Channel Impulse Response Measurements Research Articles

Identification of Solid and Liquid Materials Using Acoustic Signals and Frequency-Graph Features.

Material identification is playing an increasingly important role in various sectors such as industry, petrochemical, mining, and in our daily lives. In recent years, material identification has been utilized for security checks, waste sorting, etc. However, current methods for identifying materials require direct contact with the target and specialized equipment that can be costly, bulky, and not easily portable. Past proposals for addressing this limitation relied on non-contact material identification methods, such as Wi-Fi-based and radar-based material identification methods, which can identify materials with high accuracy without physical contact; however, they are not easily integrated into portable devices. This paper introduces a novel non-contact material identification based on acoustic signals. Different from previous work, our design leverages the built-in microphone and speaker of smartphones as the transceiver to identify target materials. The fundamental idea of our design is that acoustic signals, when propagated through different materials, reach the receiver via multiple paths, producing distinct multipath profiles. These profiles can serve as fingerprints for material identification. We captured and extracted them using acoustic signals, calculated channel impulse response (CIR) measurements, and then extracted image features from the time-frequency domain feature graphs, including histogram of oriented gradient (HOG) and gray-level co-occurrence matrix (GLCM) image features. Furthermore, we adopted the error-correcting output code (ECOC) learning method combined with the majority voting method to identify target materials. We built a prototype for this paper using three mobile phones based on the Android platform. The results from three different solid and liquid materials in varied multipath environments reveal that our design can achieve average identification accuracies of 90% and 97%.

Joint Optimization of OFDM and Channel Coding for URLLC in Industrial Channels

Industrial communications have very tight requirements of reliability and latency, which are challenging to achieve at highly dynamic industrial radio channels. Redundancy in the modulation and coding can improve reliability but incurs excess latency. Minimizing latency subject to reliability constraint for a given channel state opens up the scope for static and runtime optimization. In this paper we explore joint optimal configuration of Orthogonal Frequency Division Multiplexing (OFDM) and channel coding, using polar, Low Density Parity Check (LDPC) and convolutional codes to minimize the transmission time subject to a maximum acceptable packet error rate, for three realistic channels reported by National Institute of Standards and Technology, using channel impulse response measurements, as well as perfect and imperfect channel estimation. The results show that the use of strong channel codes can significantly reduce transmission time, by up to 24% compared to convolutional codes, with LDPC achieving fastest transmission. For transmission times of 10-20 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> s the contribution of the Cyclic Prefix (CP) is significant, up to 30% for convolutional codes. Stronger channel codes allow reduced CP, even considering the added redundancy such as Cyclic Redundancy Check (CRC), resulting in overall lower transmission time. The decoding time also introduces significant overheads, up to 50% of transmission time for polar codes. The paper also investigates the impact of channel estimation errors, which adversely impact Ultra-Reliable Low-Latency performance: lower bound errors violate the reliability constraint and higher bound errors introduce excess transmission times.

Radio Channel Measurements and Characterization in Substation Scenarios for Power Grid Internet of Things

Wireless communication technologies play a key role to support the implementation of power grid Internet of Things (PIoT). An in-depth knowledge of the radio channel is vital to the application of wireless communication technologies in PIoT. This paper investigates the radio channel measurements and characterization for PIoT substation scenarios. A novel channel sounder is designed for achieving omnidirectional measurements and phased array antennas based directional measurements, and a directional multipath components extraction algorithm is proposed. The channel sounding system is verified and is used to perform a series of 3.35 GHz omnidirectional and directional channel measurements in four substation scenarios, involving a 10 kV switch room, a 110 kV GIS room, a semi-indoor 110 kV substation and an outdoor 220 kV substation. Based on the measured channel impulse responses data, both large-scale and small-scale fading characteristics of substation channels are extracted and analyzed. Empirical models of path loss, shadow fading, Ricean K-factor and root-mean-square (RMS) delay spread are proposed. In addition, results of RMS angle spread of departure and RMS angle spread of arrival are presented. These results will provide useful reference for the deployment and optimization of wireless communication networks in PIoT substation scenarios.

Ionospheric Channel Impulse Response Measurement between Pameungpeuk and Bandung, Indonesia

Ionospheric Channel Impulse Response Measurement between Pameungpeuk and Bandung, Indonesia

3GPP-Compatible Channel Generation Framework for FR2-2 Indoor Short-Range Communication

This study proposes a 3GPP-compatible channel generation framework for ultra-wideband and indoor shortrange communication realized by the fifth-generation (5G) new radio operating in the frequency range (FR) of 52.6-71.0 GHz. The addition of this band, coined “FR2-2”, to the 5G specification allows foreseeing the use cases of shorter-range communications with ultra-wide bandwidth. However, the current focus of the 3GPP channel model on longer-range communication hinders link-level simulations of this use case. To fill this void, we develop a channel generation framework compatible with the 3GPP channel model and applicable to the FR2-2 indoor short-range use case based on real channel measurements. We highlight that even with appropriate parameters for this use case, the 3GPP channel model does not necessarily reproduce similar characteristics of the measured channel impulse response (CIR) owing to the lack of uniformity of cluster angle of arrival (AoA) and power dispersion in intra-cluster subpaths. Based on this finding, an amendment is proposed, where cluster AoA is uniformly distributed, and the intra-cluster power dispersion term is introduced. We demonstrate the feasibility of the proposed framework for reproducing the real CIR characteristic by showcasing an agreement of root-mean-square delay and angular spreads with the measured CIR.

Exploiting Ultra-Wideband Channel Impulse Responses for Device-Free Localization.

In radio-frequency (RF)-based device-free localization (DFL), the number of sensors acting as RF transmitters and receivers is crucial for accuracy and system costs. Two promising approaches for DFL have been identified in the past: radio tomographic imaging (RTI) and multi-static radar (MSR). RTI in its basic version requires many sensors for high accuracy, which increases the cost. In this paper, we show how RTI benefits from multipath propagation. By evaluating the direct and echo paths, we increase the coverage of the target area, and by utilizing UWB signals, the RTI system is less susceptible to multipath propagation. MSR maps reflections that occur within the target area to reflectors such as persons or other objects. MSR does not require that the person is located near a signal path. Both suggested methods exploit ultra-wideband (UWB) channel impulse response (CIR) measurements. CIR measurements and the modeling of multipath effects either increase the accuracy or reduce the required number of sensors for localization with RTI. We created a test setup and measure UWB CIRs at different positions with a commercially available off-the-shelf UWB radio chip, the Decawave DW1000. We compare the localization results of RTI, multipath-assisted (MA)-RTI, and MSR and investigate a combined approach. We show that RTI is improved by the analysis of multipath propagation; furthermore, MA-RTI results in a better performance compared to MSR: with 50% of all cases, the localization error is better than 0.82 m and in 80% of all cases 1.34 m. The combined approach results in the best localization result with 0.64 m in 50% of all cases.

Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization.

Ultra-Wide Bandwidth (UWB) and mm-wave radio systems can resolve specular multipath components (SMCs) from estimated channel impulse response measurements. A geometric model can describe the delays, angles-of-arrival, and angles-of-departure of these SMCs, allowing for a prediction of these channel features. For the modeling of the amplitudes of the SMCs, a data-driven approach has been proposed recently, using Gaussian Process Regression (GPR) to map and predict the SMC amplitudes. In this paper, the applicability of the proposed multipath-resolved, GPR-based channel model is analyzed by studying features of the propagation channel from a set of channel measurements. The features analyzed include the energy capture of the modeled SMCs, the number of resolvable SMCs, and the ranging information that could be extracted from the SMCs. The second contribution of the paper concerns the potential applicability of the channel model for a multipath-resolved, single-anchor positioning system. The predicted channel knowledge is used to evaluate the measurement likelihood function at candidate positions throughout the environment. It is shown that the environmental awareness created by the multipath-resolved, GPR-based channel model yields higher robustness against position estimation outliers.

Passive indoor visible light-based fall detection using neural networks

In this paper, a passive visible light sensing (VLS) fall detection system based on luminaires is proposed that uses neural networks to learn the state (i.e., upright or prone) of a target (e.g., a person). The proposed method measures the channel impulse response (CIR) between different source-receiver pairs in a passive scenario, where the user does not hold a device or sensor. The CIR measurements are collected in a realistically modeled room and neural networks are employed to learn the relationship between the CIR measurements and the states of the target at randomly selected positions in the room. The performance evaluation of the system shows that an accuracy of more than 97% is attainable by utilizing a large number of data samples and high brightness factor of the luminaires. The robustness of the proposed method is validated by using a tilted state which is labeled with same class as the upright state, however, the tilted state is not used to train the network. One of the key applications of fall detection is in healthcare domain for patient monitoring. The correct prediction of the prone state is particularly critical in such scenarios since emergency situations may arise from a fall.

Linear frequency modulation signal for channel impulse response measurement in shallow water environment

Understanding the characteristics of channel propagation plays a very important role in the design of underwater acoustic communication. Underwater acoustic channel (UAC) model is usually carried out by measuring directly at a specific location and time. This paper presents the use of Linear Frequency Modulation (LFM) signal for channel impulse response estimation and power delay profile (PDP) measurement in a shallow water environment. Measurements were made in a laboratory-scale towing tank with three variations of distance and depth. Furthermore, the measurement results are compared with the existing underwater acoustic channel model. The measurement results show that the response impulses at the three distances have almost the same pattern and the resulting amplitude is similar to the existing underwater acoustic channel model simulation. The RMS delay spread generated from the three distances has a value of about 0,2 msec. Meanwhile, the maximum excess delay obtained at a distance of 120 m has the highest value, which is 29 msec.

Analysis of Non-Stationarity for 5.9 GHz Channel in Multiple Vehicle-to-Vehicle Scenarios.

The vehicle-to-vehicle (V2V) radio channel is non-stationary due to the rapid movement of vehicles. However, the stationarity of the V2V channels is an important indicator of the V2V channel characteristics. Therefore, we analyzed the non-stationarity of V2V radio channels using the local region of stationarity (LRS). We selected seven scenarios, including three directions of travel, i.e., in the same, vertical, and opposite directions, and different speeds and environments in a similar driving direction. The power delay profile (PDP) and LRS were estimated from the measured channel impulse responses. The results show that the most important influences on the stationary times are the direction and the speed of the vehicles. The average stationary times for driving in the same direction range from 0.3207 to 1.9419 s, the average stationary times for driving in the vertical direction are 0.0359–0.1348 s, and those for driving in the opposite direction are 0.0041–0.0103 s. These results are meaningful for the analysis of the statistical characteristics of the V2V channel, such as the delay spread and Doppler spread. Small-scale fading based on the stationary times affects the quality of signals transmitted in the V2V channel, including the information transmission rate and the information error code rate.

Distributed MIMO for Li-Fi: Channel Measurements, Ray Tracing and Throughput Analysis

LiFi has been considered as a promising candidate for future wireless indoor networks. The IEEE P802.15.13 and P802.11bb standardization groups agreed upon channel models generated using the non-sequential ray tracing approach of OpticStudio. In this paper, in order to validate the channel modelling approach, at first 2×2 multiple-input multiple-output (MIMO) channel measurements are carried out over 200 MHz bandwidth using a channel sounder. The experimental scenario is also modeled in 3D by applying ray tracing. The obtained results indicate good agreement between simulations and measured channel impulse responses, from which parameters such as path loss and delay spread are derived. After validating the channel modeling approach, we investigate the singular values and the effect of user mobility onto the performance in a 4×4 distributed multi-user MIMO scenario.

MAMPI-UWB-Multipath-Assisted Device-Free Localization with Magnitude and Phase Information with UWB Transceivers.

In this paper, we propose a multipath-assisted device-free localization (DFL) system that includes magnitude and phase information (MAMPI). The DFL system employs ultra-wideband (UWB) channel impulse response (CIR) measurements, enabling the extraction of several multipath components (MPCs) and thereby benefits from multipath propagation. We propose a radio propagation model that calculates the effect on the received signal based on the position of a person within a target area. Additionally, we propose a validated error model for the measurements and explain the creation of different feature vectors and extraction of the MPCs from Decawave DW1000 CIR measurements. We evaluate the system via simulations of the position error probability and a measurement setup in an indoor scenario. We compare the performance of MAMPI to a conventional DFL system based on four sensor nodes that measures radio signal strength values. The combination of the magnitude and phase differences for the feature vectors results in a position error probability that is comparable to a conventional system but requires only two sensor nodes.

Channel impulse response‐based source localization in a diffusion‐based molecular communication system

Molecular source localization finds its applications in future healthcare systems, including proactive diagnostics. This work localizes a molecular source in a diffusion based molecular communication (DbMC) system via a minimal set of passive anchor nodes and a fusion center. Two methods are presented which both utilize (the peak of) the channel impulse response measurements to uniquely localize the source, under the assumption that the molecular source of interest lies within the open convex‐hull of the sensor/anchor nodes. The first method is a one‐shot, triangulation‐based approach which estimates the unknown location of the molecular source using least‐squares method. The second method is an iterative approach, which utilizes the gradient‐descent control law to minimize a non‐convex cost function. The corresponding Cramer‐Rao bound (CRB) is also derived. Simulation results reveal that: (a) the gradient‐descent method outperforms the triangulation method (in terms of mean squared error performance) for a wide range of values of signal‐to‐noise ratio; (b) the gradient‐descent method converges to the true source location uniformly (in less than 100 iterations).

UltraGesture: Fine-Grained Gesture Sensing and Recognition

With the rising of AR/VR technology and miniaturization of mobile devices, gesture recognition is becoming increasingly popular in the research area of human-computer interaction. Some pioneer ultrasound-based gesture recognition systems have been proposed. However, they mostly rely on low-resolution Doppler Effect, with the focus on whole hand motion and fail to deal with minor finger motions. This paper is to present UltraGesture, an ultrasonic finger motion perception and recognition system based on Channel Impulse Response (CIR). CIR measurements can provide with 7 mm resolution, which is sufficient for minor finger motion recognition. UltraGesture encapsulates CIR measurements into image, and builds a Convolutional Neural Network model to classify these images into different categories corresponding to distinct gestures. Furthermore, we use a sliding-window based method to improve accuracy and reduce response latency. UltraGesture can run on the already existed commercial speakers and microphones on most mobile devices without any hardware modification. Our results demonstrate that UltraGesture can achieve an average accuracy ofgreater than 99 percent for 12 gestures including finger click and rotation.

Detection and Parameter Estimation of Solitary Internal Waves Using Distributed Acoustic Sensors

A method to detect solitary internal waves passing through the sensors area in shallow water and estimate their parameters is proposed in this paper using distributed acoustic sensors. The proposed detection method is based on cross correlation of the (envelop of) channel impulse responses estimated from broadband signals transmitted between the sensor nodes with the reference impulse responses in the absence of solitary internal waves. An iterative sequential parameter estimation method is proposed based on time domain matching of the measured channel impulse responses with modeled impulse responses. Simultaneous parameter estimation can be obtained using a global search method such as the matched field inversion. Simulation studies are carried out using environmental acoustic data collected in the northern South China Sea. The results show that the proposed method can effectively detect the existence of passing SIWs, and their parameters can be estimated with reasonable accuracy even under low signal-to-noise ratio conditions.

A Super-Resolution-Assisted Fingerprinting Method Based on Channel Impulse Response Measurement for Indoor Positioning

The channel impulse response (CIR), which characterizes the multipath channel between a transmitter and a receiver, can serve as a received position signature for indoor position fingerprinting (FP). Since it takes large system bandwidth to distinguish individual paths along which the signal waves travel in an indoor environment, a small bandwidth may yield an unsatisfactory performance of FP based on mere CIR. In this paper, we apply the multiple signal classification (MUSIC) algorithm, a super-resolution method, to unveil the path-delay signatures covered by bandwidth-limited CIRs. With the pseudospectrum evaluated with MUSIC, we resolve and identify the arrival times of the individual paths at a sub-sample precision. We further propose a super-resolution-aided fingerprinting (SFP) algorithm to estimate the receiver's position by taking the averaged positions of the reference points (RPs) of similar FP signatures with weights evaluated by the difference in pseudospectrum and received power. Experiments in an indoor environment show that SFP reduces the positioning error compared to the FP based on conventional channel state information (CSI), and that demands fewer infrastructures and less protocol complexity than CIR-based FP does to achieve similar performance.

Millimeter-Wave Base Station Diversity for 5G Coordinated Multipoint (CoMP) Applications

Millimeter-wave (mmWave) will be used for fifth-generation (5G) wireless systems. While many recent empirical studies have presented propagation characteristics at mmWave bands, macrodiversity and Coordinated Multipoint (CoMP) have not been carefully studied. This paper describes a large-scale mmWave base station diversity measurement campaign at 73 GHz in an urban microcell (UMi) in downtown, Brooklyn, NY, USA, and provides the first detailed analysis of CoMP and macrodiversity performance based on extensive measurements. The research employed nine different base station locations in a 200 m by 200 m area and considered 36 individual transmitter-receiver combinations for extensive co- and cross-polarized varying directional beam channel impulse response measurements. From the measured data, hypothesis testing with cross-validation shows that large-scale shadow fading of directional path loss at an RX from multiple base stations can be modeled as being independent. To consider life-like human blockage in CoMP and macrodiversity analysis, simulated human blockage traces are superimposed on the directional measurements to quantitatively show that a user that is served by multiple base stations undergoes dramatically less outage in the presence of rapid fading events, compared to a single serving base station. Moreover, the base station diversity measurements are used to determine the effectiveness of downlink precoding techniques for mmWave CoMP. While results show that the coordination can improve network performance by suppressing interference when it exists, nearly half of the 680 000 directional CoMP measurements (~43%) result in no interference for either user, meaning that macrodiversity alone may offer sufficient link and capacity improvement and that CoMP may not be necessary for interference coordination at mmWave when narrow directional beams are used.

Measurement Stand and Methodology for Research of the Off-Body and Body-to-Body Radio Channels in WBANs with Different Diversity Schemes

The concept of an experimental test bed for system loss and channel impulse response measurements for off-body and body-to-body radio channels in wireless body area networks (WBANs) is fully described. The possible measurement scenarios that may occur in investigation of off-body and body-to-body channels are classified and described in detail. Additionally, an evaluation is provided of the standard and expanded uncertainties of the presented measurement stand and methodology. Finally, the exemplary results are presented and discussed, in order to point out the need for further investigations of different diversity schemes and their applications in WBANs.

Mapping of ocean currents in shallow water using moving ship acoustic tomography.

This study investigates techniques for the acoustic mapping of ocean currents in a shallow-water environment using moored and ship-towed stations. The currents are estimated using the differential travel times (DTTs) observed in the reciprocal acoustic transmissions between those stations. Due to the relative motion induced by the ship-towed station, the Doppler shift estimated from the measured channel impulse response is used to compensate for the arrival patterns and to correct the influence of the relative speed on the DTTs. Furthermore, to estimate the DTTs from the arrival patterns received in the reciprocal directions, a method is devised which involves the time-evolving cross-correlation function of the reciprocal arrival patterns. A feasibility test was carried out at Sizhiwan Marine Test Field, Kaohsiung, Taiwan in September of 2015. The currents were estimated using the data collected from one ship-towed and four moored stations. The estimated currents are consistent with the direct measurements from a shipboard acoustic Doppler current profiler and reveal the spatial distribution of the currents.

Real-Time Geometry-Based Wireless Channel Emulation

Connected autonomous vehicles and industry 4.0 production scenarios require ultrareliable low-latency communication links. The varying positions of transmitter, reflecting objects, and receiver cause a nonstationary time- and frequency-selective fading process. In this paper, we present the necessary hardware architecture and signal processing algorithms for a real-time geometry-based channel emulator, that is needed for testing of wireless control systems. We partition the nonstationary fading process into a sequence of local stationarity regions and model the channel impulse response as sum of propagation paths with time-varying attenuation, delay, and Doppler shift. We implement a subspace projection of the propagation path parameters, to compress the time-variant channel impulse response. This enables a low data-rate link from the host computer, which computes the geometry-based propagation paths, to the software defined radio unit, that implements the convolution on a field programmable gate array (FPGA). With our new architecture, the complexity of the FPGA implementation becomes independent of the number of propagation paths. Our channel emulator can be parametrized by all known channel models. Without loss of generality, we use a parameterization by a geometry-based stochastic channel model, due to its nonstationary nature. We provide channel impulse response measurements of the channel emulator, using the RUSK Lund channel sounder for a vehicular scenario with 617 propagation paths. A comparison of the time-variant power delay profile and Doppler spectral density of simulated and emulated channel impulse response showed a close match with an error smaller than -35 dB. The results demonstrate that our channel emulator is able to accurately emulate nonstationary fading channels with continuously changing path delays and Doppler shifts.