Tx-Rx Distance Research Articles

Measurement of distance and speed between transmitter and receiver using the propagation time of underwater acoustic communication signals with orthogonal signal division multiplexing

This paper proposes a procedure for measuring transmitter–receiver (Tx–Rx) distance using acoustic communication signals to realize communication and positioning underwater with the same signal and device. Specifically, we focus on an underwater acoustic communication using orthogonal signal division multiplexing, where a pilot signal and messages are placed in the time–frequency domain. In this paper, we show that measurements of both Tx–Rx distance and speed are available by utilizing the pilot signal. We conducted a sea trial and evaluated the performance of the proposed method. During the experiment, the Tx–Rx distance was 50–550 m. The obtained results suggest that the proposed method can measure the Tx–Rx distance and speed in a specific environment. The mean absolute error and the standard deviation error of ranging are 4.0 and 2.7 m, respectively, while those of measurement speed are 0.13 and 0.22 m s−1, respectively.

Enhanced-efficiency Capacitive Coupling Intra-body Power Transfer Systems with 1.8 V Output for Neural Interfaces.

Traditional wireless power transfer methods for powering neural interfaces have many restrictions such as short transmission distance and strict device alignment. The recently proposed capacitive coupling intra-body power transfer (CC-IBPT) which utilizes human body as the medium supports flexible placements of the transmitter electrode. In this paper, we established two prototype systems based on CC-IBPT with different power sources of a grounded signal generator and a battery-powered board to explore the maximum output power levels with 1.8 V load voltage. To improve the power transmission efficiency, LC impedance matching (IM) and backward compensation (BC) are conducted at the transmitter (TX) and receiver (RX) respectively. Measured results show that 2.5 and 7.4 times load power is enhanced in the two prototype systems. Moreover, the maximum power transfer efficiency (PTE) of 11.16% can be obtained with the TX-RX distance of 16 cm. Therefore, our work verifies CC-IBPT's capability of achieving a high PTE in long-distance wireless power supply for neural interfaces and promotes its widespread application.

Numerical and Experimental Characterization of LoRa-Based Helmet-to-Unmanned Aerial Vehicle Links on Flat Lands: A numerical-statistical approach to link modeling

The use of the LoRa communication protocol in a new generation of transceivers is attractive for search and rescue(SaR) procedures because they can operate in harsh environmentscovering vast areas while maintaining a low power consumption.The possibility of wearing helmets equipped with LoRa-radiosand installing LoRa transceivers in unmanned aerial vehicles (UAVs) will accelerate the localization of the targets, probably unconscious. In this paper, the achievable communication ranges of such links are theoretically and experimentally evaluated by considering the possible positions of the helmet wearer (standing or lying) on a flat field, representing a simple SaR scenario.Simulations and experimental tests demonstrated that, for the standing position, the ground-bounce multi-path produces strong fluctuations of the received power versus the Tx-Rx distances. Such fluctuations can be kept confined within 100 m from the target by lowering the UAV altitude. Instead, for a more critical lying position, the received power profile is monotonic and nearly insensitive to the posture. For all the considered cases, the signal emitted by the body-worn transceiver can be exploited to localize the helmet wearer based on its strength, and it is theoretically detectable by the UAV radio up to 5 km on flat terrain.

Experimental Investigation of Body-Centric Indoor Localization Using Compact Wearable Antennas and Machine Learning Algorithms

A simple and effective body-centric localization algorithm has been proposed in this article using ultra-wideband (UWB) wearable technology. The algorithm has been validated through measurement campaigns with a human subject volunteer in an indoor environment. The algorithm takes into account statistical channel parameter analysis, machine learning (ML) algorithms, and time-of-arrival (TOA)-based range estimation/data fusion techniques. Two channel parameters namely path loss magnitude and rms delay spread are proposed as classification features to be applied to the ML algorithm to accurately classify the off-body channel links into LOS, PNLOS, and NLOS scenarios. Multiclass support vector machine (MC-SVM) classifier along with SMOTE algorithm to take into account class imbalance is applied with the channel classification accuracy of 98.63%. Threshold-based range estimation algorithms are applied in order to mitigate NLOS scenarios caused mainly due to the presence of the human subject. Results report human localization accuracy in 0.5–3 cm range using TDOA data fusion technique for target estimation. Further validation is presented considering wide range of Tx–Rx distance, presence of another obstruction between the Tx and Rx links, and performance in different environment which shows the suitability of the proposed methodology.

On-Body UWB Channel Classification and Characterization for Various Physical Exercises

This paper presents classification, characterization and modelling of ultra-wideband (UWB) on-body channel links while performing various physical exercises. The physical exercises mainly focus on range-of-motion exercises in which the upper and lower limb movement is dominant. Such exercises are suitable for various applications in medical domain such as rehabilitation, physiotherapy, in sports for training and general-well-being. Wrist and ankle regions have been chosen for the wearable antenna placement and three different antenna orientations have been considered with respect to the location on the limb, inner, outer, and front region. The channel for various activities has been classified into line of sight (LOS) and non-line of sight (NLOS) links based on computation of Kurtosis. On-body statistical analysis and distance-dependent study is performed on two important channel parameters, path loss magnitude and rms delay spread considering the LOS and NLOS links. The channel variation is attributed to the location/orientation of the antenna, Tx-Rx distance, obstruction caused by the human body and different categories of activities.

LTE massive MIMO (Pre-5G) test with an updated boat user terminal solution for land-to-boat scenarios in Oslo fjord

Autonomous shipping is considered to be one of the most important technologies in the maritime industry. Remote control of autonomous shipping is supported by communication solutions featuring long coverage, high throughput and low latency. Since 2018, together with the Norwegian Internet Service Provider (ISP) Telia, we have performed tests with a massive MIMO (Pre-5G) LTE base station, using the 3.7 GHz band, in Horten close to the Oslo fjord. The first Pre-5G tests with user terminal mounted on a 40 feet sailboat performed in 2018, showed great potential for maritime applications in terms of throughputs [1]. The Customer Premise Equipment (CPE) used in 2018 was a LTE Pre-5G terminal from Telia for fixed LAN use, and a modified version of it in 2019. However, since both the base station and the user terminal/CPE are not originally designed and optimized for maritime radio propagation environments, the test results in 2018 unveiled that a CPE designed for land usage experienced limited coverage and instability caused by received unstable signal level. Since 2019, a new user terminal prototype dedicated and optimized for maritime propagation conditions, was designed by Super Radio AS. This new CPE was tested in autumn 2019 under the similar setups as in 2018. The test results of the Reference Signal Receive Power and throughput are analysed and compared the test results in 2018. The comparison proved that the new user terminal solution showed considerable improvement with respect to stability and throughputs in the harsh maritime environments, which means that the new designed solution can be a potential maritime terminal solution for the remote control of autonomous shipping. The prototypes mounted at different places of the sailboat also show different system performances at the same TX-RX distances, which indicates the potential of exploiting the system diversity in the similar propagation environments.

Understanding Sub-GHz Signal Behavior in Deep-Indoor Scenarios

Critical Internet-of-Things (IoT) services require seamless connectivity, which is not always simple to provide and particularly in deep-indoor scenarios, it can be even impossible in some cases. The existing outdoor-to-indoor path-loss models lack accuracy in underground situations, thus IoT coverage planning in such areas cannot rely on robust tools and becomes a process of trial and error. In this work, we derive and analyze various environmental features that can be useful in understanding sub-GHz deep-indoor signal propagation. Based on a large-scale field trial in an underground tunnel system, we formulate several parameters related to the TX-RX distance and tunnel geometry. Through feature relevance studies in linear (ordinary least-squares (OLS) regression) and nonlinear (the Gaussian process regression) realms, we show that 2-D indoor distance and the distances to the tunnel walls may be useful in sub-GHz signal strength prediction in deep-indoor situations. We construct a linear and a Gaussian process model for the indoor path-loss prediction that outperforms the 3rd Generation Partnership Project (3GPP) model by 1.8 and 4.1 dB, respectively.

An Underwater Acoustic Channel Modeling for Internet of Things Networks

Interest in wideband and medium distance underwater acoustic communication systems is increasing due to the practical application of underwater Internet of Things (IoT) networks. In this paper, we propose a simplified empirical channel model for the medium distance underwater acoustic channels based on real measurement results. The simple and tractable channel model is critical for the development of advanced underwater communications technology. The underwater channel measurements were performed at 20 m sea water depth, the transmitters (TXs) were located at 5 m and 15 m from the bottom, the receivers (RXs) were located at 4 m, 8 m, 12 m, and 16 m from the bottom, and the TX–RX distances were 21 m, 71 m, 127 m, and 273 m. We derived the path loss from the measured dataset, and modified the log-distance model to create a model suitable for an underwater IoT channel. Numerical results show that the proposed model is accurate and reliable enough to use in the development of advanced underwater communication technologies.

Characterization of Field of View in Visible Light Communication Systems for Intelligent Transportation Systems

This paper reports a detailed experimental characterization of non Line-of-Sight (LoS) optical performances of a Visible Light Communication (VLC) system using a real traffic light for ultra-low latency, infrastructure-to-vehicle (I2V) communications for intelligent transportation systems (ITS) protocols. Despite the implementation of long-sought ITS protocols poses the crucial need to detail how the features of optical stages influence the overall performances of a VLC system in realistic configurations, such characterization has rarely been addressed at present. We carried out an experimental investigation in a realistic configuration where a regular traffic light (TX), enabled for VLC transmission, sends digital information towards a receiving stage (RX), composed by an optical condenser and a dedicated amplified photodiode stage. We performed a detailed measurements campaign of VLC performances encompassing a broad set of optical condensers, and for TX-RX distances in the range 3-50 m, in terms of both effective Field of View (EFOV) and Packet Error Rate (PER). The results show several angle-dependent nontrivial behaviors for different lens sets as a function of position on the measurement grid, highlighting critical aspects for ITS applications as well as identifying most suitable optical configurations depending on the specific application and on the required EFOV. We also provide a theoretical model for both the signal intensity and the EFOV as a function of several parameters, such as distance, RX orientation and focal length of the specific condenser. To our best knowledge, there are no optical and EFOV experimental analyses for VLC systems in ITS applications in literature. Our results could be very relevant in the near future to assess a most suited solution in terms of acceptance angle when designing a VLC system for real applications, where angle-dependent misalignment effects play a non-negligible role, and we argue that they could have more general implications with respect to the pristine I2V case mentioned here.

A Big Data Enabled Channel Model for 5G Wireless Communication Systems

The standardization process of the fifth generation (5G) wireless communications has recently been accelerated and the first commercial 5G services would be provided as early as in 2018. The increasing of enormous smartphones, new complex scenarios, large frequency bands, massive antenna elements, and dense small cells will generate big datasets and bring 5G communications to the era of big data. This paper investigates various applications of big data analytics, especially machine learning algorithms in wireless communications and channel modeling. We propose a big data and machine learning enabled wireless channel model framework. The proposed channel model is based on artificial neural networks (ANNs), including feed-forward neural network (FNN) and radial basis function neural network (RBF-NN). The input parameters are transmitter (Tx) and receiver (Rx) coordinates, Tx-Rx distance, and carrier frequency, while the output parameters are channel statistical properties, including the received power, root mean square (RMS) delay spread (DS), and RMS angle spreads (ASs). Datasets used to train and test the ANNs are collected from both real channel measurements and a geometry based stochastic model (GBSM). Simulation results show good performance and indicate that machine learning algorithms can be powerful analytical tools for future measurement-based wireless channel modeling.

A Model-Based RF Hand Motion Detection System for Shadowing Scenarios

With the explosive growth of mobile computing, new modes of human-computer interaction (HCI) are emerging and becoming feasible. Compared to vision-based systems that require lighting, radio frequency (RF)-based hand motion detection systems are becoming more popular in HCI applications. In real RF hand motion detection scenarios, the line-of-sight between the transmitter (Tx) and receiver (Rx) is usually blocked. Hence, shadowing significantly affects the detection accuracy. To design better RF hand motion detection systems, we propose a simple diffraction and interference model (DIM) to interpret the received signal strength (RSS) variation caused by hand motions in the shadowing scenario. Based on theories of knife-edge diffraction and mutual radio interference, DIM provides a simple theoretical foundation for analyzing the RSS variation with hand size, signal frequency, and Tx-Rx distance. Furthermore, a model-based RF hand motion detection system benefiting from DIM is presented. Unlike existing systems that require a large number of motion features to train a motion classifier, the model-based system achieves training-free motion classification, which has potential for hand motion detection on a real-time basis. Empirical data collected from a vector network analyzer validate our system as well as demonstrate a simple diffraction model can help hand motion detection processing for commonly growing HCI applications.

LTE massive MIMO (Pre-5G) test for land-to-boat scenarios in Oslo fjord

In this paper, a 3-day Pre-5G LTE test campaign was performed in Oslo fjord. A detailed description of the LTE test campaign including base station radio coverage, route design, Customer Premises Equipment (CPE) placement, weather conditions and other related info is given. The measured data were analysed according to LOS and NLOS scenarios. For the LOS Scenario, the averaged Received Signal strengths (RSS) vary along the routes from -55 dBm to -85 dBm (about 30 dB), while the averaged standard deviations change from 2 dB to 7 dB. It is also found that most of the cross-covariance between the signal strength obtained in the front CPE and the rear CPE is less than 0.7 with the antenna separation of 10-meter on the sail boat, which suggests a potential for multi-user diversity in the similar radio propagation environments. For the NLOS scenario, it can be found that some of the RSS results are less than 80 dBm, and partly the radio link was lost (no recording), which limits the corresponding conclusion. The RSS was found to be between -80 dBm and -100 dBm at the TX-RX distances up to 27 km, which shows the potential of a long coverage up to 27 km at 3.7 GHz by using the pre-5G solutions for the maritime applications.

Comparing WiFi RSS Filtering for Wireless Robot Location System

Abstract Wireless infrastructure such as WiFi gained wide interest by researchers and private companies to determine the location of a target object in a building. Hence, we observe an increase in popularity of in building WiFi solutions. However, significant fluctuations in WiFi signal strength are affecting the measurement quality and as a result the fingerprinting positioning approach. The accuracy of the positioning will be improved if the RSS measured at different distances between transmitter (Tx) to receiver (Rx) is distinctly different. Several filtering methods may be applied to reduce the data noise for estimating. Many methods demonstrate great noise reduction. The time taken to compute data becomes limited to mobile robot application since real-time is required. The requirement for real time data singles out mobile robot application as an effective solution. In this paper, the focus will be on the difference of RSS measurements with varying Tx-Rx distances, following the design of experiment (DoE). Further we include a comparison between the Kalman filtering and weight fusion, which is Weight-Average of the Top-n Populated values model (WATP). Errors in estimation and reduction in computation time are taken into consideration.

Line-of-Sight Massive MIMO Channel Characteristics in an Indoor Scenario at 94 GHz

The fading and correlation characteristics of virtual, yet realistic, line-of-sight (LOS) $4\times 2500$ millimetric (mmW) massive MIMO channels are investigated at 94 GHz in an indoor office environment for three different Tx–Rx distance scenarios. The capability of the mmW massive MIMO channel to spatially decorrelate the users is evaluated with the computation of the channel correlation and other channel metrics, such as power-to-interference ratio and condition number. In particular, the correlation between channel vectors for a given user and its influence on receiving correlation is discussed. The results clearly demonstrate the capability of mmW massive MIMO systems to reach orthogonal Tx–Rx streams even for a small $7\times 7$ antenna array subset with correlation between users <0.2. Moreover, strong phase variations at Tx side at this frequency range are highlighted through channel phase correlation studies and were shown to contribute to the decorrelation at Rx side between close users, paving the way for further massive MIMO system enhancements.

Analog Eigenmode Transmission for Short-Range MIMO Based on Orbital Angular Momentum

This paper proposes an analog eigenmode transmission technique suitable for a short-range multiple-input multiple-output (SR-MIMO) system consisting of arbitrary power-of-two number of antennas utilizing the idea of orbital angular momentum. In the proposed technique, uniform circular arrays that are coaxially arranged are used at both the transmitting (Tx) and receiving (Rx) sides. With this array configuration, the channel matrix is always a circulant matrix regardless of antenna type, array radius, Tx–Rx distance, and rotation about the coaxis. Due to the characteristics of a circulant matrix, the channel matrix can be diagonalized independently of the above-mentioned factors by fixed-weight beamforming based on a discrete Fourier transform (DFT) matrix uniquely determined by just the number of antennas. In this paper, the operating principle of the proposed technique is discussed from the viewpoints of linear algebra, and some example network configurations are presented with the determination of the DFT-matrix weight. Numerical analyses confirm the two important features of the proposed technique: 1) support of more than $4\times 4$ SR-MIMO and 2) independence with regard to rotation about the coaxis. Furthermore, an experiment on a fabricated DFT circuit confirmed the feasibility of the proposed technique in realizing practical short-range communication.

A Wideband Dual-Antenna Receiver for Wireless Recording From Animals Behaving in Large Arenas

A low-noise wideband receiver (Rx) is presented for a multichannel wireless implantable neural recording (WINeR) system that utilizes time-division multiplexing of pulse width modulated (PWM) samples. The WINeR-6 Rx consists of four parts: 1) RF front end; 2) signal conditioning; 3) analog output (AO); and 4) field-programmable gate array (FPGA) back end. The RF front end receives RF-modulated neural signals in the 403-490MHz band with a wide bandwidth of 18MHz. The frequency-shift keying (FSK) PWM demodulator in the FPGA is a time-to-digital converter with 304ps resolution, which converts the analog pulse width information to 16-bit digital samples. Automated frequency tracking has been implemented in the Rx to lock onto the free-running voltage-controlled oscillator in the transmitter (Tx). Two antennas and two parallel RF paths are used to increase the wireless coverage area. BCI-2000 graphical user interface has been adopted and modified to acquire, visualize, and record the recovered neural signals in real time. The AO module picks three demultiplexed channels and converts them into analog signals for direct observation on an oscilloscope. One of these signals is further amplified to generate an audio output, offering users the ability to listen to ongoing neural activity. Bench-top testing of the Rx performance with a 32-channel WINeR-6 Tx showed that the input referred noise of the entire system at a Tx-Rx distance of 1.5m was 4.58μV rms with 8-bit resolution at 640 kSps. In an in vivo experiment, location-specific receptive fields of hippocampal place cells were mapped during a behavioral experiment in which a rat completed 40 laps in a large circular track. Results were compared against those acquired from the same animal and the same set of electrodes by a commercial hardwired recording system to validate the wirelessly recorded signals.

A Novel Impedance Matching Topology for Magnetically Coupled Wireless Power Transfer

A modified 4-coil magnetic resonance wireless power transfer (MRWPT) system is proposed. Four coils based on 2-coil system with additional two matching coils were used in this topology. When Tx-Rx distance is changed, the input impedance is changed. However, it can be adjusted by coil parameters of matching coils to maintain impedance matching for maximum efficiency. The equivalent circuit of MRWPT system was analyzed for both transmission function and optimum coupling coefficient of the matching coils. By using four spiral resonant coils, these design considerations was experimentally verified. The measured data agreed well with the calculated data and the transmission function of the proposed system was more efficient than that of conventional 2-coil system.

Propagation Characteristics of Dense Multipath Components

The dense multipath components (DMC) represent the part of the radio channel that cannot be characterized by a superposition of distinct plane waves, i.e., the specular components (SC). In this letter, the propagation characteristics of the DMC are analyzed in indoor environments from two perspectives. First, the proportion of DMC in the total power is studied as a function of the distance between the transmitter (TX) and receiver (RX). Second, the characteristics of the DMC and SC are compared in angular and delay domains. The measurement results show that the amount of DMC in the total power increases as the TX-RX distance increases in both line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. In addition, it is shown that the power of the DMC is concentrated around the same angles and delays as the SC.

Scaling laws of single-hop cognitive networks

We consider a cognitive network consisting of n cognitive users uniformly distributed with constant density among primary users. Each user has a single transmitter and a single receiver, and the primary and cognitive users transmit concurrently. The cognitive users use single-hop transmission in two scenarios: (i) with constant transmit power, and (ii) with transmit power scaled according to the distance to a designated primary transmitter. We show that, in both cases, the cognitive users can achieve a throughput scaled linearly with the number of users n. The first scenario requires the cognitive users to have the transmitter-receiver (Tx-Rx) distance bounded, but it can be arbitrarily large. Then with high probability, any network realization has the throughput scaling linearly with n. The second scenario allows the cognitive Tx-Rx distance to grow with the network at a feasible exponent as a function of the path loss and the power scaling factors. In this case, the average network throughput grows at least linearly with n and at most as n log(n). These results suggest that single-hop transmission may be a suitable choice for cognitive transmission.

Ground penetrating radar antennas: theoretical and experimental directivity functions

The prediction of the directivity function of a GPR antenna still remains a partially unsolved problem because of the subject complexity. First, the far-field conditions are often not satisfied and second, the antenna design has little in common with the Hertzian dipole for which an analytical approach can be used. The authors' contribution is both theoretical and experimental. On one side, they solve the (electromagnetic) EM integral equations numerically to derive the wavefield components from near to far-field distances. On the other side, they experiment with two novel techniques for measuring the directivity functions in the near to far-field range on dry and saturated sand. Theoretical and experimental results show that neither the analytic approximation of far-field directivity for the numerical integration of near-field directivity can perfectly match the measured functions, although near-field solutions are generally more consistent. The mismatch should be attributed to the present-day GPR antenna design that includes absorbers and shields. Although the effects of these elements are not included in the present numerical near-field solutions, they believe the approach to be of practical value to predict an average directivity function. A smoothed version of the analytic far-field solution can also be used in the range of the near to far-field transition but near-field solutions are really recommended when TX-RX distances are shorter than five wavelengths.