Channel Impulse Response Research Articles

On the Noise Effect of Fingerprinting-Based Positioning Error in Underwater Visible Light Networks.

This paper assesses the performance of a localization technique for underwater visible light networks. The proposed approach is based on a fingerprinting technique, collecting the channel impulse responses from different wireless optical signals in the visible range. A local database related to the power level distribution within a maritime environment is built and exploited to estimate user position, e.g., a diver moving in a given space for underwater fish monitoring. In this paper, we investigate on the noise effect on the localization accuracy in underwater scenarios and for different water turbidity coefficient and we demonstrate that the estimation error suffers on variable channel impulse responses. Different configuration parameters and environmental scenarios have been considered, showing that the LED transmitter deployment can be effective in the localization estimation. A comparison of the proposed localization approach to the traditional triangulation method has been finally carried out, showing the effectiveness of the fingerprinting-based solution for a lower number of LED transmitters.

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.

Variational autoencoder based receiver for orthogonal time frequency space modulation

The emerging orthogonal time frequency space (OTFS) modulation is demonstrated to offer reliable communication performance advantages over orthogonal frequency division multiplexing (OFDM) in doubly-dispersive fading channel. However, the existing embedded pilot-aided method to estimate channel impulse response (CIR) requires enormous spectral overhead to avoid the contamination of pilot symbols. In this paper, we present a variational autoencoder (VAE) based receiver for OTFS modulation that achieve a joint estimation and detection without pilot in delay-Doppler (DD) domain. The variational approach is considered to simplify the problem, and evidence lower bound (ELBO) is derived as loss function. In encoder step, an approximate posterior probability is introduced and utilized to minimize the Kullback-Leibler (KL) distance. Then we estimate CIR in decoder step and maximize the ELBO at last. From our simulation results, the proposed VAE based receiver for OTFS modulation enjoys a promising performance with other methods.

A survey on estimation schemes in molecular communications

This survey paper focuses on the estimation schemes in molecular communication (MC) systems. The existing studies in estimation schemes can be divided into parameter estimation (e.g., distance, diffusion coefficient, and flow velocity) and channel estimation. In this paper, we present, for the first time, a comprehensive survey on i) distance estimation, since distance is the most widely estimated parameter in current studies, ii) estimation of other parameters (i.e., the parameters excluding distance), and iii) channel estimation that focuses on the channel impulse response (CIR). Moreover, we examine the noise that may impact on the estimation performance and the metrics applied to evaluate the performance of different estimation schemes. Numerical results are provided to compare the performance of different distance estimation schemes. In addition, future research directions in parameter estimation and channel estimation are identified and discussed.

Quantitative analysis of different LED lamp configurations in indoor VLC system

SummaryIn this article, an indoor environment of 5 × 5 × 3 m3 dimensions is considered and a total of nine LED lamps are installed at the ceiling in a symmetrical pattern. The inter‐spatial separation between LED lamps is varied to achieve the dual purpose of lighting and communication services. The multipath channel impulse response for distinct receiver locations is also calculated under line‐of‐sight (LOS) and non‐line‐of‐sight (NLOS) channel conditions. Several performance parameters, that is, illumination uniformity, received power fluctuations, root‐mean‐delay spread (RMDS), are evaluated to estimate the performance of the proposed system. The results show that spatial separation of 1.5 m between the LED lamps outperforms the other considered spatial separations, and the error‐free data transmission rate for the proposed system comes out to be about 40 Mbps across the entire receiver plane. Furthermore, an RGB image is transmitted at 40 Mbps and the received image quality is estimated in terms of image quality parameter, that is, structure similarity index (SSIM) over the receiver plane. The results outlined that the received image shows 100% similarity with the transmitted image, and thus, the proposed system can be effectively deployed in practical indoor environments.

Iterative channel estimation-based soft successive interference cancellation for multiuser underwater acoustic communications.

This paper presents a single-carrier multiuser receiver in underwater acoustic communications with strong multiple access interference (MAI) combining passive time-reversal (PTR) and direct-adaptation-based turbo equalization. The receiver works in an iterative block by block manner. In the first iteration, when the symbols of all users are detected by successive interference cancellation (SIC) in the block, the channel impulse response (CIR) of each user is then updated by post-SIC signal to achieve more accurate MAI reconstruction and PTR combination for the next block. In the following iterations, the a priori mean of symbol in the current block is available and used to further improve the accuracy of reconstructed MAI and the updated CIR. The proposed receiver is demonstrated using experimental data collected at Songhua Lake, China, in 2019. The results show that single-carrier nine-user communication data with quadrature phase-shift keying can be successfully recovered, with an average data rate of 1.67 kbps for each user.

Multi-link channel simulation based on propagation graph theory and application in performance evaluation of TDOA positioning system

In order to solve the problems of high measurement cost and many uncontrollable interference factors in the accuracy evaluation of time difference of arrival (TDOA) localization method by measurement, a method of evaluating the accuracy of a TDOA localization system based on multi-link channel propagation graph theory is proposed. In this paper, we use the propagation graph theory to generate different channel impulse responses, and ultilize software-defined radio devices to generate channel-distorted radio frequency signals as inputs to multiple TDOA sensors and construct a novel TDOA localization evaluation method. In order to verify the accuracy of the TDOA technology effectively, we simulate the method in 4 typical scenarios. It is the first time that a complex scenario is simulated using multi-channel radio frequency signal to test the localization accuracy of the TDOA system. The simulation result shows that when the signal bandwidth is not smaller than 200 kHz, the multi-link localization system based on graph modeling shows good and stable performance. Moreover, graph modeling method with diffraction model embedded enhances the accuracy of performance simulation for the TDOA system, particularly in the non-line-of-sight scenarios.

Effect of scattering phase function on underwater visible light communication channel models

Non-sequential ray tracing simulations are commonly employed to model underwater visible light communication (VLC) channels. The accuracy of such simulations highly depends on how well the optical properties of water (i.e., absorption and scattering) as well as scattering phase function (SPF) are modeled in the simulation. Existing empirical models are only a function of chlorophyll concentration and particle composition and are independent of refractive index, size and concentration of particles. In this paper, we carry out an underwater VLC channel modeling study using the Mie SPF which provides a full description of the scattering from phytoplankton particles which dominate the optical properties of most oceanic waters. We obtain the channel impulse response (CIR) based on an extensive non-sequential ray tracing study and calculate the fundamental channel parameters such as channel gain and delay spread. Comparison of CIRs reveals out that deployment of simplified SPF models results in the overestimation of path loss with respect to Mie SPF. Our results clearly demonstrate the importance of selecting realistic SPF models for an accurate underwater VLC channel modeling. While highlighting the channel models, we discuss adaptive modulation technique to maximize the data rate under the constraint of a targeted bit error rate. Besides, the maximum achievable distance is also determined both in terms of analytical guarantees and computer simulations. The results reveal that larger transmission distances can be achieved through Mie SPF channel model.

A new time-domain heuristic diffraction coefficient for characterization of diffracted and transmitted field with UWB applications

In this paper, a novel heuristic diffraction coefficient in the frequency-domain (FD) for non-perfectly conducting wedges and buildings is proposed. The six-terms diffraction coefficient which is an extension of the four-terms UTD coefficient is proposed to include the effect of transmitted ray for a lossy dielectric wedge with arbitrary low wedge angle, thus, attaining the continuity of the total field all around the structure. This new six-terms UTD diffraction coefficient is verified with the earlier available finite-difference time-domain (FDTD) result. Further, the time-domain (TD) solution based on the classical frequency domain result is proposed for UWB applications in indoor environments. Finally, a case of double diffraction for two consecutive buildings scenario is presented based on slope diffraction and their corresponding TD solution is also presented. The different input pulses and building materials are considered to test the overall behavior of the TD model. All the TD results are verified with inverse fast Fourier transform (IFFT) of the FD results in both the soft and hard polarization and the results are found to be in very good agreement. The channel impulse response is also presented to determine the distortion on the input pulse. The computational efficiency of the proposed TD solutions is demonstrated by comparing them with IFFT-FD solutions.

Watching Your Phone's Back

Gesture recognition on the back surface of mobile phone, not limited to the touch screen, is an enabling Human-Computer Interaction (HCI) mechanism which enriches the user interaction experiences. However, there are two main limitations in the existing Back-of-Device (BoD) gesture recognition systems. They can only handle coarse-grained gesture recognition such as tap detection and cannot avoid the air-borne propagation suffering from the interference in the air. In this paper, we propose StruGesture, a fine-grained gesture recognition system using the back of mobile phones with ultrasonic signals. The key technique is to use the structure-borne sounds (i.e., sound propagation via structure of the device) to recognize sliding gestures on the back of mobile phones. StruGesture can fully extract the structure-borne component from the hybrid Channel Impulse Response (CIR) based on Peak Selection Algorithm. We develop a deep adversarial learning architecture to learn the gesture-specific representation for robust and effective recognition. Extensive experiments are designed to evaluate the robustness over nine deployment scenarios. The results show that StruGesture outperforms the competitive state-of-the-art classifiers by achieving an average recognition accuracy of 99.5% over 10 gestures.

Channel Measurement for Multiple Frequency Bands in Subway Tunnel Scenario

In next-generation radio communication systems, the use of higher frequency bands and the massive multiple-input-multiple-output (MIMO) systems has turned into hot research topics because they have the potential to increase network capacity significantly by exploiting the available narrowband and broadband spectrums. Therefore, the narrowband channel measurements are executed at the following five potential frequency bands, including 2.6 GHz, 3.5 GHz, 5.6 GHz, 10 GHz, and 28 GHz in the Shanghai subway tunnel environment in order to fulfill the latest standards of fifth generation (5G). Moreover, in the broadband channel measurements, the center frequency is 3.5 GHz and 5.6 GHz and the bandwidth is considered as 160 MHz, respectively. At the transmitter (Tx) side, a uniform rectangular antenna array composed of 32 elements is fixed on the platform near the tunnel walls. The receiver (Rx) is equipped with a uniform cylindrical antenna array consisting of 64 elements, which is set on a trolley along the track. Based on the acquired massive MIMO channel impulse responses, delay spread, angle spread, eigenvalue and channel capacity are analyzed. The results reveal that the multipath delay in the tunnel scenario is quite short, the delay spread and angle spread drop rapidly as the distance between Tx and Rx increases and the channel matrix gradually becomes serious. This research provides a reference for the deployment of future 5G systems in the subway tunnel.

Impacts of channel fluctuations on least-squares channel estimation in underwater acoustic communications.

The time-varying multipath introduces major distortions to transmissions in the underwater acoustic communication channel. Channel estimation is often used as one of the central steps to address such distortions in high-rate communication receivers. The focus of this paper is to quantify the impacts of the channel fluctuations on the performance of the least-squares channel estimator. A metric, channel variation ratio (CVR), is defined to describe the rate of fluctuations in the channel impulse responses. Equations are derived to reveal the direct relationships between the CVR and channel estimation performance, which is measured by the channel estimation mean squared error (MSE) and signal prediction error (SPE). The equations show that both the MSE and SPE increase linearly with the CVR. The MSE and SPE metrics both have an error floor for time-varying impulse responses, even with zero ambient noise. It is confirmed that an optimum estimated channel length, achieving the minimum estimation error, exists for time-varying impulse responses. The truncation effects in the channel estimation are also investigated. Experimental data are used to validate the findings.

Reconfigurable Intelligent Surfaces for Rich Scattering Wireless Communications: Recent Experiments, Challenges, and Opportunities

Recent advances in the fabrication and experimentation of Reconfigurable Intelligent Surfaces (RISs) have motivated the concept of the smart radio environment, according to which the propagation of information-bearing waveforms in the wireless medium is amenable to programmability. Although the vast majority of recent experimental research on RIS-empowered wireless communications gravitates around narrowband beamforming in quasi-free space, RISs are foreseen to revolutionize wideband wireless connectivity in dense urban as well as indoor scenarios, which are usually characterized as strongly reverberant environments exhibiting severe multipath conditions. In this article, capitalizing on recent physics-driven experimental explorations of RIS-empowered wave propagation control in complex scattering cavities, we identify the potential of the spatiotemporal control offered by RISs to boost wireless communications in rich scattering channels via two case studies. First, an RIS is deployed to shape the multipath channel impulse response, which is shown to enable higher achievable communication rates. Second, the RIS-tunable propagation environment is leveraged as an analog multiplexer to localize non-cooperative objects using wave fingerprints, even when they are outside the line of sight. Future research challenges and opportunities in the algorithmic design and experimentation of smart rich scattering wireless environments enabled by RISs for sixth Generation (6G) wireless communications are discussed.

Empirical millimeter‐wave wideband propagation characteristics of high‐speed train environments

Owing to the difficulties associated with conducting millimeter-wave (mmWave) field measurements, especially in high-speed train (HST) environments, most propagation channels for mmWave HST have been studied using methods based on simulation rather than measurement. In this study, considering a linear cell layout in which base stations are installed along a railway, measurements were performed at 28 GHz with a speed up to 170 km/h in two prevalent HST scenarios: viaduct and tunnel scenarios. By observing the channel impulse responses, we could identify single- and double-bounced multipath components (MPCs) caused by railway static structures such as overhead line equipment. These MPCs affect the delay spread and Doppler characteristics significantly. Moreover, we observed distinct path loss behaviors for the two scenarios, although both are considered line-of-sight (LoS) scenarios. In the tunnel scenario, the path loss exponent (PLE) is 1.3 owing to the waveguide effect, which indicates that the path loss is almost constant with respect to distance. However, the LoS PLE in the viaduct scenario is 2.46, which is slightly higher than the free-space loss.

UWB Radio-Based Motion Detection System for Assisted Living.

Because of the ageing population, the demand for assisted living solutions that can help prolonging independent living of elderly at their homes with reduced interaction with caregivers is rapidly increasing. One of the most important indicators of the users’ well-being is their motion and mobility inside their homes, used either on its own or as contextual information for other more complex activities such as cooking, housekeeping or maintaining personal hygiene. In monitoring users’ mobility, radio frequency (RF) communication technologies have an advantage over optical motion detectors because of their penetrability through the obstacles, thus covering greater areas with fewer devices. However, as we show in this paper, RF links exhibit large variations depending on channel conditions in operating environment as well as the level and intensity of motion, limiting the performance of the fixed motion detection threshold determined on offline or batch measurement data. Thus, we propose a new algorithm with an online adaptive motion detection threshold that makes use of channel impulse response (CIR) information of the IEEE 802.15.4 ultra-wideband (UWB) radio, which comprises an easy-to-install robust motion detection system. The online adaptive motion detection (OAMD) algorithm uses a sliding window on the last 100 derivatives of power delay profile (PDP) differences and their statistics to set the threshold for motion detection. It takes into account the empirically confirmed observation that motion manifests itself in long-tail samples or outliers of PDP differences’ probability density function. The algorithm determines the online threshold by calculating the statistics on the derivatives of the 100 most recent PDP differences in a sliding window and scales them up in the suitable range for PDP differences with multiplication factors defined by a data-driven process using measurements from representative operating environments. The OAMD algorithm demonstrates great adaptability to various environmental conditions and exceptional performance compared to the offline batch algorithm. A motion detection solution incorporating the proposed highly reliable algorithm can complement and enhance various assisted living technologies to assess user’s well-being over long periods of time, detect critical events and issue warnings or alarms to caregivers.

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.

A UAV-aided channel sounder for air-to-ground channel measurements

Unmanned aerial vehicle (UAV) is a promising platform for future communication systems due to its high mobility, maneuverability, and low cost. The unique features that distinguish UAV communications from conventional land communications include the high altitude, mobility, and three dimensional (3D) trajectories. Thus, it is urgent to measure and analyze the characteristics of air-to-ground (A2G) channels. In this paper, a UAV-aided channel sounder for characterizing A2G channels is developed, which includes two components, i.e., the air transmitter and ground receiver. For measuring the channels, the raw channel impulse response (CIR) is extracted from the measured channel data firstly. According to the parametric channel model, the simplified and more practical CIR is then reconstructed by the clustering and parameter estimation algorithms. In order to verify the effectiveness and accuracy of proposed channel sounder, a commercial channel emulator is used to reproduce realistic channels in the lab and calibrate the measured results by the proposed channel sounder. Finally, the channel sounder is applied to measure the air-to-ground channels under campus scenarios, which shows that the measured channel parameters such as path loss and path delay are consistent with the theoretical ones.

Simulation and Analysis of Extended Spatial Channel Model in Vehicle-to-Vehicle Communication Environments

In this paper, an extension spatial channel model (SCM) for vehicle-to-vehicle (V2V) communications is proposed. To efficiently illustrate the real-world scenarios and reflect nonstationary properties of V2V channels, all effective scattering objects are subdivided into three categories of clusters according to the relative position of clusters. Besides, a birth-death process is introduced to model the appearance and disappearance of clusters on both the array and time axes. Their impacts on V2V channels are investigated via statistical properties including correlation functions. Additionally, a closed-form expression of channel impulse response (CIR) is derived from an extension SCM and cluster-based models. Furthermore, the spatial and frequency statistical properties of the reference model are thoroughly investigated. Finally, simulation results show that the proposed SCM V2V model is in close agreement with previously reported results, thereby validating the accuracy and effectiveness of the proposed model.

CIR-Based Device-Free People Counting via UWB Signals.

The outbreak of COVID-19 has resulted in many different policies being adopted across the world to reduce the spread of the virus. These policies include wearing surgical masks, hand hygiene practices, increased social distancing and full country-wide lockdown. Specifically, social distancing involves keeping a certain distance from others and avoiding gathering together in large groups. Automatic crowd density estimation is a technological solution that could help in guaranteeing social distancing by reducing the probability that two persons in a public area come in close proximity to each other while moving around. This paper proposes a novel low complexity RF sensing system for automatic people counting based on low cost UWB transceivers. The proposed system is based on an ordinary classifier that exploits features extracted from the channel impulse response of UWB communication signals. Specifically, features are extracted from the sorted list of singular values obtained from the singular value decomposition applied to the matrix of the channel impulse response vector differences. Experimental results achieved in two different environments show that the proposed system is a promising candidate for future automatic crowd density monitoring systems.

Robust ultra-wideband range error mitigation with deep learning at the edge

Ultra-wideband (UWB) is the state-of-the-art and most popular technology for wireless localization. Nevertheless, precise ranging and localization in non-line-of-sight (NLoS) conditions is still an open research topic. Indeed, multipath effects, reflections, refractions, and complexity of the indoor radio environment can easily introduce a positive bias in the ranging measurement, resulting in highly inaccurate and unsatisfactory position estimation. This article proposes an efficient representation learning methodology that exploits the latest advancement in deep learning and graph optimization techniques to achieve effective ranging error mitigation at the edge. Channel Impulse Response (CIR) signals are directly exploited to extract high semantic features to estimate corrections in either NLoS or LoS conditions. Extensive experimentation with different settings and configurations has proved the effectiveness of our methodology and demonstrated the feasibility of a robust and low computational power UWB range error mitigation.