial grid supply is not viable. This paper is focused on the cost aware energy management framework addressing to least net present cost (NPC) for the envisioned hybrid powered green cellular base stations (BSs) considering tempo-spatial traffic dynamics. In such wireless networks, solar photovoltaic modules are considered as a primary energy source, while the DG and energy storage device are kept as the standby supply in case of inadequate solar energy to ensure zero outage. A comprehensive simulation-based investigation is carried out in the context of downlink Long-Term Evolution (LTE) cellular networks for evaluating cost-efficiency and reliability performance under a wide range of network settings. Particularly, this paper examines the energy yield, greenhouse gas emissions, and cost analysis based on the optimal architecture of Remote Radio Head-enabled LTE BS. Moreover, wireless network performance in terms of throughput, energy efficiency gain, and radio efficiency is thoroughly investigated using Monte Carlo simulations. Numerical results demonstrate a substantial reduction of carbon footprints with minimum NPC while satisfying the quality of service requirements.

Self-Tuning of Service Priority Parameters for Optimizing Quality of Experience in LTE

Rising user expectations are changing the way mobile operators manage their networks. In this paper, a self-tuning algorithm for adjusting parameters in a multiservice packet scheduler of a Long-Term Evolution base station is proposed to optimize the overall system Quality of Experience (QoE) based on network performance statistics. For this purpose, the algorithm iteratively changes service priority parameters to reprioritize services so as to make the most of available resources. The proposed algorithm ensures that the best overall system QoE is always reached by analyzing optimality conditions, unlike previous works, which only guarantee a minimum user satisfaction level or aim to balance QoE among services. Method assessment is carried out with a dynamic system-level simulator in a realistic service scenario. Simulation results show that the overall network QoE can be improved up to $35\%$ by tuning service priority parameters.

Performance Analysis of Uplink Scheduling Algorithms in LTE Networks

Scheduling is referring to the process of allocating resources to User Equipment based on scheduling algorithms that is located at the LTE base station. Various algorithms have been proposed as the execution of scheduling algorithm, which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of three well-known uplink schedulers namely, Maximum Throughput (MT), First Maximum Expansion (FME), and Round Robin (RR). The evaluation is considered for a single cell with interference for three flows such as Best effort, Video and VoIP in a pedestrian environment using the LTE-SIM network simulator. The performance evaluation is conducted in terms of system throughput, fairness index, delay and packet loss ratio (PLR). The simulations results show that RR algorithm always reaches the lowest PLR, delivering highest throughput for video and VoIP flows among all those strategies. Thus, RR is the most suitable scheduling algorithm for VoIP and video flows while MT and FME is appropriate for BE flows in LTE networks.

RACH Session Initiation Procedure with Retranslations

Due to the rapidly growing number of user’s equipments, operating in the LTE (Long-Term Evolution) mobile radio network, it became necessary to find methods to reduce the user load and signaling message’s traffic. New rules and procedures of devices communication are created to downsize network resources. This article explores the procedure for establishing a connection between mobile user’s equipment and the LTE base station. Such possible solution of transferring small data generated by machine-to-machine connections (M2M, Machine-to-Machine) was presented in the technical report TR 37.868 of the 3GPP consortium (3rd Generation Partnership Project). This approach implies the use of the random access channel (RACH) to interconnect between devices. Effective usage of the procedure for establishing a connection through a random access radio channel is based on the analysis of time-probability characteristics, such as the access success probability and failed access probability, average access delay. In this article we proposed analytical model in term of Markov chain to find these characteristics and present numerical analysis, considering collisions of preamble message, retransmissions of signalling messages and the boundary conditions on the number of possible retransmissions. The accuracy of the proposed analytical model was verified using programming environment R.