Indoor Radio Channel Research Articles

Dispersive Optical Wireless Indoor Channels—From Frequency-Domain Modeling to Bit-Error-Rate Prediction

Dispersive Optical Wireless Indoor Channels—From Frequency-Domain Modeling to Bit-Error-Rate Prediction

Indoor wireless channel characterization in the W band for the planning of 6G communication systems

This work presents a wireless channel characterization based on an extensive campaign of massive multiple-input multiple-output (mMIMO) measurements conducted under line-of-sight (LOS) conditions. These measurements focus on the 94 GHz band (W band), and the results are compared to the same positions measured at 60 GHz. The values of the relative received power, root mean square (RMS) delay spread, maximum excess delay (MED), and coherence bandwidth in an indoor laboratory environment are analyzed. The results of this study can contribute to a better understanding of the propagation channel behavior in the 94 GHz band, and can be used to assess the potential of this band for the upcoming sixth-generation (6G) networks in laboratory environments.

Blockage loss and shadow fading behavior of millimeter‐wave signals due to human bodies at 28 GHz

AbstractAs the millimeter‐wave (mm‐Wave) spectrum is considered to be an essential enabler to the fifth generation (5G) wireless communication systems. Human movements are one of the most significant factors that cause transient blockage in indoor mm‐wave channels. In this letter, human blockage measurements and shadow fading statistics due to human body movements in an indoor office environment are reported for the 28 GHz band. The effect of human bodies on the channel is measured for several scenarios including a variety of population and using diverse antenna heights. The reported shadow fading statistics include both the duration and the depth of the blockage fade, and accordingly, we propose several empirical models that cater for such blockage events. The findings reported in this letter could improve the modeling of indoor radio channels at 28 GHz bands by considering the presence of humans, as well as their movements.

Frequency Domain UWB Channel Characterization and Modeling in Indoor Static Environment

In this article, distance and frequency‐dependent indoor wireless channel characterization and modeling are presented in C, X, and Ku bands at the line of sight (LOS) and nonline of sight (nLOS) scenarios. Complex frequency responses of the indoor radio channel are measured using the frequency‐domain approach. The terminal and measurement setup dependencies of the propagation channel are deconvoluted using closed‐form expressions devised from a two‐port network model approach of the antenna transreceiver system. Subsequently, terminal independent frequency‐domain channel transfer functions (CTFs) and time‐domain channel impulse responses (CIRs) are derived for accurate statistical analysis of large‐ and small‐scale fading parameters of the propagation channel. A distance‐dependent statistical pathloss model is proposed. Successively, a frequency domain channel model using the fifth‐order autoregressive process is proposed. Subsequently, the existence of the multiple clusters in the environment is analyzed by the poles of the transfer functions of the model. Models are validated in both time and frequency domains by comparing the computer‐simulated synthetic model data with the empirical channel responses. The measurement data and the model data are seen to be in good agreement.

Longer Term Time Dynamics of Bit Error Rates

n this paper an analysis is conducted to study the properties of indoor and outdoor wireless channel conditions over long time scales (several minutes). It shows that long term time dynamics exist in many different situations even when transmitters and receivers are stationary and the distance between them is only a few meters. We use software-defined radio (SDR) that implements radio communication functionalities in software. Transmissions have been achieved using the Universal Software Radio Peripheral (USRP), with the signal processing and time synchronization occurring in the GNU Radio environment on the LINUX (Ubuntu 14.04 LTS) platform. The work has been implemented in a typical school environment i.e., indoor conditions including a lab environment along with a hallway and outdoor conditions comprising a quadrangle environment. We used the benchmarking tool in the GNU Radio that defines and modifies modulation schemes, transmitter and receiver gains, operating frequencies, and other channel properties. Per-packet bit error rate is computed, visualized, and compared across multiple scenarios. We find a series of interesting time dynamics of the BER over several minutes that are not commonly studied in the literature.

Radio environment maps for indoor visible light communications aided by machine learning

VLC has been proposed as reliable high-capacity wireless optical communication system for indoor access networks. This technology comprises a high bandwidth unlicensed solution and has been suggested for ultra-reliable environments like hospitals. In this study, Machine Learning is used to investigate indoor wireless optical channels where ultra-reliable communications and signal coverage are required. Specifically, we assess the precision of different Decision Trees ML algorithms based on their mean absolute error metric in comparison to the anticipated simulated outcomes for optical channel estimation in various rooms that could be used in medical care. We demonstrate that Decision Trees models are capable of making fast and accurate predictions. It is shown that the Stack model is the most appropriate Decision Trees-based method, from the ones we studied, for predicting indoor VLC RSS values and constructing the corresponding REMs. These models are 300–65,000 times faster than traditional calculation methods, depending on the number of reflections bounces considered, and deliver accurate predictions, with less than 0.015 mean absolute percentage error, of the Radio Environment Map of a communication system that supports VLC. This is the first implementation of constructing optical REMs for Indoor VLC systems to the best knowledge of the authors.

Modeling and measurement of human body blockage loss at 28 GHz

ABSTRACT Millimeter-wave (mm-Wave) spectrum is an essential enabler to the fifth generation (5G) wireless technology. Humans are one of the most noticeable blockers that cause temporal variation in indoor radio channels. This paper presents human blockage measurements at 28 GHz, with several humans of different sizes. The effect of the crossing orientations of the human bodies is investigated for three different transmitter heights. A human blockage model based on the Fresnel diffraction scheme is shown to be applicable in estimating the human blockage loss in indoor radio links considering various body sizes, different crossing orientations, and different transmitter heights. The findings reported in this paper could help improve indoor radio channel models at 28 GHz bands for 5G technologies considering the presence of human body blockages.

Optimized Multi-Primary Modulation for Visible Light Communication

Multi-primary modulation scheme has the potential to provide robust visible light communication links and mitigate any color fluctuations by providing identical chromaticity modulation alphabets. This work describes constellation optimization technique for multi-primary modulation (MPM), which shows that using different power levels for the primary lights can lead to obtain the same color and, furthermore, enhance the Euclidean distances between data symbols in the multi-dimensional color space. The bit error rate performances of the optimized MPM and the original non-optimized MPM schemes are evaluated considering indoor optical wireless channel models with additive white Gaussian noise. The results show that the optimized MPM provides better spectral efficiency and outperforms the original non-optimized MPM scheme by achieving up to 3.5 dB Signal-to-noise ratio gain for the same spectral efficiency and, therefore, opens doors for implementation of robust visible light communication links exploiting multi-color light sources.

Analysis of Multipath Components Distributions Over a Large Array in Indoor mmWave Channels

In this article, we analyze the characteristics of indoor radio channels at millimeter waves. Measurements were performed using a large virtual antenna array (VAA), for massive multiple input multiple output (MIMO) applications. The results in terms of correlation and multipath components (MPCs) characteristics are analyzed for the whole large array and virtual subarrays composing it. Common MPC among the subarrays are identified, and the impact on the overall channel large-scale parameters is discussed.

Impact of Human Blockage on Dynamic Indoor Multipath Channels at 27 GHz

Human blockage and its dynamics are potential challenges for millimeter-wave (mm-wave) mobile communication. This article presents the results of wideband measurements at 27 GHz with one human blocker close by a dynamic mobile terminal (MT) as well as one or multiple dynamic human blockers further away from an MT. The measured human blockage loss is largest when the direct path (DP) in a line-of-sight (LOS) is blocked, but this loss is limited by other multipath components (MPCs). For nonline-of-sight (NLOS) channels, it is shown that human blockage loss is typically negligible. The presented measurement results show that human blockage loss in multipath channels is much smaller than that reported in diffraction- and measurement-based models, which neglect or minimize the contribution of all MPCs other than the DP. This suggests that the multipath nature of the indoor wireless channel highly limits the impact of human blockage.

WiFi-Based Indoor Positioning and Communication: Empirical Model and Theoretical Analysis

GPS (Global Positioning System) has been developed more mature and perfect in outdoor positioning. However, because GPS signals cannot be effectively transmitted in a complex indoor environment, positioning and navigation cannot be performed in typical situations such as indoor emergency occurrence location determination, shopping mall guides, and intelligent service robot fixed-point services. With the deepening of related researches, technologies based on ultrasound, WiFi, Bluetooth, radio frequency identification, infrared, etc. have been used to achieve indoor target positioning. The traditional WiFi-based indoor positioning technology uses the RSS value and CSI value of the WiFi signal to build a fingerprint database for positioning. The algorithm is complex and highly cost, and the function is relatively single. In this paper, for the first time, we propose a new algorithm for integrating indoor target positioning and communication based on WiFi signals. Using RSS value of WiFi signal for target location and using CSI value for indoor wireless channel modeling to get the system transmission function to achieve communication purpose, the experimental results show that the positioning algorithm can achieve positioning within the ideal accuracy range, and the communication algorithm part can accurately recover the system function of the wireless multipath channel and finally achieve the goal of integration of positioning and communication based on the WiFi signal level.

Research on indoor positioning of power grid equipment based on deep learning

In view of the increasing number of power grid equipment and a large number of indoor deployments, the existing positioning technology cannot meet the requirements. In this paper, a DOA estimation method based on deep learning is proposed to improve the indoor positioning accuracy. Firstly, by studying the propagation characteristics of wireless signals and the transmission characteristics of indoor wireless channels, a statistical channel model with multi subcarrier characteristics is established to generate channel impulse response information. Furthermore, the transformation matrix required for virtual antenna expansion is designed by using the idea of interpolation transformation. This matrix is combined with the channel impulse response to obtain the virtual antenna array data for DOA estimation. The DOA estimation model based on CNN is optimized to obtain high-precision DOA. Finally, the simulation results show that the positioning accuracy can be doubled by using the virtual antenna array technology. The performance of the two-stage DOA estimation algorithm proposed in this paper is slightly better than the accuracy of a large difference step. Even when there are fewer APS, the positioning accuracy is better than the traditional MUSIC algorithm, which is more suitable for indoor positioning of a large number of power grid equipment in the future.

Derivation ofK-Factor Detection Statistics to Discriminate Between LOS and NLOS Scenarios

The Rician <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> -factor has been extensively used to characterize indoor and outdoor wireless propagation channels based on experimental and analytical models. In this paper, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -factor statistics are derived analytically and experimentally validated for LOS and NLOS scenarios. Receiver operating characteristics (ROC) are formulated based on the derived detection statistics such that an optimal decision threshold can be selected to better enhance LOS/NLOS detection accuracy compared to usual methods. The proposed approach is shown to have a greater LOS/NLOS discrimination accuracy than other state-of-the-art approaches. Furthermore, there is evidence that a second metric can be obtained which characterizes the current environment and provides a confidence value, which can be used to inform further decisions.

Investigations into the Effect of High-Ordering the Log-Distance Dependency of Path Loss Models for Indoor Wireless Channels

The massively available amounts of bandwidth that exist in the frequency regime beyond 6 GHz together with the inability of the previous frequencies below 6 GHz have attracted the attention of the research and industrial communities to consider new frequency bands such as Super-High Frequency (SHF), millimeter-wave (mmWave), and further high-frequency bands such as the Terahertz (THz) bands to be the promising solutions to cope with the explosive demand of higher mobile data rate traffic. As a result, many research studies have reported the main wireless channel’s characteristics, such as the path loss over wide ranges of the SHF, mmWave, and THz frequency bands. However, most of the path loss modeling research has adopted the well-known close-in (CI) free space reference distance model to describe propagation effects of the wireless channel leaving behind the improvement concept. It is vital to estimate the path loss accurately since these high-frequency bands significantly suffer from the wireless propagation effects because of their tiny wavelength. This study presents investigations on high-ordering the dependency of the standard CI path loss model on the distance between the transmitting and the receiving antennas in the logarithmic scale. Two improved models are provided and discussed in this work: second-order CI and third-order CI models. The validation of the models’ accuracy is based on measurement data collected in a typical indoor corridor environment at 14, 18, and 22 GHz frequency bands. The main results show that the proposed two models outperform the standard CI model. Moreover, the results reveal notable reductions in the shadow fading’s standard deviation values as the model’s order increases. This means that more precision is provided. Finally, a trade-off study between the model’s accuracy and simplicity is provided in this paper.

A Comparison of Distribution Models for Fast Variations in the Indoor Radio Channel at 5G Frequency Range 1 Microwave Bands

The use of long-term (slow variations) for modelling radio propagation behavior in indoor scenarios limits the validity of such models, as most of the environments induced fast variations overlapped with the slow ones. Real world data gathered at different locations in two bands within Fifth Generation FR1 spectrum, 3 GHz and 5 GHz, provide insight on the effect of such fast variations and on the distribution models that would be useful to complement the long term analysis with short term behavior in order to improve the design of such 5G microwave networks. Comparisons among short term performance taking into account both the frequency, the visibility conditions and the environment size, shape and furnishing are presented with the focus on modelling as accurate as possible the narrowband channel. The use of ΔBIC (describing the difference between Bayesian Information Criteria indexes of each fitting) complements and confirms the insight provided by direct inspection on traditional fitting plots. This parameter could be interesting for future network deployments.

Scattering and Roughness Analysis of Indoor Materials at Frequencies from 750 GHz to 1.1 THz

The problem of wave propagation and scattering at terahertz (THz) frequencies has become increasingly important, in particular for accurate modeling of future indoor wireless communication channels. The reflective properties of indoor materials with different surface roughness and dielectric constants are important to explore diffuse scattering for accurate channel modeling. First and foremost, a terahertz <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Swissto12</i> system is adopted to obtain the first ever transmission measurements for a wide choice of indoor material groups, such as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">wood, plastic</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">brick</i> at frequencies from 750 GHz to 1.1 THz using up-conversion (frequency-domain) method. Both the reflection ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S_{11}$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S_{22}$ </tex-math></inline-formula> ) and transmission coefficients ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S_{12}$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S_{21}$ </tex-math></inline-formula> ) are measured using this novel and noninvasive electromagnetic technique. The inversion method based on Kramers–Kronig (K-K) relations is then applied to convert the calibrated scatter data into intrinsic material properties (i.e., refractive index, permittivity, absorption coefficient). Then, the surface topography of rough material samples is acquired using surface measurement instruments. Further, the optically smooth <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(\sigma _{h} /\lambda \ll 1)$ </tex-math></inline-formula> materials are assorted as most to least rough based on Rayleigh roughness factor. Lastly, the ray tracer considering the Rayleigh-Rice (R-R) scattering model is employed to obtain the maximum achievable reflected paths of the above-mentioned indoor material samples at 300 GHz followed by their experimental validation.

Millimeter Wave and Sub-THz Indoor Radio Propagation Channel Measurements, Models, and Comparisons in an Office Environment

This letter provides a comparison of indoor radio propagation measurements and corresponding channel statistics at 28, 73, and 140 GHz, based on extensive measurements from 2014-2020 in an indoor office environment. Side-by-side comparisons of propagation characteristics (e.g., large-scale path loss and multipath time dispersion) across a wide range of frequencies from the low millimeter wave band of 28 GHz to the sub-THz band of 140 GHz illustrate the key similarities and differences in indoor wireless channels. The measurements and models show remarkably similar path loss exponents over frequencies in both line-of-sight (LOS) and non-LOS (NLOS) scenarios, when using a one meter free space reference distance, while the multipath time dispersion becomes smaller at higher frequencies. The 3GPP indoor channel model overestimates the large-scale path loss and has unrealistic large numbers of clusters and multipath components per cluster compared to the measured channel statistics in this letter.

FPGA implementation of fuzzy sparse adaptive equalizer for indoor wireless communication systems

Channel equalization is a basic requirement of wireless receiver to alleviate the effects of inter symbol interference (ISI) that helps in faithful reconstruction of original information. The accuracy of channel state information (CSI) also affects the equalizer performance designed for fading communication channels. The paper proposes a robust decision feedback equalizer (DFE) for indoor wireless channels with limited user mobility using sparse fuzzy modeling. The main contributions of the paper can be realized looking into three important aspects. First, the equalizer is designed for practical indoor channel conditions using adaptive model whose learning parameter is selected using fuzzy rule. Second, the computational complexity is substantially reduced by incorporating norm-based sparsity to the cost function. Third important point is validation of equalization model using Xilinx FPGA and Artix 7 board. QPSK modulated data is transmitted through the channel having non-ideal frequency response which is characterized by IEEE 802.11 model. Further bit error rate(BER), mean square error(MSE), eye diagram and power delay profile(PDP) are taken as the performance measures to test the equalizer in presence of fading effects and user mobility. Both MATLAB simulation and FPGA implementation results are presented to justify the usefulness of the proposed equalization model for indoor wireless communication.

RBF neural network channel modeling of millimeter wave based on adaptive particle swarm optimization algorithm

In this paper, the method of radial basis function (RBF) in machine learning is applied to the modeling of millimeter-wave channel based on millimeter wave indoor wireless channel measurement data. A RBF neural network channel parameter prediction model based on adaptive particle swarm optimization (APSO) is established, and the prediction results of the traditional RBF algorithm are compared. Specifically, the RBF model optimized based on APSO is used to learn and predict the characteristics of large-scale channel parameters (LSCP), such as path loss and delay spread. The results show that the predicted channel parameters of the APSO-RBF model is consistent well with the actual measured value. The learning performance and prediction effect of this algorithm are better than the traditional RBF algorithm, that is, the RBF algorithm has a smaller root-mean-square error (RMSE), and the predicted curve has a larger fitting degree with the original measured curve. In addition, the APSO-RBF model has good adaptability to the change of channel parameters in the case of large data fluctuation, and can achieve good prediction effect for 5G millimeter wave channel parameters.

InAs/InP quantum dash buried heterostructure mode-locked laser for high capacity fiber-wireless integrated 5G new radio fronthaul systems.

We have developed and experimentally demonstrated a highly coherent and low noise InP-based InAs quantum dash (QDash) buried heterostructure (BH) C-band passively mode-locked laser (MLL) with a pulse repetition rate of 25 GHz for fiber-wireless integrated fronthaul 5G new radio (NR) systems. The device features a broadband spectrum providing over 46 equally spaced highly coherent and low noise optical channels with an optical phase noise and integrated relative intensity noise (RIN) over a frequency range of 10 MHz to 20 GHz for each individual channel typically less than 466.5 kHz and -130 dB/Hz, respectively, and an average total output power of ∼50 mW per facet. Moreover, the device exhibits low RF phase noise with measured RF beat-note linewidth down to 3 kHz and estimated timing jitter between any two adjacent channels of 5.5 fs. By using this QDash BH MLL device, we have successfully demonstrated broadband optical heterodyne based radio-over-fiber (RoF) fronthaul wireless links at 5G NR in the underutilized spectrum of around 25 GHz with a total bit rate of 16-Gb/s. The device performance is experimentally evaluated in an end-to-end fiber-wireless system in real-time in terms of error vector magnitude (EVM) and bit error rate (BER) by generating, transmitting and detecting 4-Gbaud 16-QAM RF signals over 0.5-m to 2-m free-space indoor wireless channel through a total length of 25.22 km standard single mode fiber (SSMF) with EVM and BER under 8.4% and 2.9 × 10-5, respectively. The intrinsic characteristics of the device in conjunction with its system transmission performance indicate that QDash BH MLLs can be readily used in fiber-wireless integrated systems of 5G and beyond wireless communication networks.