Signal Path Loss Research Articles

Research on Waterway Wireless Propagation Characteristics Based on Channel Measurement: Ship Moving Across vs. Moving Through

Zhang, J.; Li, C.; Shu, X., and Chen, W., 2020. Research on waterway wireless propagation characteristics based on channel measurement: Ship moving across vs. moving through. In: Zheng, C.W.; Wang, Q.; Zhan, C., and Yang, S.B. (eds.), Air-Sea Interaction and Coastal Environments of the Maritime and Polar Silk Roads. Journal of Coastal Research, Special Issue No. 99, pp. 99-104. Coconut Creek (Florida), ISSN 0749-0208.The safety of ship traffic in inland waterway is crucial and relies on wireless communications. Yet previous wireless communication studies have focused on coastal and vehicles on land. This manuscript present measurement and analyses ship-to-boat pontoon campaign investigating the wireless propagation channel at 5.9 GHz in inland waterway. Research explore in particular the effect of ship motion transverse to and parallel to a fixed boat pontoon. And study analyze the effects of line-of-sight and non-line-of-sight conditions, which typify “inland intelligent waterway” scenarios. Beside different motion conditions like moving transverse to and parallel to boat pontoon, research also explore channel metrics such as path loss, small-scale fading, and correlations of signal with ship motion. The research results show that the relative motion of ships in inland intelligent waterway communication cannot be ignored.

Theoretical and Experimental Studies on the Signal Propagation in Soil for Wireless Underground Sensor Networks.

Wireless Underground Sensor Networks (WUSNs), an important part of Internet of things (IoT), have many promising applications in various scenarios. Signal transmission in natural soil undergoes path loss due to absorption, radiation, reflection and scattering. The variability and dynamic of soil conditions and complexity of signal attenuation behavior make the accurate estimation of signal path loss challenging. Two existing propagation models for predicting path loss are reviewed and compared. Friis model does not consider the reflection loss and is only applicable in the far field region. The Fresnel model, only applicable in the near field region, has not considered the radiating loss and wavelength change loss. A new two stage model is proposed based on the field characteristics of antenna and considers four sources of path loss. The two stage model has a different coefficient m in the near field and far field regions. The far field distance of small size antenna is determined by three criteria: 2 D2/λ, 5 D, 1.6 λ in the proposed model. The proposed two stage model has a better agreement with the field experiment data compared to Friis and Fresnel models. The coefficient m is dependent on the soil types for the proposed model in near field region. It is observed from experiment data that the m value is in the range of 0~0.20 for sandy soils and 0.433~0.837 for clayey silt.

THzPrism: Frequency-Based Beam Spreading for Terahertz Communication Systems

With large available bandwidths, Terahertz (THz) band communication has been envisioned as a key technique to satisfy the increasing demand for ultra-high-speed wireless communications. To overcome severe path loss of THz signals, large antenna array based beamforming, i.e., directional communication, is required for THz communications. Beamforming increases distance coverage, but it significantly reduces angular coverage, which severely limits the efficiency and flexibility of THz systems. In this letter, a novel phased array architecture called THzPrism is designed to conduct beamforming for THz systems. The key idea of THzPrism is to insert several true time delay devices in a phased array so as to achieve frequency-based beam spreading. As a result, THzPrism can significantly enlarge angular coverage while maintaining the distance coverage for THz systems. Both theoretical analysis and numerical results are conducted to validate the effectiveness of THzPrism.

Measurement-Based 5G Millimeter-Wave Propagation Characterization in Vegetated Suburban Macrocell Environments

An empirically based analysis of propagation characteristics in two vegetated suburban areas with different types and fractions of vegetation cover in 5G millimeter-wave (mmWave) bands is presented. A basic distance-dependent path loss model with a Gaussian random variance for shadow fading is utilized in accordance with the maximum-power directional and omnidirectional measurement data, therein exploiting significant path loss exponents in the presence of vegetation. In comparison with the existing ITU-R and 3GPP models, the effect of dense-leaved trees on path loss prediction is similar to that of buildings, whereas these standard models are inapplicable for sparse obstacle-line-of-sight (OLoS) links. Consequently, an azimuth-angle-based path loss characterization is proposed considering the antenna pattern, beam misalignment, and blockage effects. Moreover, several composite and cluster-level small-scale channel parameters, such as the number of clusters, delay spread, and angular spread, are extracted. Analysis of the first-arrival cluster in the OLoS setting reveals that forward scattering through foliage is still dominant and is expected to produce a larger azimuth angular spread of the arrival and compact multipath components in the time domain compared with line-of-sight and reflected clusters. The measurement results improve existing 3GPP channel models for suburban macrocell scenarios in mmWave bands.

Development of an Underground Through-Soil Wireless Acoustic Communication System

The practical development of WUSN would benefit numerous applications, including online infrastructure monitoring, earthquake warning systems, and agricultural automation. However, stateof- the-art RF electromagnetic wireless systems are ineffective for communicating through-soil, due to extreme signal path losses from absorption and scattering in soil, even though the typical data requirements for such applications are modest, ranging from tens to hundreds of bps. In contrast, elephants, rodents and a wide variety of insects use acoustic waves for communicating through-soil, suggesting the viability of soil as a communication channel, and of acoustic waves as carriers. In this article, we demonstrate how soil can be used as a communication medium for wireless acoustic digital communication over distances up to 50 m at 20 bps data rates. By leveraging a physical model of the soil channel derived from its identified characteristics, then employing QPSK and OOK modulation and sparse decision feedback equalization schemes, and exploiting well-coupled and matched acoustic sources, wireless digital communication was successful in both laboratory and field experiments, illustrating the viability of sending application- specific data, ranging from binary sensor readings to low-resolution images.

Impact of Relay Location of STANC Bi-Directional Transmission for Future Autonomous Internet of Things Applications

Wireless communication using existing coding models poses several challenges for RF signals due to multipath scattering, rapid fluctuations in signal strength and path loss effect. Unlike existing works, this study presents a novel coding technique based on Analogue Network Coding (ANC) in conjunction with Space Time Block Coding (STBC), termed as Space Time Analogue Network Coding (STANC). STANC achieves the transmitting diversity (virtual MIMO) and supports big data networks under low transmitting power conditions. Furthermore, this study evaluates the impact of relay location on smart devices network performance in increasing interfering and scattering environments. The performance of STANC is analyzed for Internet of Things (IoT) applications in terms of Symbol Error Rate (SER) and the outage probability that are calculated using analytical derivation of expression for Moment Generating Function (MGF). In addition, the ergodic capacity is analyzed using mean and second moment. These expressions enable effective evaluation of the performance and capacity under different relay location scenario. Different fading models are used to evaluate the effect of multipath scattering and strong signal reflection. Under such unfavourable environments, the performance of STANC outperforms the conventional methods such as physical layer network coding (PNC) and ANC adopted for two way transmission.

Effective Capacity Based Power Allocation for the Coexistence of an Integrated Radar and Communication System and a Commercial Communication System

Considerable interest has been shown in the coexistence between airborne radar and commercial communication systems in recent years. In particular, the integrated radar and communication system (IRCS) is promising for the airborne platforms like Unmanned Air Vehicles (UAVs). However, due to fast varying channels caused by high mobility, it is a great challenge for the fusion center to collect detection information within a given delay threshold through the air-to-ground (A2G) communication. Based on slowly varying components of the channel, i.e, target spectrum, power spectral densities of the signal dependent clutters, path loss and shadow fading, this paper considers the problem of power minimization for an IRCS and a base station (BS) coexisting in the same frequency band. The latency bound, latency violation probability (LVP), and channel capacity for the A2G communication to the fusion center are considered based on the effective capacity (EC) theory. The detection performance for radar and the rate requirement of BS user are also taken into account. The power allocation problem is non-convex and formulated to a monotonic optimization problem. Afterward, an efficient heuristic scheduling algorithm with acceptable computational complexity is proposed to solve the formulated problem. Then, the robust power allocation with channel estimation error is considered. Simulation results demonstrate the effectiveness of the proposed heuristic algorithm from the perspectives of the total transmit power, EC, and LVP of the IRCS.

Hybrid Beamforming for 5G and Beyond Millimeter-Wave Systems: A Holistic View

Millimeter-wave (mm-wave) communication is a key technology for future wireless networks. To combat significant path loss and exploit the abundant mm-wave spectrum, effective beamforming is crucial. Nevertheless, conventional fully digital beamforming techniques are inapplicable, as they demand a separate radio frequency (RF) chain for each antenna element, which is costly and consumes too much energy. Hybrid beamforming is a cost-effective alternative, which can significantly reduce the hardware cost and power consumption by employing a small number of RF chains. This paper presents a holistic view on hybrid beamforming for 5G and beyond mm-wave systems, based on a new taxonomy for different hardware structures. We take a pragmatic approach and compare different proposals from three key aspects: 1) hardware efficiency, i.e., the required hardware components; 2) computational efficiency of the associated beamforming algorithm; and 3) achievable spectral efficiency, a main performance indicator. Through systematic comparisons, the interplay and trade-off among these three design aspects are demonstrated, and promising candidates for hybrid beamforming in future wireless networks are identified.

RIS-Assisted Coverage Enhancement in Millimeter-Wave Cellular Networks

The use of millimeter-wave (mmWave) bandwidth is one key enabler to achieve the high data rates in the fifth-generation (5G) cellular systems. However, mmWave signals suffer from significant path loss due to high directivity and sensitivity to blockages, limiting its adoption within small-scale deployments. To enhance the coverage of mmWave communication in 5G and beyond, it is promising to deploy a large number of reconfigurable intelligent surfaces (RISs) that passively reflect mmWave signals towards desired directions. With this motivation, in this work, we study the coverage of an RIS-assisted large-scale mmWave cellular network using stochastic geometry, and derive the peak reflection power expression of an RIS and the downlink signal-to-interference ratio (SIR) coverage expression in closed forms. These analytic results clarify the effectiveness of deploying RISs in the mmWave SIR coverage enhancement, while unveiling the major role of the density ratio between active base stations (BSs) and passive RISs. Furthermore, the results show that deploying passive reflectors are as effective as equipping BSs with more active antennas in the mmWave coverage enhancement. Simulation results confirm the tightness of the closed-form expressions, corroborating our major findings based on the derived expressions.

Dependability of Directional Millimeter Wave Vehicle-to-Infrastructure Communications

Vehicle-to-infrastructure (V2I) communication is an important enabler for intelligent transportation and rail traffic management systems, which are expected to provide significant road traffic safety and efficiency enhancements. Such systems require a level of dependability of the wireless communication link that can be hard to support by state-of-the-art technologies. Transmissions in the millimeter wave (mmWave) band have the potential to provide sufficient bandwidth to support not only traffic management services, but additionally also web and entertainment applications for car and train passengers. mmWave transmissions require directional antennas at the transmitter and/or receiver to compensate for the significant pathloss and to achieve a practically acceptable maximum coupling loss. Such directional communication is feasible in V2I scenarios, because the mobility of users is confined to streets and roads. In this article, we discuss the dependability of directional mmWave V2I communications under two-ray fading conditions. We review methods for enhancing the dependability of the communication link by exploiting macroscopic spatial diversity and by mitigating interference from other transmitters. We furthermore provide guidelines for a dependable system design under two-ray fading and identify open research questions in this context.

Clustering Based Hybrid Precoding Design for Multi-User Massive MIMO Systems

Hybrid precoding has been recognized as a promising technology to combat the path loss of millimeter-wave signals in massive multiple-input multiple-output (MIMO) systems. However, due to the joint optimization of the digital and analog precoding matrices as well as extra constraints for the analog part, the hybrid precoding design is still a tough issue in current research. In this paper, we adopt the thought of clustering in unsupervised learning and provide design schemes for fully-connected hybrid precoding (FHP) and adaptively-connected hybrid precoding (AHP) in multi-user massive MIMO systems. For FHP, we propose the hierarchical-agglomerative-clustering-based (HAC-based) scheme to explore the relevance among radio frequency (RF) chains in the optimal hybrid precoding design. The similar RF chains are merged into an individual when insufficient RF chains are available. For AHP, we propose the modified-K-means-based (MKM-based) scheme to explore the relevance among antennas. The similar antennas are supported by the same RF chain to make full use of the flexible connection in AHP. Particularly, in the proposed MKM-based AHP design, the clustering centers are updated by alternating-optimum-based (AO-based) scheme with a specific initialization method, which is capable to independently provide feasible sub-connected hybrid precoding (SHP) design with quick convergence. Simulation results highlight the superior spectrum efficiency of the proposed HAC-based FHP scheme, and the high power efficiency of the proposed MKM-based AHP scheme. Moreover, all the proposed schemes are clarified to effectively handle the inter-user interference and outperform the existing work.

A Smart Insect Pest Detection Technique With Qualified Underground Wireless Sensor Nodes for Precision Agriculture

Wireless underground sensor networks are the new area of research. It is widely used in many engineering applications, from smart irrigation to security and precision agriculture. Some of the application areas of wireless underground sensor networks are underground with space, such as tunnel, cave, and so on, while some consist of no spaced underground solid areas as well. In this context, wireless underground sensor networks have recently become very important for precision agriculture purposes. In this paper, a smart insect pest detection technique with qualified underground wireless sensor nodes for precision agriculture has been investigated with a mathematical simulation model. In a simulated smart technique, insect pest detection is assumed to be carried out with a qualified acoustic sensor. In order to evaluate the performance of the underground network structure, the received signal strength and path loss parameters are examined. As the depth distance increases, the increase in path loss of communication has been revealed. The obtained performance evaluation result reveals the need for signal transmission with different transmitter power for depth-based communication in wireless underground sensor networks.

Statistics-Assisted Beam Training for MmWave Massive MIMO Systems

Combined with massive multiple-input multiple-output technology, beamforming can effectively compensate the high path-loss of millimeter-wave signals and hence improve the received power at user equipment (UE). In order to establish the beam alignment between base station (BS) and UE, beam training (BT) is required to select appropriate beamforming vectors at both BS and UE sides. In general, a good trade-off between beamforming gain and BT overhead is critical to enhance the system performance. In this letter, a statistics-assisted beam training (SA-BT) scheme is proposed to reduce the BT overhead. Specifically, BS scans the candidate beams according to the descending order of the utilization frequency of each beam. Meanwhile, the BT procedure is finished when the beamforming gain at UE exceeds the pre-defined threshold. The theoretical analyses and the numerical simulations prove that the proposed scheme can reduce the BT overhead and hence improve the spectral efficiency significantly compared with the existing methodologies.

Efficient localization of target in large scale farmland using generalized regression neural network

SummaryAlthough simple to implement, the traditional trilateration technique is generally associated with significant location estimation errors because of highly nonlinear relationship between Received Signal Strength Indicator (RSSI) and distance. In case of agricultural farmland, there is always noise uncertainty in the RSSI measurements because of signal propagation issues such as NLOS, multipath propagation, and reflection. In the context of such environmental dynamicity, the localization algorithm must be efficient in terms of Localization Accuracy and Execution Speed to provide real‐time performance. The Generalized Regression Neural Network (GRNN) is a noniterative highly parallel neural architecture with the capability to get trained quickly using very few training samples. This paper introduces a range free GRNN localization algorithm as an alternative to the traditional range‐based trilateration technique for a large scale wheat farmland. This paper also presents the modified Optimal Fitted Parametric Exponential Decay Model (OFPEDM)‐based signal path loss model to deal with the issue of environmental dynamicity. The evaluation of localization performance of the trilateration and the proposed GRNN‐based approaches is carried out with the help of Wireless Sensor Network (WSN) using three path loss models, namely, Log Normal Shadow Fading (LNSM), Original OFPEDM, and proposed Modified OFPEDM. For all these implementations, the proposed GRNN algorithm demonstrates superior localization performance (localization accuracy of the order of few centimeters) over traditional trilateration irrespective of nonlinear system dynamics, path loss model, and environmental dynamicity. The execution speed of the proposed algorithm is of the order of few milliseconds.

Analytical modeling of UASNs for fractional power control algorithm

In Underwater Acoustic Sensor Networks (UASNs), the path loss of signal is serious due to the harsh underwater environment. Fractional power control algorithm has been widely used for the compensation of path loss. However, the randomness of underwat

Indoor 3-D RT Radio Wave Propagation Prediction Method: PL and RSSI Modeling Validation by Measurement at 4.5 GHz

This article introduces an efficient analysis of indoor 4.5 GHz radio wave propagation by using a proposed three-dimensional (3-D) ray-tracing (RT) modeling and measurement. The attractive facilities of this frequency band have significantly increased in indoor radio wave communication systems. Radio propagation predictions by simulation method based on a site-specific model, such as RT is widely used to categorize radio wave channels. Although practical measurement provides accurate results, it still needs a considerable amount of resources. Hence, a computerized simulation tool would be a good solution to categorize the wireless channels. The simulation has been performed with an in-house developed software tool. Here, the 3-D shooting bouncing ray tracing (SBRT) and the proposed 3-D ray tracing simulation have been performed separately on a specific layout where the measurement is done. Several comparisons have been performed on the results of the measurement: the proposed method, and the existing SBRT method simulation with respect to received signal strength indication (RSSI) and path loss (PL). The comparative results demonstrate that the RSSI and the PL of proposed RT have better agreements with measurement than with those from the conventional SBRT outputs.

Multi-Tb/s-per-Fiber Coherent Co-Packaged Optical Interfaces for Data Center Switches

Co-packaging of optical and electronic interfaces inside data center switches has been proposed to reduce the system-level power consumption and support higher density, higher capacity optical links. However, co-locating electronics and optics increases optical losses and exposes lasers, (de)multiplexers and other components to temperature fluctuations. We propose a design for co-packaged interfaces using coherent detection and wide-passband (de)multiplexers to increase the total bit rate per fiber in the presence of demultiplexer center frequency shifts up to ±150 GHz. We compare direct and coherent detection systems within this architecture and demonstrate that unamplified coherent links can provide over 20 dB higher loss budget than direct detection links at 400 Gb/s per fiber. Moreover, coherent links can offer far higher bit rates per fiber. For example, in the presence of (de)multiplexer center frequency shifts of up to ±150 GHz, DP-QPSK links can scale to over 5 Tb/s per fiber, while four pulse amplitude modulation (PAM) links are optical bandwidth limited to ~400 Gb/s per fiber. We quantify signal path loss and optical signal-to-noise ratio budgets when optical amplifiers, limited to eye-safe output powers, are used to compensate for losses of fibers or optical switches. While the loss and SNR budgets of direct detection links may be improved by optical amplifiers, these systems cannot scale to high bit rates per fiber because large channel spacings are required to accommodate (de)multiplexer center frequency shifts. For example, amplified 4-PAM links can scale to less than 1.3 Tb/s per fiber, while amplified DP-QPSK links can scale to greater than 12.8 Tb/s per fiber.

Optimal Haptic Communications Over Nanonetworks for E-Health Systems

A Tactile Internet-based nanonetwork is an emerging field that promises a new range of e-health applications, in which human operators can efficiently operate and control devices at the nanoscale for remote-patient treatment. A haptic feedback is inevitable for establishing a link between the operator and unknown in-body environment. However, haptic communications over the terahertz band may incur significant path loss due to molecular absorption. In this paper, we propose an optimization framework for haptic communications over nanonetworks, in which in-body nanodevices transmit haptic information to an operator via the terahertz band. By considering the properties of the terahertz band, we employ Brownian motion to describe the mobility of the nanodevices and develop a time-variant terahertz channel model. Furthermore, based on the developed channel model, we construct a stochastic optimization problem for improving haptic communications under the constraints of system stability, energy consumption, and latency. To solve the formulated nonconvex stochastic problem, an improved time-varying particle swarm optimization algorithm is presented, which can deal with the constraints of the problem efficiently by reducing the convergence time significantly. The simulation results validate the theoretical analysis of the proposed system.

An Efficient 3-D Ray Tracing Method: Prediction of Indoor Radio Propagation at 28 GHz in 5G Network

Millimeter wave technology will be dominating the fifth-generation networks due to the clear advantage of higher frequency bands and hence wider spectrum. In this paper, the indoor radio wave propagation at 28 GHz is studied by developing an efficient three-dimensional ray tracing (ETRT) method. The simulation software based on the ETRT model has been verified by measurement data. The received signal strength indication and path loss have shown significant agreement between simulation and measurement. Compared with the conventional shooting bouncing ray tracing method, the proposed ETRT method has better agreement with measurement data.

3-D Deployment Optimization for Heterogeneous Wireless Directional Sensor Networks on Smart City

The development of smart cities and the emergence of three-dimensional (3-D) urban terrain data have introduced new requirements and issues to the research on the 3-D deployment of wireless sensor networks. We study the deployment issue of heterogeneous wireless directional sensor networks in 3-D smart cities. Traditionally, studies on the deployment problem of WSNs focus on omnidirectional sensors on a 2-D plane or in full 3-D space. Based on 3-D urban terrain data, we transform the deployment problem into a multiobjective optimization problem, in which objectives of Coverage, Connectivity Quality, and Lifetime, as well as the Connectivity and Reliability constraints, are simultaneously considered. A graph-based 3-D signal propagation model employing the line-of-sight concept is used to calculate the signal path loss. Novel distributed parallel multiobjective evolutionary algorithms (MOEAs) are also proposed. For verification, real-world and artificial urban terrains are utilized. In comparison with other state-of-the-art MOEAs, the novel algorithms could more effectively and more efficiently address the deployment problem in terms of optimization performance and operation time.