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The recently proposed orthogonal time-frequency space (OTFS) modulation scheme is able to provide significant performance gain over orthogonal frequency division multiplexing (OFDM) in high Doppler spread scenarios. Qualified channel estimation in delay-Doppler domain is the prerequisite for such good performance, but it requires a large number of guard and pilot symbols, which degrades channel capacity significantly. In this paper, a prior channel statistics based scheme is proposed to maximize the system ergodic capacity by optimizing the channel estimation overhead while ensuring the high-quality performance of the OTFS over delay-Doppler channels. We first investigate the signal-to-interference-plus-noise ratio (SINR) performance of the proposed scheme and derive the closed-form ergodic capacity of the OTFS system on its basis. And then, the capacity maximization problem is studied given the root-mean-square (RMS) delay spread rather than a request for instantaneous perfect channel state information (CSI). In addition, we reveal that the additive white Gaussian noise (AWGN) power has an impact on the solution to the optimization problem, so optimization instances are proposed to treat differently according to SNR levels. Extensive simulations are carried out to evaluate the performance of the proposed overhead reduction scheme. Numerical results demonstrate the superiority of the proposed scheme, and the effect of channel characteristics and system parameters are also revealed.

In this paper, we propose a deep learning based algorithm for downlink channel estimation for 5G new radio. The channel estimation block in the downlink plays an important role in mobile device performance. Here, we explore the usage of convolutional neural network (CNN) and compare its performance with conventional and other known CNN based channel estimation methods. The novelty of this method is that, it separates the channel estimation method into three logical blocks. First, obtaining channel coefficients from pilots and filtering for noise reduction. Second, interpolating the channel in frequency domain using the noise filtered channel estimate on pilots. Third, interpolating the channel in time domain across orthogonal frequency-division multiplexing (OFDM) symbols. This architectures allows considerable flexibility in handling various combinations of delay spread (DS) and Doppler spread (DoS) that are possible in practical scenarios. This in turn helps in reducing the complexity and storage requirements. The proposed channel estimation method showed a performance gain of 4 dB in NMSE compared to linear minimum mean square error for clustered delay line channel model at signal to noise ratio of 30 dB, and is robust to mismatches in parameters like DS and DoS because of estimation errors.

To establish reliable wireless communication systems in underground mines, accurate channel modeling plays an indispensable role in the design phase. In this paper, we propose ray tracing-based channel modeling in room-and-pillar mines. Specifically, the propagation paths of signals are firstly determined in the horizontal plane of a room-and-pillar mine using the ray tracing method. Then, the two-dimensional (2D) propagation paths are converted into their corresponding three-dimensional (3D) counterparts by deriving the heights of intersection points at obstacles and the locations of reflection points on mine ceilings and floors. Since the roughness of mine surfaces has a non-negligible influence on radio propagation properties, it is also taken into account when the electric fields of propagation paths are calculated. To validate the accuracy of the proposed ray tracing-based room-and-pillar channel model, we compare simulation results with experimental measurements conducted in an actual mine in terms of mean excess delay and root mean square (RMS) delay spread. The comparisons show simulation results have a good consistency with measurement data.

By analyzing the historical data of flight delay, the delay problem can be effectively prevented and controlled. The spread of delay propagation in continuous flights often leads to large-scale flight delays. Aiming at the problems of flight delay propagation, a flight chain model is proposed to evaluate flight delays. Because flight data has the characteristics of time and space, the flight delay visualization analytics system is put forward to directly interpret the spatio-temporal pattern of flight delay. The time-varying delay trend is shown by the time line chart and sequence histogram. At the same time, it analysis the time sequence of the impact of flight delays on the consecutive flights through the thermal sequence diagram of flight and parallel coordinate chart. The spatial model reflects the spatial distribution rule and spatial clustering results of delay in airports in different regions by thermal map and rectangular tree diagram. Simultaneously, through the tree diagram of flight propagation delay from the perspective of spatial spread, the delay sweep problems are intuitively analyzed. According to the results of the delay spread assessment and visualization, it can provide corresponding suggestions for various departments to control the delay propagation.

Sensor networks have become more popular in recent years, now featuring plenty of options and capabilities. Notwithstanding this, remote locations present many difficulties for their study and monitoring. High-frequency (HF) communications are presented as an alternative to satellite communications, being a low-cost and easy-to-deploy solution. Near vertical incidence skywave (NVIS) technology provides a coverage of approximately 250 km (depending on the frequency being used and the ionospheric conditions) without a line of sight using the ionosphere as a communication channel. This paper centers on the study of the ionosphere and its characteristic waves as two independent channels in order to improve any NVIS link, increasing its robustness or decreasing the size of the node antennas through the appliance of specific techniques. We studied the channel sounding of both the ordinary and extraordinary waves and their respective channels, analyzing parameters such as the delay spread and the channel’s availability for each wave. The frequency instability of the hardware used was also measured. Furthermore, the correlation coefficient of the impulse response between both signals was studied. Finally, we applied polarization diversity and two different combining techniques. These measurements were performed on a single frequency link, tuned to 5.4 MHz. An improvement on the mean bit energy-to-noise power spectral density (Eb/N0) was received and the bit error rate (BER) was achieved. The results obtained showed that the extraordinary mode had a higher availability throughout the day (15% more availability), but a delayed spread (approximately 0.3 ms mean value), similar to those of the ordinary wave. Furthermore, an improvement of up to 4 dB was achieved with the usage of polarization diversity, thus reducing transmission errors.

The millimeter wave (mmWave) band around 60 GHz has been identified as one of the ISM bands for wireless indoor communication systems. In this paper, we present wideband channel measurements conducted at 60 GHz in a seminar room and office environment using state of art Durham University’s channel sounder. The statistical channel parameters of power angle profile, root mean square delay spread, and angular spread are presented for different orientations which include line of sight, obstructed line of sight and non-line of sight with the smallest delay spreads and angular spreads values being observed for the line of sight case.

In this paper, we investigate the millimeter-wave (mmWave) propagation characteristics of large office environments based on measurement data analysis. The measurement campaign was conducted at 28, 38 and 71 GHz with a 500 MHz measurement bandwidth, which frequency bands were chosen considering the WRC-19 mmWave 5G frequencies. In particular, we focus on an open-space type office furnished with cubicle partitions. Unlike regular classical offices, cubicle partitions and pillars are major clutter sources in this office type. Compared with the existing 3GPP model, a larger path loss exponent (PLE) was observed in our LOS measurements, while a smaller PLE was observed in our NLOS measurements. This seems due to a larger hall effect rather than a wave-guiding effect. We also investigate the shadow fading statistics and the excess loss from the free space loss. In addition, we examine the delay spread statistics from the 500-MHz bandwidth measurement data.

In this paper, small-scale indoor channel measurements at millimeter wave frequencies are conducted at the American University of Sharjah campus in the United Arab Emirates. The measurements are performed using a wideband correlation-based channel sounder, which uses a 250 MHz bandwidth signal modulating a 24 GHz carrier. Different indoor scenarios are considered to examine the effect of the environment on the channel characteristics. The measurements are analyzed to obtain the channel's power delay profile, from which various parameters are calculated such as the average excess delay, the delay spread, and the number of resolvable multipath components.

The performance of the underwater optical wireless communication (UOWC) system is highly affected by seawater´s inherent optical properties and the solar radiation from sunlight, especially for a shallow environment. The multipath effect and degradations in signal-to-noise ratio (SNR) due to absorption, scattering, and ambient noises can significantly limit the viable communication range, which poses key challenges to its large-scale commercial applications. To this end, this paper proposes a unified model for underwater channel characterization and system performance analysis in the presence of solar noises utilizing a photon tracing algorithm. Besides, we developed a generic simulation platform with configurable parameters and self-defined scenarios via MATLAB. Based on this platform, a comprehensive investigation of underwater channel impairments was conducted including temporal and spatial dispersion, illumination distribution pattern, and statistical attenuation with various oceanic types. The impact of ambient noise at different operation depths on the bit error rate (BER) performance of the shallow UOWC system was evaluated under typical specifications. Simulation results revealed that the multipath dispersion is tied closely to the multiple scattering phenomenon. The delay spread and ambient noise effect can be mitigated by considering a narrow field of view (FOV) and it also enables the system to exhibit optimal performance on combining with a wide aperture.

Sub-Terahertz frequencies (frequencies above 100 GHz) have the potential to satisfy the unprecedented demand on data rate on the order of hundreds of Gbps for sixth-generation (6G) wireless communications and beyond. Accurate beam tracking and rapid beam selection are increasingly important since antenna arrays with more elements generate narrower beams to compensate for additional path loss within the first meter of propagation distance at sub-THz frequencies. Realistic channel models for above 100 GHz are needed, and should include spatial consistency to model the spatial and temporal channel evolution along the user trajectory. This paper introduces recent outdoor urban microcell (UMi) propagation measurements at 142 GHz along a 39 m $\times$ 12 m rectangular route (102 m long), where each consecutive and adjacent receiver location is 3 m apart from each other. The measured power delay profiles and angular power spectrum at each receiver location are used to study spatial autocorrelation properties of various channel parameters such as shadow fading, delay spread, and angular spread along the track. Compared to the correlation distances reported in the 3GPP TR 38.901 for frequencies below 100 GHz, the measured correlation distance of shadow fading at 142 GHz (3.8 m) is much shorter than the 10-13 m as specified in 3GPP; the measured correlation distances of delay spread and angular spread at 142 GHz (both 12 m) are comparable to the 7-10 m as specified in 3GPP. This result may guide the development of a statistical spatially consistent channel model for frequencies above 100 GHz in the UMi street canyon environment., 6 pages, 6 figures

Real-time accurate channel estimation has been an ongoing challenge because of diverse oceanic events that cause rapid fluctuations of high-energy multipath activity across the delay spread. This work leverages current compressed sensing and sparse optimization techniques with topological signal processing to improve estimation time and localize channel estimation to salient parts of the delay spread. This work improves the estimation time by tracking the channel as a union of overlapping multipath and other scattering events, which are modeled as “feature braids” in the delay-time domain. A channel feature braid may be intuitively visualized as the topologically connected trajectory of a group of channel delay taps, which represent the support of dominant or persistent scattering events, e.g., surface bounce multipath scattering. We present algorithms that harness support-constrained mixed norm optimization techniques to track the evolving support of channel feature braids. We validate our channel feature tracking algorithm independently in experimental field data as well as BELLHOP channel simulations across a diversity of oceanic conditions. This work shows that braiding used in estimation can improve estimation time and track high-energy events that develop within the delay vs time channel representation.

The new generation of capsules that circulate through vacuum tubes at speeds up to 1200 km/h, which is being developed, demands communication systems that can operate at these speeds with high capacity and quality of service. Currently, the two technologies available are the new generation of 802.11ax networks and 5G NR. Using these technologies at such high speeds in a confined environment requires a careful study and design of the configuration of the network and optimization of the physical interface. This paper describes the requirements for critical and business communications, proposing a WLAN and 5G network design based on the analysis of the propagation characteristics and constraints of vacuum tubes and using propagation measurements and simulations made in similar environments at frequencies of 2.5/5.7/24 GHz. These measurements and simulations show that propagation losses in this environment are low (4–5 dB/100 m), as a consequence of the guided propagation, so that the use of bands is preferred. Finally, considering the propagation constraints and requirements of a Hyperloop system, a complete wireless communication system is proposed using two networks with 802.11 and 5G technology.

The operation of an intelligent reflecting surface (IRS) under predictable receiver mobility is investigated. We develop a continuous time system model for multipath channels and discuss the optimal IRS configuration with respect to received power, Doppler spread, and delay spread. It is shown that the received power can be maximized without adding Doppler spread to the system. In a numerical case study, we show that an IRS having the size of just two large billboards can improve the link budget of ground to Low Earth Orbit (LEO) satellite links by up to 6 dB. It also adds a second, almost equivalently strong, communication path that improves the link reliability., Comment: 5 pages, 4 figures

With the next generation of mobile communication being trialled across the world, 5G New Radio (NR) promises to provide a flexible radio interface that fits a diverse range of use cases. As trials and pilots progress, propagation studies are required that evaluate electromagnetic (EM) propagation effects for 5G NR signals. In this article, 5G NR signals are used to evaluate the over-the-air (OTA) error vector magnitude (EVM) within a line-of-sight (LoS) rural/urban environment. For the same receiver locations, time dispersion and propagation loss were measured via the root mean square (RMS) delay spread and path loss. The transmitter−receiver distance investigated ranged from $\mathrm {60~m}$ to $\mathrm {450~m}$ . From the measurement campaign, the path loss exponent (PLE) using a directional antenna at the receiver was 1.98, and 1.82 with an omnidirectional antenna. The root mean square error (RMSE) of the floating intercept/close-in (FI/CI) models for the path loss was 4.96/4.74 and 3.84/3.23 for directional and omnidirectional receivers. The delay spread using a cross polar configuration showed significant increase and a dependency of the delay spread on the path loss was observed. For the measurement route, the mean delay spread was $\mathrm {24~ns}$ and $\mathrm {35~ns}$ for directional and omnidirectional measurements. With regards to the EVM, 16 and 64-QAM transmissions were robust along the entire route for directional and omnidirectional antennas, whereas 256-QAM worked in locations where there was minimal obstruction to the propagation path. The average EVM (%) for 16, 64 and 256-QAM measured along the route was 4.5/5.3/3.9 and 3.4/4.3/3.6 for omnidirectional and directional antennas. The OTA results also show that using a directional antenna (as the receiver) significantly improves the obtainable signal quality of 5G NR signals and also reduces outages for higher modulation schemes. With the measurement results presented, system designers can design efficient receivers, estimate coverage and adequately provision services using 5G NR on the sub-6 GHz frequency band.

In this chapter, multi-path time varying channel model (continuous and discrete), coherence time, coherence frequency, Doppler spread, and the Delay spread are discussed. The probabilistic models like κ–μ, η–μ, Rayleigh, Rician, Nakagami distribution, Case study on Flat-Rayleigh channel model, and Rician channel model are also covered in this chapter.

We have already discussed the time-variant impulse response w(t, s) and the delay spread function \(g(t,\tau )\), which characterize a linear time-variant system completely and hence are called system functions. Now we will see that the latter provides meaningful Fourier transforms for applications in electrical engineering, and thus system functions in the frequency domain.

This paper presents results of path loss measurements, in two indoor environments for both LoS and NLoS scenarios across a frequency range from 0.6-73 GHz using the multi-band custom designed channel sounders developed at Durham University. The data are analysed to estimate the path loss parameters for each frequency band with either the close in path loss model which assumes free space loss at 1 m reference distance and the floating intercept path loss model which estimates both parameters of the path loss model. The data across the multiple bands are then combined to generate a single set of coefficients for a frequency dependent path loss model. The median and 90% values of the rms delay spread values for a 20 dB threshold are presented across the frequency range of 0.6-39 GHz.

Understanding multi-node vehicular wireless communication channels is crucial for future time-sensitive safety applications for human-piloted as well as partly autonomous vehicles on roads, railways and in the air. These highly dynamic wireless communication channels are characterized by rapidly changing channel statistics. In this paper we present the first fully mobile multi-node vehicular wireless channel sounding system, which is capable of simultaneously capturing multiple channel frequency responses, ensuring that measurement conditions are identical for all observed links. We use it to analyze road scenarios with multiple vehicles and a large obstructing double-decker bus. The empirical measurement data is used to parametrize a model for the large obstructing vehicle within a geometry-based stochastic channel model. We compare the time-variant channel statistics obtained from our channel model with the ones from the measurement campaign. By means of a channel emulator we obtain the packet error rates of commercial modems for the measured and the simulated wireless communication channels and compare them, in order to validate the model at the link level. We find that the path loss, the root mean square (RMS) delay spread, and the RMS Doppler spread deviate by less than $3.6\,\mathrm{dB}$, $78\,\mathrm{ns}$, and $52\,\mathrm{Hz}$, respectively, for $80\%$ of the total simulation duration. The PER obtained from measured data is within the maximum and minimum bounds of our model for $86\%$ of the simulation duration.

In the following sections, we introduce the principles of signal transmission over a Multiple Input Multiple Output (MIMO) channel and emphasize on wireless links. We will derive a block diagram of a MIMO system and compact it using the concept of the equivalent baseband channel, which is described in Part I for single input single output (SISO) channels. We characterize the physical channels between the various inputs and outputs of the MIMO system by the delay spread functions, which are functions of two variables t and \(\tau \) to prepare for the case of time-variant wireless channels. For time-invariant MIMO channels, such as cables composed of many two-wire electrical lines or optical fibers, the delay spread function turns into the impulse response and just depends on the delay variable \(\tau \), which is then renamed as t.

Hitherto, we have considered signals and characteristic functions of time-variant system, in particular, the delay spread function \(g(t,\tau )\), as deterministic. With the Fourier transform different spectra or transfer functions, such as the Doppler spread function \(G(f_{t},f_{\tau })\), have been defined. In many applications, e.g., wireless communications the time-variant channel can take on a fast of different characteristics depending on the environment, the speed of the transmitter or receiver, and other effects. Hence, there is a need for the introduction of a statistical description for the most important system parameters. The use of multivariate probability density functions could help in principle.

In this paper, the vehicle-to-vehicle (V2V) channel characteristics in peak hours at the 5.9 GHz band in two typical urban road scenarios, the urban straight road and the intersection, are investigated. The channel characteristics, such as path loss, root mean square (RMS) delay spread, and angular spread, are derived from the ray-tracing (RT) simulations. Due to the low height of antennas at both the transmitter (Tx) and the receiver (Rx), the line of sight (LOS) between the Tx and the Rx will often be obstructed by other vehicles. Based on the RT simulation results, the shadowing loss is modelled by the multimodal Gaussian distribution, and path loss models in both LOS and non-LOS (NLOS) conditions are obtained. And the RMS delay spread in two scenarios can be modelled by the Weibull distribution. In addition, the deployment of an antenna array is discussed based on the statistics distribution of the angular spread.

International audience; We propose a multivariate log-normal distribution to jointly model received power, mean delay, and root mean square (rms) delay spread of wideband radio channels, referred to as the standardized temporal moments. The model is validated using experimental data collected from five different measurement campaigns (four indoor scenarios and one outdoor scenario). We observe that the received power, the mean delay, and the rms delay spread are correlated random variables, and therefore, should be simulated jointly. Joint models are able to capture the structure of the underlying process, unlike the independent models considered in the literature. The proposed model of the multivariate log-normal distribution is found to be a good fit for a large number of wideband data sets.

Future wireless systems are envisaged to be deployed in various scenarios and across a wide range of frequencies which include below 6 GHz with massive multiple input multiple output (MIMO) configurations and above 6 GHz in the millimeter wave frequency band and extending to the Tera Hertz (THz) band. Successful deployment requires a range of models informed by measurements and extraction of appropriate channel parameters for high data rates and dense deployment. Starting from the deployment scenarios which include traditional cellular deployment, short range and long-range links, and more recent high-speed scenarios including vehicular communication e.g. vehicle to infrastructure and vehicle to vehicle, and high speed train scenarios, on body networks and challenging industrial deployment. Measurements in typical environments are reported for outdoor, indoor, outdoor to indoor and clutter loss with estimated channel parameters such as path loss model coefficients and wideband parameters such as RMS delay spread. Simulations of propagation using ray tracing tools are compared with measurements in various frequency bands. The specifics of propagation in the millimeter wave band including the impact of blockage such as human and vehicular blockage and the impact of precipitation are studied from measurements and simulation. Massive MIMO channel measurements in various frequency bands are assessed and modelled.

This article describes the characterization of a wireless channel model from the Rumiwasi archaeological site, based on Received Signal Strength Indicator (RSSI) using LoRa technology for one-slope log-normal model and two-slope log-normal model, for trajectories: non-line of sight (NLOS) and line of sight obstruction (LOBS), for which an analysis of their respective parameters was made and the most suitable model for each trajectory was chosen; RMS delay spread time of the most representative Inca walls of this archaeological site is also presented, of which a comparative analysis of the attenuation of each of these are made and how they influence the RSSI for the NLOS and LOBS trajectories.

Wireless data traffic has increased significantly due to the rapid growth of smart terminals and evolving real-time technologies. With the dramatic growth of data traffic, the existing cellular networks including Fifth-Generation (5G) networks cannot fully meet the increasingly rising data rate requirements. The Sixth-Generation (6G) mobile network is expected to achieve the high data rate requirements of new transmission technologies and spectrum. This paper presents the radio channel measurements to study the channel characteristics of 6G networks in the 107–109 GHz band in three different industrial environments. The path loss, K-factor, and time dispersion parameters are investigated. Two popular path loss models for indoor environments, the close-in free space reference distance (CI) and floating intercept (FI), are used to examine the path loss. The mean excess delay (MED) and root mean squared delay spread (RMSDS) are used to investigate the time dispersion of the channel. The path loss results show that the CI and FI models fit the measured data well in all industrial settings with a path loss exponent (PLE) of 1.6–2. The results of the K-factor show that the high value in industrial environments at the sub-6 GHz band still holds well in our measured environments at a high frequency band above 100 GHz. For the time dispersion parameters, it is found that most of the received signal energy falls in the early delay bins. This work represents a first step to establish the feasibility of using 6G networks operating above 100 GHz for industrial applications.

International audience; The use of organic light emitting diodes (OLEDs) is being growing in public places, mobile phones, and wearable smartwatches and computers, which facilitate simultaneous illumination, display, and data communications. Therefore, there is a high demand to model the OLED-based visible light communications (VLC) channel in device-to-device (D2D) communications. This paper proposes D2D communications where the information data is transmitted via the smartphone's display pixels and received using the built-in cameras of another smartphone. The impact of the receiver orientation on the channel characteristics is investigated, where two static users face each other and the receiver is intentionally oriented towards the transmitter. It is shown that, in an empty room, the range of delay spreads are around 6 to 7.5 ns and 6 to 10 ns when the distances of the transmitter from the wall are 1.5 and 7.5 m, respectively. Furthermore, in a furnished room, there is a drop in the delay spread at the cost of increased optical path loss compared to the empty room

In this paper we present a millimeter wave radio channel sounding campaign, enabled by Reconfigurable Intelligent Surfaces (RISs). The measurement setup is based on an electronically reconfigurable Transmitting-RIS (T-RIS) composed by 400 unit-cells. Optimal phase distributions were implemented in order to operate a beam scan over 120 degrees. Two indoor scenarios were investigated in the Ka Band, exploiting the beam scanning capabilities of the antenna. The results in terms of path loss and delay spread are presented and discussed.

Underwater acoustic (UWA) communication plays a key role in the process of exploring and studying the ocean. In this paper, a modified non-stationary wideband channel model for UWA communication in shallow water scenarios is proposed. In this geometry-based stochastic model (GBSM), multiple motion effects, time-varying angles, distances, clusters’ locations with the channel geometry, and the ultra-wideband property are considered, which makes the proposed model more realistic and capable of supporting long time/distance simulations. Some key statistical properties are investigated, including temporal autocorrelation function (ACF), power delay profile (PDP), average delay, and root mean square (RMS) delay spread. The impacts of multiple motion factors on temporal ACFs are analyzed. Simulation results show that the proposed model can mimic the non-stationarity of UWA channels. Finally, the proposed model is validated with measurement data.

Millimeter-wave (mmWave) is considered a key technology for 5G wireless communication in order to fulfill the increase rapidly the demand of all services that can 5G offer. However, mmWave channel propagation suffers from several obstacles such as weather conditions, rigorous line-of-sight (LOS) requirement, and short range coverage. In this paper, we simulate the characteristics of a spatial channel for 5G mmWave at 73 GHz. A NYUSIM tool has been used to assist in analyze 73 GHz channel characteristics and investigate the effects of different environmental conditions including LOS and NLOS. The simulation uses MIMO-OFDM technology through two main integrated models; the free space path loss model (PL) and the statistical spatial channel model (SSCM). Several simulation results illustrated the 3D channel characteristics, power delay profile (PDP), small scale PDP, and root mean square (RMS) delay spread for both LOS and NLOS.

This paper considers the massive connectivity problem in an asynchronous grant-free random access system, where a huge number of devices sporadically transmit data to a base station (BS) with imperfect synchronization. The goal is to design algorithms for joint user activity detection, delay detection, and channel estimation. By exploiting the sparsity on both user activity and delays, we formulate a hierarchical sparse signal recovery problem in both the single-antenna and the multiple-antenna scenarios. While traditional compressed sensing algorithms can be applied to these problems, they suffer high computational complexity and often require the perfect statistical information of channel and devices. This paper solves these problems by designing the Learned Approximate Message Passing (LAMP) network, which belongs to model-driven deep learning approaches and ensures efficient performance without tremendous training data. Particularly, in the multiple-antenna scenario, we design three different LAMP structures, namely, distributed, centralized and hybrid ones, to balance the performance and complexity. Simulation results demonstrate that the proposed LAMP networks can significantly outperform the conventional AMP method thanks to their ability of parameter learning. It is also shown that LAMP has robust performance to the maximal delay spread of the asynchronous users., Comment: 31 pages, 11 figures

International audience; 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 multiuser MIMO scenario.

In order to meet the higher data transmission rate requirements of subway communication services, the millimeter wave (mmWave) broadband communication is considered as a potential solution in 5G technology. Based on the channel measurement data in subway tunnels, this paper uses ray-tracing (RT) simulation to predict the propagation characteristics of the 28 GHz millimeter wave frequency band in different tunnel scenarios. A large number of simulations based on ray-tracing software have been carried out for tunnel models with different bending radiuses and different slopes, and we further compared the simulation results with the real time measurement data of various subway tunnels. The large-scale and small-scale propagation characteristics of the channel, such as path loss (PL), root mean square delay spread (RMS-DS), and angle spread (AS), for different tunnel scenarios are analyzed, and it was found that the tunnel with a greater slope causes larger path loss and root mean square delay spread. Furthermore, in the curved tunnel, the angle spread of the azimuth angle is larger than that in a straight tunnel. The proposed results can provide a reference for the design of future 5G communication systems in subway tunnels.

This paper presents the results of parameter measurements in two indoor environments for both line of sight (LoS) and non-line of sight (NLoS) scenarios at 25 GHz using multiple directional antennae at the transmitter and a single omnidirectional antenna at the receiver (MISO) with the custom-designed channel sounder developed at Durham University. The data are analysed to estimate the K-factor, path loss parameters and root mean square (RMS) delay spread for each scenario. The 50% and 90% values of the RMS delay spread values for a 20 dB threshold are presented for both scenarios.

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.

This chapter focusses on state-of-the art techniques for body-centric localization using ultra-wideband (UWB) technology with applications suitable for tracking, patient monitoring, training of athletes and motion capture. Human body 3D localisation applying compact and cost-effective wearable antennas placed at different locations on the body is presented for uncluttered and realistic indoor environments. The overall average accuracy in 3D localisation obtained is in the range of 0.5–3 cm for short range communication which is comparable with the optical motion capture systems which are considered as gold standard reference. Detailed channel studies are performed using parameters such as path loss, received signal amplitude, number of multipath components, rms delay spread and kurtosis which assists in identifying LOS and NLOS situations. Simple and effective localization algorithms are presented which makes use of the channel information for channel classification, techniques for identifying and mitigating along with time of arrival (TOA)-based data fusion algorithms. GDOP analysis is performed for validating the accuracy of the compact BS configurations and the influence on localization accuracy considering optimum and random base station configurations. Very compact base-station configurations are reported in this chapter which give high accuracy localization results when compared with conventional used configurations. The applicability of machine learning algorithms for enhancing localization accuracy by accurately classifying the channel links is also discussed.

It‘s widely used in the communication between the unmanned aerial vehicle (UAV) and the ground terminal. In particular, the air-to-ground channel will be interfered with by various obstacles in the complex and changeable urban environments. To further study the air-to-ground channel in the street scenario, a random model suitable for the city street scene is proposed based on the geometric structure of the section ellipsoid. In this model, assuming that the static scatterers on both sides of the road are uniformly distributed in the building area, the mobile scatterers are uniformly distributed in the roadway area. Then the angles of arrival, time-averaged power delay profile, temporal autocorrelation function, spatial cross-correlation function, Doppler power spectral density and root mean square delay spread of the model are derived and analyzed. Also, by adjusting the channel parameters, the geometry-based random channel model is general enough to be suitable for modeling various UAV communication scenarios.

The rapid development of the Internet of Things (IoT) puts forward many requirements for wireless communication technology. Low Power Wide Area Networks (LPWAN) are designed for low bandwidth, low power, longrange and large number of connected IoT applications. As one of the LPWAN, Low Power Long Range Transceiver (LoRa) described as a Frequency Shift Chirp Modulation (FSCM), is widely concerned and studied. In this paper, the performance of Lora modulation in the fading channel is analyzed. Because the delay spread of the multipath signal will propagate to the next symbol, which will cause intersymbol interference (ISI) and result in performance degradation of the system, the FSCM signal with Cyclic Prefix (CP) is introduced. The effectiveness of CP to resist ISI is proved by theoretical analysis and performance simulation. At the same time, the rake receiver is introduced, The performance of the system is greatly improved by the rake reception of multipath signals.

Delay dispersion is one of the key propagation channel characteristics that impact system design and performance. In particular, for OFDM-based systems such as Wi-Fi, it determines both the amount of available frequency diversity and the minimum required cyclic prefix, which in turn impacts the spectral efficiency. For this reason, delay spread and power delay profiles have been analyzed for a long time. However, recent upgrades in Wi-Fi, in particular the addition of a new frequency range (6-7.1 GHz), and the introduction of adaptive beamforming, require a re-assessment based on new measurements. This paper presents extensive measurement results of RMS delay spread and interference quotient that take these developments into account. Results were measured in the 2.4-2.5, 5-6, and 6-7 GHz bands. Furthermore, we compare the “omni-directional” delay spread and interference quotient (i.e., when measured with omni-antennas at transmitter and receiver), to those that occur when beamformed antennas are used. We found that for both outdoor and indoor environments, beamforming typically improves the interference quotient (for a given window size) by about 3-5 dB. The 2.4 and 5-7 GHz bands show a significant difference, while we could not observe statistically significant differences between the 5-6 and 6-7 GHz bands.

In this paper, we first define a high dimensional (HiDi) channel characteristics, i.e., space-frequency covariance, for wideband MIMO-OFDM systems. We then design the conversion of the HiDi covariance in frequency domain from one carrier frequency to another, e.g., for FDD systems. Specifically, we apply the projection method in a Hilbert space to estimate the power angle delay spectrum and form the frequency domain conversion of the space-frequency covariance. We also obtain the asymptotic solutions when considering the infinite delay spread, which significantly reduces the complexity. Moreover, we generalize the conversions of space-frequency covariance in both spatial and frequency domains with two exemplary multi-panel scenarios. We then apply the general solutions to a specific antenna array configuration, i.e., uniform linear array (ULA), and obtain the explicit expressions of conversions. Numerical simulations demonstrate the efficiency of the designed conversions.

In this paper, we study the problem of estimating rank indicator (RI) and channel quality indicator (CQI) under 5G new radio (NR) specification. The main challenge for estimating RI and CQI comes from the fact that their estimation result is affected by many factors, e.g., delay spread, Doppler spread, etc. We use a shallow reinforcement learning technique to estimate the expected spectral efficiency for different RIs and CQIs. In particular, Q-learning is applied to solve the problem with a neural network consisting of a single hidden layer. To update the neural network output when the channel behavior changes, we develop an online adaptation (OA) algorithm working on top of the trained neural network. As a result, the combined algorithm adaptively controls the reported RI and CQI values to satisfy a target block error rate (BLER). We show through simulation results that the proposed algorithm adapts to different channel conditions and maintains the BLER to be around a target value of 10%. The proposed algorithm also significantly outperforms a scheme of fixed CQI and fixed RI when channel varies slowly.

This paper explores to improve the quality of channel estimation when a bundling structure is imposed under 3GPP new radio (NR) specification. When bundling is configured, the precoding per bundle is determined solely by a gNB, which is transparent to a user equipment (UE). Due to the possibility that each bundle is precoded in a different manner, the power delay profile (PDP) needs to be estimated within a bundle in a frequency domain, not in a time domain. One simple approach is to assume that PDP is uniformly distributed up to the maximum delay spread. This method is acceptable when a channel is propagated within a short delay spread, but is not in general. Alternatively, this paper utilizes channel correlation even across bundles in a frequency domain and estimates PDP values by using all the correlation directly. A deep learning technique is applied with a neural network to generate correlation as if not to be precoded. To stabilize the performance, post-processing has been added to the neural network such as filtering, truncation and normalization. Simulation results show that the proposed method achieves the performance close to that of ideal PDP and outperforms the uniform PDP assumption by more than 2 dB.