scispace - formally typeset
Search or ask a question

Showing papers on "Multipath propagation published in 2022"


Journal ArticleDOI
TL;DR: In this paper , a software defined receiver (SDR) is developed for indoor positioning in 5G new radio (NR) networks, where the 5G NR signals are first sampled by universal software radio peripheral (USRP), and then, coarse synchronization is achieved via detecting the start of the synchronization signal block (SSB).
Abstract: Indoor positioning is one of the core technologies of Internet of Things (IoT) and artificial intelligence (AI), and is expected to play a significant role in the upcoming era of AI. However, affected by the complexity of indoor environments, it is still highly challenging to achieve continuous and reliable indoor positioning. Currently, 5G cellular networks are being deployed worldwide, the new technologies of which have brought the approaches for improving the performance of wireless indoor positioning. In this paper, we investigate the indoor positioning under the 5G new radio (NR), which has been standardized and being commercially operated in massive markets. Specifically, a solution is proposed and a software defined receiver (SDR) is developed for indoor positioning. With our SDR indoor positioning system, the 5G NR signals are firstly sampled by universal software radio peripheral (USRP), and then, coarse synchronization is achieved via detecting the start of the synchronization signal block (SSB). Then, with the assistance of the pilots transmitted on the physical broadcasting channel (PBCH), multipath acquisition and delay tracking are sequentially carried out to estimate the time of arrival (ToA) of received signals. Furthermore, to improve the ToA ranging accuracy, the carrier phase of the first arrived path is estimated. Finally, to quantify the accuracy of our ToA estimation method, indoor field tests are carried out in an office environment, where a 5G NR base station (known as gNB) is installed for commercial use. Our test results show that, in the static test scenarios, the ToA accuracy measured by the 1-{\sigma} error interval is about 0.5 m, while in the pedestrian mobile environment, the probability of range accuracy within 0.8 m is 95%.

27 citations


Journal ArticleDOI
TL;DR: A novel single-anchor localization algorithm for a state-of-the-art architecture where the position of the user equipment is to be estimated at the base station with the aid of a RIS.
Abstract: Reconfigurable intelligent surfaces (RISs) are considered among the key techniques to be adopted for sixth-generation cellular networks (6G) to enhance not only communications but also localization performance. In this regard, we propose a novel single-anchor localization algorithm for a state-of-the-art architecture where the position of the user equipment (UE) is to be estimated at the base station (BS) with the aid of a RIS. We consider a practical model that accounts for both near-field propagation and multipath environments. The proposed scheme relies on a compressed sensing (CS) technique tailored to address the issues associated with near-field localization and model mismatches. Also, the RIS phases are optimized to enhance the positioning performance, achieving more than one order of magnitude gain in the localization accuracy compared to RISs with non-optimized phases.

26 citations


Journal ArticleDOI
TL;DR: This paper points out that the interference bandwidth is wider and more taps in STAP are required, under the same experiment conditions, and reveals how the STAP can solve the interference multipath.
Abstract: Interference multipath is an important factor to affect the anti-jamming performance for the global navigation satellite system (GNSS) antenna array receiver. However, interference multipath must be considered in practical application. In this paper, the antenna array model for interference multipath is analyzed, and an equivalent model for interference multipath is proposed. According to the equivalent interference multipath model, the influence of interference multipath on anti-jamming performance is analyzed from the space only processing (SOP) and space-time adaptive processing (STAP). Interference multipath can cause loss of the degree of freedom (DoF) of SOP. Through analysis of the equivalent model and STAP mechanism, it further reveals how the STAP can solve the interference multipath. The simulation experiments prove that the equivalent model is effective, and the analysis conclusion is correct. This paper also points out that the interference bandwidth is wider and more taps in STAP are required, under the same experiment conditions.

26 citations


Journal ArticleDOI
TL;DR: In this article , a shape remodeling group sparse constraint algorithm is proposed and combined with the particle swarm optimization method to simultaneously reconstruct the unknown layout and targets, which integrates the basic structural characteristics and sparsity prior of the NLOS image.
Abstract: Non-line-of-sight (NLOS) detection is an enduring topic as it provides a powerful tool to monitor visually blocked areas. Currently, NLOS detection requires precise prior knowledge of building layout, which limits its further applications in practice. In this article, we consider the problem of joint estimation of building layout and target location in the NLOS scenario by exploiting multipath returns. Specifically, first, the building layout is simplified into combined linear equations with unknown parameters. In this way, we establish a parametrized multipath propagation model in the multiple targets’ NLOS scenario for the multiple-input–multiple-output (MIMO) radar, which is used in the image reconstruction and layout estimation problem. Then, a shape remodeling group sparse constraint algorithm is proposed and combined with the particle swarm optimization method to simultaneously reconstruct the unknown layout and targets. Compared with the conventional compressed sensing-based methods, the proposed method integrates the basic structural characteristics and sparsity prior of the NLOS image to improve the stability of the solution. Finally, the performance of the proposed method is verified with numerical and experimental results.

24 citations


Journal ArticleDOI
31 Mar 2022-Sensors
TL;DR: A hybrid deep-learning-based indoor localization system called RRLoc is presented which fuses fingerprinting and time-based techniques with a view of combining their advantages and improves localization accuracy by at least 267% and 496% compared to the state-of-the-art fingerprints and ranging-based-multilateration techniques, respectively.
Abstract: Great attention has been paid to indoor localization due to its wide range of associated applications and services. Fingerprinting and time-based localization techniques are among the most popular approaches in the field due to their promising performance. However, fingerprinting techniques usually suffer from signal fluctuations and interference, which yields unstable localization performance. On the other hand, the accuracy of time-based techniques is highly affected by multipath propagation errors and non-line-of-sight transmissions. To combat these challenges, this paper presents a hybrid deep-learning-based indoor localization system called RRLoc which fuses fingerprinting and time-based techniques with a view of combining their advantages. RRLoc leverages a novel approach for fusing received signal strength indication (RSSI) and round-trip time (RTT) measurements and extracting high-level features using deep canonical correlation analysis. The extracted features are then used in training a localization model for facilitating the location estimation process. Different modules are incorporated to improve the deep model’s generalization against overtraining and noise. The experimental results obtained at two different indoor environments show that RRLoc improves localization accuracy by at least 267% and 496% compared to the state-of-the-art fingerprinting and ranging-based-multilateration techniques, respectively.

24 citations


Journal ArticleDOI
TL;DR: A dataset generation method, the Multilevel Feature Synthesis Method (Multilevel-FSM), to obtain positioning features and a specially designed deep learning positioning method, Multipath Res-Inception (MPRI), trained on the proposed dataset to enhance positioning accuracy.
Abstract: Location-based services (LBSs) provide necessary infrastructure for daily life, from bicycle sharing to nursing care. In contrast to traditional positioning methods such as Wi-Fi, Bluetooth, and ultra-wideband (UWB), fifth-generation (5G) networking is defined as a paradigm of integrated sensing and communication (ISAC). With its advantages of wide-range coverage and indoor-outdoor integration, 5G is promising for high-precision positioning in indoor and urban canyon environments. However, 5G location studies face great obstacles due to the lack of commercialized 5G ISAC base stations that support positioning functions as well as publicly available datasets. In this paper, we first propose a dataset generation method, the Multilevel Feature Synthesis Method (Multilevel-FSM), to obtain positioning features. In particular, the features of a multiple-input multiple-output (MIMO) channel are flattened into a single image to increase the information density and improve feature expression, and data augmentation is performed to provide stronger robustness to noise. Subsequently, we devise a specially designed deep learning positioning method, Multipath Res-Inception (MPRI), trained on the proposed dataset to enhance positioning accuracy. Finally, the results of extensive experiments conducted in two typical 5G scenarios (indoors and urban canyon) show that Multilevel-FSM and MPRI outperform state-of-the-art works in accuracy, time overhead and robustness to noise.

23 citations


Journal ArticleDOI
TL;DR: In this article , a learning-driven latency-aware MPTCP (LDA-MPTCP) is proposed to mitigate the out-of-order packet arrival and receive buffer blocking problems associated with the network heterogeneity in the industrial Internet.
Abstract: With various industrial wireless networks greeting booming development, modern industrial devices configured with several network interfaces increasingly become the norm. Such multihomed industrial devices can increase application throughput by making use of multiple network paths, enabled by the multipath transmission control protocol (MTCP) (MPTCP). However, MPTCP might be challenged in the heterogeneous industrial networks because concurrent transmitting industrial application data over asymmetric network paths with different delays is almost bound to the receive buffer blocking problem, which is caused by out-of-order packet arrival and is harmful to the performance of the multipath transmission. The existing MPTCP solutions generally use static mathematical models to evaluate path quality and prohibit transmission on paths with poor quality, which are unable to perform efficiently under highly dynamic and complex network environments. Therefore, in this article, we propose a learning-driven latency-aware MPTCP variant, called ${l}\,^2$ -MPTCP, which seeks to possibly mitigate the out-of-order packet arrival and receive buffer blocking problems associated with the network heterogeneity in the industrial Internet. ${l}\,^2$ -MPTCP accurately computes each MPTCP path’s forward delay and assigns application data to multiple paths according to their calculated forward delay differences by using a novel multiexpert learning-enabled forward delay estimator. ${l}\,^2$ -MPTCP dynamically manages path usage and chooses the optimal path collection for bandwidth aggregation and multipath transmission by using a promising reinforcement learning-empowered multipath manager. Experimental results demonstrate that ${l}\,^2$ -MPTCP outperforms the current MPTCP solutions in terms of multipathing service quality.

21 citations


Journal ArticleDOI
TL;DR: For better understanding of impact factors on the signal quality and transmission coverage of the directional 40GHz mmWave band in the indoor environment, a measurement campaign is introduced in detail and the channel characteristics are measured and analysed in varying cases.
Abstract: Due to the great demand of throughput and reliability for multimedia applications in Fifth Generation (5G) networks, many broadcasting systems adopt the Millimeter Wave (mmWave) technology to address the lack of the spectrum resources. As one of 5G-PPP projects, Internet of Radio Light (IoRL) project adopts 40GHz mmWave band to support a high-speed and stable Ultra-High-Definition (UHD) television broadcasting service in the indoor environment. Because of the high frequency property, mmWave bands usually suffers from the high path loss and the penetration loss. Thus, in order to overcome these issues, directional antennas are employed to provide additional power gain while increasing transmission distance. However, the mmWave with directional antennas brings additional problems, such as limited transmission angle and more multipath effects. Therefore, in this paper, for better understanding of impact factors on the signal quality and transmission coverage of the directional 40GHz mmWave band in the indoor environment, a measurement campaign is introduced in detail and the channel characteristics are measured and analysed in varying cases. The mainly concerned characteristics are path loss, shadow fading, average Power Delay Profile (PDP), Root-Mean-Square (RMS) delay spread, arrival rate and coherence bandwidth. All Measured characteristic values are summarised in three tables at the end of this paper. Besides of these, as a reference of channel analysis and a metric of signal quality and effective coverage, Error Vector Magnitude (EVM) of received signal in each case is measured and discussed. Moreover, a simulation is performed based on a statistical channel model to validate the measured results.

21 citations


Journal ArticleDOI
TL;DR: Theoretical performance analysis for a dual-hop communication system, consisting of multiple relays and multiple users in the HSTRN with the amplify-and-forward protocol, reveals that the performance of the system can be improved by increasing the number of relays
Abstract: A hybrid satellite-terrestrial relay network (HSTRN) has been envisioned as a promising communication architecture for future wireless communications, which can prominently reduce the impact of shadow fading and expand service coverage. In this paper, we conduct theoretical performance analysis for a dual-hop communication system, consisting of multiple relays and multiple users in the HSTRN with the amplify-and-forward protocol. For the shadowing effect and the multipath effect, we introduce the shadowed-Rician distribution and Nakagami-$m$ fading to characterize the channel models for the satellite-relay and the relay-user links, respectively. Additionally, the opportunistic scheduling scheme is employed, where the optimal relay and the optimal user are selected from the alternative nodes with the maximum instantaneous signal-to-noise ratio. Thereafter, the analytical expressions including ergodic capacity and average symbol error rate (SER) are derived. More specifically, we also present the asymptotic behavior of the average SER at the high signal-to-noise ratio (SRN) regime. The theoretical analysis is validated by the numerical results. Moreover, the results also reveal that the performance of the system can be improved by increasing the number of relays and users under different channel parameters and various modulation schemes.

20 citations


Journal ArticleDOI
01 May 2022-Sensors
TL;DR: An algorithm for joint estimation of communication channel gains and signal distortions in a direct conversion receiver using the linear least squares method and an analysis of the noise immunity of quadrature amplitude modulation (QAM) signal reception is carried out.
Abstract: In this article, an algorithm for joint estimation of communication channel gains and signal distortions in a direct conversion receiver is proposed. The received signal model uses approximations with a small number of parameters to reduce the computational complexity of the resulting algorithm. The estimation algorithm is obtained under the assumption of a priori uncertainty about the characteristics of the communication channel and noise distribution using the linear least squares method. Estimation is performed first by the test sequence, then by the information symbols obtained after detection. In addition, an analysis of the noise immunity of quadrature amplitude modulation (QAM) signal reception is carried out using different approximating structures in the estimation algorithm for systems with a single transmitting and receiving antenna (SISO) and for systems with multiple transmitting and receiving antennas (MIMO). Furthermore, this article examines the influence of the duration of the test signal, the number of sessions of its transmission, and the channel extrapolation interval on the quality of signal reception.

19 citations


Journal ArticleDOI
TL;DR: A multi-carrier differential chaos shift keying communication system with hybrid index modulation, referred to as HIM-MC-DCSK system, is proposed in this paper and intelligently integrate the carrier-number-index technique and carrier- index technique into the MC- DCSK modulation in order to significantly boost the transmission efficiency in wireless communication systems.
Abstract: To realize high energy-efficient, high spectrum-efficient, and high-throughput data transmission, a multi-carrier differential chaos shift keying communication system with hybrid index modulation, referred to as HIM-MC-DCSK system, is proposed in this paper. In the HIM-MC-DCSK system, we intelligently integrate the carrier-number-index technique and carrier-index technique into the MC-DCSK modulation in order to significantly boost the transmission efficiency in wireless communication systems. Especially, we use a pair of orthogonal signals to represent the active and inactive subcarriers in the HIM-MC-DCSK system so as to exploit all the subcarriers to transmit information bits. In addition, the theoretical bit-error-rate (BER) expressions of the HIM-MC-DCSK system are derived over additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. Also, the data rate, spectrum efficiency, energy efficiency, and complexity of the proposed system are carefully analyzed. Monte-Carlo simulations not only verify the accuracy of the theoretical analysis but also illustrate the superiority of the proposed system.

Journal ArticleDOI
TL;DR: In this paper , a passive location parameter estimator using multiple satellites for the moving aerial target is proposed, where the direct wave signals in reference channels are first filtered by a band-pass filter, followed by a sequence cancelation algorithm to suppress the direct-path interference and multipath interference.
Abstract: Estimating the location parameters of moving target is an important part of intelligent surveillance for the Internet of Vehicles (IoV). Satellite has the potential to play a key role in many applications of space–air–ground-integrated networks (SAGINs). In this article, a novel passive location parameter estimator using multiple satellites for the moving aerial target is proposed. In this estimator, the direct wave signals in reference channels are first filtered by a band-pass filter, followed by a sequence cancelation algorithm to suppress the direct-path interference and multipath interference. Then, the fourth-order cyclic cumulant cross ambiguity function (FOCCCAF) of the signals in the reference channels and the four-weighted fractional Fourier transform FOCCCAF (FWFRFT-FOCCCAF) of signals in the surveillance channels are derived. Using them, the time difference of arrival (TDOA) and the frequency difference of arrival (FDOA) are estimated and the distance between the target and the receiver and the velocity of the moving aerial target are estimated by using multiple satellites. Finally, the Cramer–Rao lower bounds of the proposed location parameter estimators are derived to benchmark the estimator. The simulation results show that the proposed method can effectively and precisely estimate the location parameters of the moving aerial target.

Journal ArticleDOI
TL;DR: The theoretical expression of bit-error rate (BER) and diversity order of the TD-DCSK scheme over multipath Rayleigh fading channels are derived, and its hardware complexity is analyzed to validate the accuracy of the theoretical derivation.
Abstract: A novel differential chaos shift keying scheme with transmit diversity, referred to as TD-DCSK scheme, is proposed in this letter. The proposed TD-DCSK scheme can achieve full diversity and high data rate by advisably designing the space-time (ST) block of the transmitted signal. With the designed ST block, the transmitter with multiple transmit antennas in the TD-DCSK scheme requires only one radio frequency chain, which is particularly important for keeping low hardware complexity. We derive the theoretical expression of bit-error rate (BER) and diversity order of the TD-DCSK scheme over multipath Rayleigh fading channels, and analyze its hardware complexity. Simulation results illustrate the superiority of the proposed scheme and validate the accuracy of the theoretical derivation. The proposed TD-DCSK scheme stands out as a promising solution for low-power and low-cost short-range wireless communications.

Journal ArticleDOI
01 Jul 2022-Sensors
TL;DR: A novel machine learning framework consisting of Bag-of-Features and followed by a k-nearest neighbor classifier to categorize the final features into their respective geographical coordinate data that outperforms previously developed models.
Abstract: Location-based services have permeated Smart academic institutions, enhancing the quality of higher education. Position information of people and objects can predict different potential requirements and provide relevant services to meet those needs. Indoor positioning system (IPS) research has attained robust location-based services in complex indoor structures. Unforeseeable propagation loss in complex indoor environments results in poor localization accuracy of the system. Various IPSs have been developed based on fingerprinting to precisely locate an object even in the presence of indoor artifacts such as multipath and unpredictable radio propagation losses. However, such methods are deleteriously affected by the vulnerability of fingerprint matching frameworks. In this paper, we propose a novel machine learning framework consisting of Bag-of-Features and followed by a k-nearest neighbor classifier to categorize the final features into their respective geographical coordinate data. BoF calculates the vocabulary set using k-mean clustering, where the frequency of the vocabulary in the raw fingerprint data represents the robust final features that improve localization accuracy. Experimental results from simulation-based indoor scenarios and real-time experiments demonstrate that the proposed framework outperforms previously developed models.

Journal ArticleDOI
TL;DR: In this paper , a support vector regression (SVR) based model was proposed to obtain a function of the elevation and azimuth angle of each satellite to extract an unbiased multipath from the GNSS measurements and a nonlinear multipath map was generated, as a result of training with the extracted multipaths, by a Support Vector Machine.
Abstract: As the necessity of location information closely related to everyday life has increased, the use of global navigation satellite systems (GNSS) has gradually increased in populated urban areas. Contrary to the high necessity and expectation of GNSS in urban areas, GNSS performance is easily degraded by multipath errors due to high-rise buildings and is very difficult to guarantee. Errors in the signals reflected by the buildings, i.e., multipath and non-line-of-sight (NLOS) errors, are the major cause of the poor accuracy in urban areas. Unlike other GNSS major error sources, the reflected signal error, which is a user-dependent error, is difficult to differentiate or model. This paper suggests training a multipath prediction model based on support vector regression to obtain a function of the elevation and azimuth angle of each satellite. To extract an unbiased multipath from the GNSS measurements, the clock error of high-elevation QZSS was estimated, and the clock offset with other constellations was also calculated. A nonlinear multipath map was generated, as a result of training with the extracted multipaths, by a Support Vector Machine, which appropriately reflected the geometry of the building near the user. The model was effective at improving the urban area positioning accuracy by 58.4% horizontally and 77.7% vertically, allowing us to achieve a 20 m accuracy level in a deep urban area, Teheran-ro, Seoul.

Journal ArticleDOI
TL;DR: This paper presents CLB, a programmable switch-based general-purpose in-network load balancer that can adapt to traffic changes at a very high speed and leads to performance improvement compared to other load balancing schemes.
Abstract: This paper presents CLB, a programmable switch-based general-purpose in-network load balancer that can adapt to traffic changes at a very high speed. It uses Weighted-Cost Multipath (WCMP) mechanism for traffic-aware load balancing over many paths at a coarse-grained precision. CLB can be configured to match the load balancing requirements of a wide range of applications at line rate. We have analytically shown that CLB can achieve a bounded response time to traffic changes in the data plane. We implement CLB using the P4 programming language. Our experimental evaluation shows CLB can successfully distribute the incoming load over multiple paths for a given path-weight distribution and leads to performance improvement compared to other load balancing schemes.

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper proposed a multipath feature fusion convolutional neural network (MF2-Net) with novel and efficient spatial group convolution (SGC) modules for automated segmentation of medical images.

Journal ArticleDOI
TL;DR: In this article , a phase-distance model was proposed to estimate the tag location with high accuracy, where a mobile robot equipped with a reader antenna localizes in 2D the tags placed in an indoor scenario and reconstructs the map of the environment through a SLAM algorithm.
Abstract: The use of radio frequency identification (RFID) technology for the traceability of products throughout the production chain, warehouse management, and the retail network is spreading in the last years, especially in those industries in line with the concept of Industry 4.0. The last decade has seen the development of increasingly precise and high-performance methods for the localization of goods. This work proposes a reliable 2-D localization methodology that is faster and provides a competitive accuracy, concerning the state-of-the-art techniques. The proposed method leverages a phase-distance model and exploits the synthetic aperture approach and unwrapping techniques for facing phase ambiguity and multipath phenomena. Trilateration applied on consecutive phase readings allows finding hyperbolae as the localization solution space. Analytic calculus is used to compute intersections among the conics that estimate the tag position. An algorithm computes intersections quality to select the best estimation. Experimental tests are conducted to assess the quality of the proposed strategy. A mobile robot equipped with a reader antenna localizes in 2-D the tags placed in an indoor scenario and reconstructs the map of the environment through a simultaneous localization and mapping (SLAM) algorithm. Note to Practitioners—A localization technology based on passive ultrahigh-frequency (UHF) radio frequency identification (RFID) is an enabling technology for intelligent warehouses, logistics, and retails. For this reason, this work presents a novel method to estimate the tag location with high accuracy. A reader antenna is mounted on an autonomous mobile robot that can move in an indoor or outdoor environment due to a simultaneous localization and mapping (SLAM) algorithm. The motion of the antenna generates a synthetic aperture. The system receives the phase measurements from the RFID tags and generates a distance model through phase unwrapping. In such a way, the possible locations of the tags in the environment are generated, creating conics. The trilateration step is performed analytically, intersecting the obtained conics. The resulting estimations are very accurate and not computation expensive. Therefore, the proposed approach can be employed in any application where localizing objects is fundamental even when reduced computational power is available, e.g., in warehouses where the products are at known heights, or where the items are placed on a fixed infrastructure, such as high-shelves logistics, to produce the inventory of the tagged objects within each shelf.

Journal ArticleDOI
TL;DR: In this paper , two common approaches to two-dimensional (2D) geometry (planar) indoor antennas, namely, broadband CP printed monopole antennas (BCPPMAs).
Abstract: With the rapid changes in wireless communication systems, indoor wireless communication (IWC) technology has undergone tremendous development. Antennas are crucial components of IWC systems that transmit and receive signals within indoor environments. Thus, the development of indoor technology is highly dependent on the development of indoor antennas. However, indoor environments with limited space require the fewest indoor antenna units and the smallest indoor antenna sizes possible. Hence, indoor antennas with compact size and broad applications have become widely preferred. In an IWC system, circularly polarised (CP) antennas are generally important, especially in dense indoor environments, because compared with linearly polarised (LP) antennas, CP antennas reduce polarisation mismatch and multipath losses. This paper combs through the existing studies related to three-dimensional (3D) geometry (nonplanar) or waveguide indoor antennas and the two common approaches to two-dimensional (2D) geometry (planar) indoor antennas, namely, broadband CP printed monopole antennas (BCPPMAs) and broadband CP printed slot antennas (BCPPSAs). The advantages, disadvantages and limitations of previous works are highlighted as well. These research works are summarised, compared and analysed to understand the recent specifications of BCPPMAs and BCPPSAs to generate the most appropriate design structure suitable for current IWC systems.

Journal ArticleDOI
TL;DR: In this paper , the authors proposed an effective channel estimation scheme for frequency selective channel, which is based on the training channel model in urban traffic environment, considering that the practical mm-wave MIMO channel is sparsity and the subcarrier multi-channels have the same sparse structure.
Abstract: In frequency selective channel environment, channel estimation in hybrid precoding millimeter-wave (mmWave) massive multiple input multiple output (MIMO) system is a challenge issue. To solve this problem, we propose an effective channel estimation scheme for frequency selective channel, which is based on the training channel model in urban traffic environment. Considering that the practical mmWave MIMO channel is sparsity and the subcarrier multi-channels have the same sparse structure, we regard the channel estimation problem as the sparse channel recovery, and propose a multipath simultaneous matching tracking estimation method. It is assumed that the noise between the practical channels has a certain correlation, and the noise correlation has an impact on the selection of the optimal atomic support set in the process of channel recovery. Therefore, noise weighting is introduced in our proposed method. The simulation results prove the validity of this proposed method in frequency selective mmWave MIMO channel. Without increasing the complexity of the algorithm, the proposed method can achieve better local performance than the traditional classical methods.

Journal ArticleDOI
TL;DR: In this article , the authors studied the effect of delay spread (DS), the specular multipath components (SMCs), and the impact of dense multipath component (DMCs) on multiple-input/multiple-output (MIMO) system performance in a tunnel environment by considering a Richter's maximumlikelihood (RiMAX)-based estimator.
Abstract: The effect of delay spread (DS), the specular multipath components (SMCs), and the impact of dense multipath components (DMCs) on multiple-input/multiple-output (MIMO) system performance in a tunnel environment are studied by considering a Richter’s maximum-likelihood (RiMAX)-based estimator. The path loss (PL), angular spread, interuser spatial correlation, and capacity of a massive MIMO framework are analyzed at the 3.5-GHz frequency band through a measurement campaign inside a subway tunnel to implement the latest 5G standards. The radio channel consists of a uniform rectangular array of 32 transmitting elements and a uniform cylindrical array of 64 receiving elements with horizontal and vertical polarizations. The power ratio of the DMCs is found to be distance dependent, as the DMCs and SMCs behave differently in tunnels. Moreover, the study shows that the channel capacity, angular spread, and DS are reduced as the distance between the transmitting and receiving antenna arrays increases, whereas the PL exponent increases with the distance. This research highlights the importance of considering spatial characteristics in 5G massive MIMO system models and provides guidelines to enhance the networks’ accuracy in underground mobile communications.

Proceedings ArticleDOI
27 Jun 2022
TL;DR: A device-free respiration detection system, ResFi, utilizing the CSI data from COTS WiFi devices is proposed, which shows an accuracy up to 15% higher than that of the traditional machine-learning methods.
Abstract: Respiration, a vital basis for life, is a key indicator of health status for the human being. Recently, with contact-based devices, some breathing signal detection methods have been proposed, which can achieve high accuracy and signal-to-noise ratio performance. However, these methods require users to be contacted with the devices, leading to a series of problems, such as hindering the movement of users. Therefore, there is an urgent need to call for a contactless solution for respiration detection. With the popularity of indoor WiFi devices, respiration detection with WiFi sensors has drawn a lot of attention. Nevertheless, the multipath effects, which commonly exist in indoor environments, have serious impacts on the propagation of wireless signals, leading to signal attenuation and poor signal quality. Moreover, although the channel state information (CSI) can be readily collected from commercial off-the-shelf (COTS) WiFi devices, the received CSI is distorted due to various offsets introduced during the propagation of the wireless signals and hardware imperfections. In this paper, we try to resolve the challenges mentioned above and propose a device-free respiration detection system, ResFi, utilizing the CSI data from COTS WiFi devices. The final evaluation shows an accuracy of 96.05% for human respiration detection, which is up to 15% higher than that of the traditional machine-learning methods.

Journal ArticleDOI
TL;DR: In this paper , the authors address the channel characterization and modeling issues of RIS-assisted wireless communication systems, which can intelligently manipulate electromagnetic waves by low-cost near passive reflecting elements.
Abstract: Reconfigurable intelligent surfaces (RISs) are 2-D metasurfaces, which can intelligently manipulate electromagnetic waves by low-cost near passive reflecting elements. RIS is viewed as a potential key technology for the sixth-generation (6G) wireless communication systems mainly due to its advantages in tuning wireless signals, thus smartly controlling propagation environments. In this article, we aim at addressing channel characterization and modeling issues of RIS-assisted wireless communication systems. First, the concept, principle, and potential applications of RIS are given. An overview of RIS-based channel measurements and experiments is presented by classifying frequency bands, scenarios, system configurations, RIS constructions, experiment purposes, and channel observations. Then, RIS-based channel characteristics are studied, including reflection and transmission, the Doppler effect and multipath fading mitigation, channel reciprocity, channel hardening, rank improvement, far field, near field, and so on. RIS-based channel modeling works are investigated, including large-scale path loss models and small-scale multipath fading models. Finally, future research directions related to RIS-assisted channels are also discussed.

Journal ArticleDOI
TL;DR: In this paper , the authors present an indoor wireless network planning system using a practical and theoretical approach to estimate the breadth and performance of wireless networks in the form of a new topology with contour presentation.
Abstract: The presence of interference has a significant impact on wireless network connections indoors. Because of the effects of multipath propagation, such as reflection, refraction, and scattering of radio waves by the structure of the building, the sent signal can usually be received in free space or via more than one pathway, and the consequence might be a phenomenon known as multipath fading. For different results, propagation models have been identified, which provide the propagation features of the initial evaluation. There are two types of wireless propagation models: empirical and theoretical models that deal with coverage, overlapping channels, and wireless network performance. The planning system was set out using a practical and theoretical approach. Furthermore, this comparison may aid in determining the accuracy of survey measures in the context of indoor wireless monitoring and provide an estimate of the breadth and performance of wireless networks in the form of a new topology with contour presentation. Layout plan optimization The typical RSSI of a Wi-Fi system ranges from -40 dBm to -55 Dbm, with a power of 17-18 Dbm, and is applied to channels 1 through 11 non-overlapping in the design of networks with multiple APs that are nearby. The new topology represents the optimization outcomes, accompanied by a contour display and dispersed over the region.

Journal ArticleDOI
TL;DR: In this paper , the authors propose and experimentally validate a mechanism using multipath sound twisting to realize real-time high-capacity communication free of signal processing or sensor-scanning.
Abstract: Abstract Speeding up the transmission of information carried by waves is of fundamental interest for wave physics, with pivotal significance for underwater communications. To overcome the current limitations in information transfer capacity, here we propose and experimentally validate a mechanism using multipath sound twisting to realize real-time high-capacity communication free of signal-processing or sensor-scanning. The undesired channel crosstalk, conventionally reduced via time-consuming postprocessing, is virtually suppressed by using a metamaterial layer as purely-passive demultiplexer with high spatial selectivity. Furthermore, the compactness of system ensures high information density crucial for acoustics-based applications. A distinct example of complicated image transmission is experimentally demonstrated, showing as many independent channels as the path number multiplied by vortex mode number and an extremely-low bit error rate nearly 1/10 of the forward error correction limit. Our strategy opens an avenue to metamaterial-based high-capacity communication paradigm compatible with the conventional multiplexing mechanisms, with far-reaching impact on acoustics and other domains.

Journal ArticleDOI
TL;DR: This article presents a cellular long-term evolution signal tracking algorithm implemented by an adaptive multipath estimating delay lock loop (AMEDLL) to achieve carrier phase synchronization and time-of-arrival (TOA) tracking under severe multipath propagation conditions.
Abstract: Positioning with cellular signals has been gaining attention in urban and indoor environments, where global navigation satellite system signals have limited availability due to interference, blockage, or multipath. However, accurate and reliable tracking of cellular signals under highly dynamic urban channel conditions remains a challenging task. This article presents a cellular long-term evolution (LTE) signal tracking algorithm implemented by an adaptive multipath estimating delay lock loop (AMEDLL) to achieve carrier phase synchronization and time-of-arrival (TOA) tracking under severe multipath propagation conditions. The analytical expression of the coherently integrated correlation result over multiple slots with the LTE cell-specific reference signal is derived. A multipath estimator along with a simple yet efficient multipath estimation monitoring approach is developed to estimate the parameters of all detected multipath signals. Several heuristic monitoring criteria based on historical multipath parameter estimations are established to enable adaptive adjustment of the estimated path number. Real LTE signals are collected in an urban environment for the signal tracking performance evaluation. This article presents two case studies with varying levels of multipath effects and signal power to illustrate the effectiveness of the developed signal tracking algorithm. Instead of a TOA truth reference, open-loop carrier phase estimations are used to analyze the TOA tracking error. Our analyses demonstrate that the AMEDLL-based tracking algorithm provides improved TOA estimation accuracy over the existing super-resolution-algorithm-based and delay-lock-loop-based tracking schemes.

Journal ArticleDOI
TL;DR: In this paper , the stochastic modeling for low-cost devices considering the impacts of multipath effects and atmospheric delays is systematically studied, and the results show that the measurement precisions of short baseline and medium-long baseline for the lowcost receiver are worse than zero baseline due to the systematic errors.

Journal ArticleDOI
TL;DR: In this article , a method of improving the diversity and capacity of multiple-input-multiple-output (MIMO) systems in nonisotropic multipath environments by loading a scatterer array is proposed.
Abstract: A method of improving the diversity and capacity of multiple-input-multiple-output (MIMO) systems in nonisotropic multipath environments by loading a scatterer array is proposed. The difference between array diversity and super-resolution imaging is discussed first. The phase differences caused by the “effective space” between adjacent antenna elements are the critical factors of diversity enhancement. The scatterer array, which is made of cross-structure periodically, is placed on top of the antenna array to adjust the phase center of the radiation pattern of each antenna port. By increasing the “equivalent size” of the antenna array, the correlation of part of the adjacent ports in the antenna array is decreased; thus, the array diversity is improved. Through a set of comparative examples, the effectiveness of the scatterer array is clearly demonstrated.

Journal ArticleDOI
TL;DR: This survey first presents the challenges/problems for supporting multipath transmission with possible solutions, and reviews recent research efforts related to the concurrent multipath Transmission Control Protocol (MPTCP) and open research issues in multipath transport protocols.
Abstract: A huge amount of generated data is regularly exploding into the network by the users through smartphones, laptops, tablets, self-configured Internet-of-things (IoT) devices, and machine-to-machine (M2M) communication. In such a situation, satisfying critical quality-of-service (QoS) requirements (e.g., throughput, latency, bandwidth, and reliability) is a large challenge as a vast amount of data travels into the network. Nowadays, strict QoS requirements must be satisfied efficiently in many networked multimedia applications when intelligent multi-homed devices are used. Such devices support the concept of multi-homing. To be precise, they have multiple network interfaces that aim to connect and communicate concurrently with different networking technologies. Therefore, many multipath transport protocols are provided to multi-homed devices, which aim (1) to take advantage of several network paths at the transport layer (Layer-4) and (2) to meet the strict QoS requirements for providing low network latency, higher data rates, and increased reliability. To this end, this survey first presents the challenges/problems for supporting multipath transmission with possible solutions. Then, it reviews recent research efforts related to the concurrent multipath transmission (CMT) protocol and the multipath transmission control protocol (MPTCP). It reviews the latest research efforts by considering (1) how a multipath transport protocol operates (i.e., its functionality); (2) in what type of network; (3) what path characteristics it should consider; and (4) how it addresses various design challenges. Furthermore, it presents some lessons learned and discusses open research issues in multipath transport protocols.