Radio Propagation Research Articles

Novel communication system for buried water pipe monitoring using acoustic signal propagation along the pipe

PurposeWireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.Design/methodology/approachAn acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.FindingsWith predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.Research limitations/implicationsAlthough an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.Originality/valueThis paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.

Methods of computer modeling of electromagnetic field propagation in urban scenarios for Internet of Things

Abstract The paper investigates software solutions to simulate radio waves propagation in urban environment, specifically for the context of the Internet of Things (IoT). The purpose of the study is to provide a comprehensive guide for utilizing the Altair Feko software to obtain a detailed representation of the IoT network, its associated parameters and how they relate to the modeling of electromagnetic fields. It is beneficial to simulate the network during the design stage to obtain valuable data and make necessary adjustments. The key features of a Sigfox or other low power IoT network can be obtained by simulation, enabling an evaluation of the network design prior to its actual implementation. Given the growing demand for IoT devices and networks, researching the optimal design and performance of such networks is of great importance. This underscores the need for continuous exploration of effective methods to achieve efficient design and performance of IoT networks.

The Application of 5G Wireless Communication in Maritime Environment

Recently, 5G wireless communication have been rapidly adopted for maritime applications. As a result, significant progress has been made in the ocean digitalization. 5G features with low latency, high reliability, and a large bandwidth, which satisfies the requirements of maritime applications. Due to significant differences between land and marine radio propagation environments, the maritime communication encounters a large challenge for providing maritime users with reliable data communication service. In order to solve the abovementioned challenge, we designed a maritime 5G terminal and tested it on an unmanned surface vehicle (USV) in the Lanyue Lake of Zhejiang Ocean University. The test data were collected, and the corresponding data analysis are presented, which includes signal strength, signal reception quality, upload and download data rate. The received signal level (RSL) and transmission data rate obtained by the maritime 5G terminals demonstrate great potential of meeting the communication requirements of the maritime users. It is also can be found that the RSL and the data transmission rate of the maritime 5G can be used for the remote control of the unmanned ships, with the signal strength at sea up to -89.45 dBm, and maximum rate up to 226 Mbps.

Energy-Efficient Joint Collaborative and Passive Beamforming for Intelligent-Reflecting-Surface-Assisted Wireless Sensor Networks

Intelligent reflecting surface (IRS) provides a promising technology that can improve the energy efficiency of wireless communications, by building the controllable wireless propagation environment with the utilization of massive passive reflecting elements. Motivated by this, we apply the IRS to assist the data collection based on collaborative beamforming in Wireless Sensor Networks (WSNs). With the objective to maximize the network lifetime, we present an energy efficient joint collaborative and passive beamforming design for an IRS-assisted WSN, which jointly optimizes the beamforming vector for all nodes and phase shifts for IRS’s reflecting elements. To efficiently resolve the joint optimization problem, we develop a penalty dual decomposition (PDD) based algorithm combined with augmented Lagrangian method, penalty-based method and block coordinate descent algorithm, which decomposes the joint optimization problem into four simplified subproblems. Especially in solving IRS’s phase shifts optimization subproblem, we formulate this subproblem as a quadratically constrained quadratic programming (QCQP) problem and further propose a low computational complexity approximate iteration algorithm to resolve this QCQP problem, which iteratively linearizes this QCQP problem to a sequence of approximate programming with linear equality constraints, whose closed-form solution is presented. Theoretical analysis indicates the proposed algorithm can converge to a KKT solution. Simulation results indicate that the IRS-assisted design and proposed algorithm improve the energy efficiency and prolong the network lifetime as compared to alternative algorithms.

Fundamental Limits of Intelligent Reflecting Surface Aided Multiuser Broadcast Channel

Intelligent reflecting surface (IRS) has recently received significant attention in wireless networks owing to its ability to smartly control the wireless propagation through passive reflection. Although prior works have employed the IRS to enhance the system performance under various setups, the fundamental capacity limits of an IRS aided multi-antenna multi-user system have not yet been characterized. Motivated by this, we investigate an IRS aided multiple-input single-output (MISO) broadcast channel by considering the capacity-achieving dirty paper coding (DPC) scheme and dynamic beamforming configurations. We first propose a bisection based framework to characterize its capacity region by optimally solving the sum-rate maximization problem under a set of rate constraints, which is also applicable to characterize the achievable rate region with the zero-forcing (ZF) scheme. Interestingly, it is rigorously proved that dynamic beamforming is able to enlarge the achievable rate region of ZF if the IRS phase-shifts cannot achieve fully orthogonal channels, whereas the attained gains become marginal due to the reduction of the channel correlations induced by smartly adjusting the IRS phase-shifts. The result implies that employing the IRS is able to reduce the demand for implementing dynamic beamforming. Finally, we analytically prove that the sum-rate achieved by the IRS aided ZF is capable of approaching that of the IRS aided DPC with a sufficiently large IRS in practice. Simulation results shed light on the impact of the IRS on transceiver designs and validate our theoretical findings, which provide useful guidelines to practical systems by indicating that replacing sophisticated schemes with easy-implementation schemes would only result in slight performance loss.

Ergodic Capacity Analysis of IRS Aided Wireless-Powered Relay Communication Network

The intelligent reflecting surface (IRS) can smartly provide supplementary links to improve the wireless propagation environment between the base station and the users. Due to the randomness of user distribution and the limitations of IRS deployment location, it is difficult to guarantee that the propagation loss of all the links constructed by IRS to users at any location can be efficiently compensated. In this paper, a wireless-powered device with ambient backscatter and active transmission acts as a relay to assist in forwarding the IRS reflected signals to extend coverage in the energy constrained conditions. The system ergodic capacity of the proposed model is characterized by deriving the approximate analytical expressions. Furthermore, two types of mode selection mechanisms, namely hard-threshold and soft-threshold for the wireless-powered relay are designed according to the statistical analysis to enhance appropriateness for surrounding signal environment. The accuracy of the theoretical analysis expressions is verified by Monte Carlo simulations. The numerical results show that the proposed model surpasses the scenarios in the case of IRS direct connection, standalone active transmission or backscatter, and the soft-threshold scheme can choose the optimal communication mode in different environments.

Multi-Agent Reinforcement Learning Resources Allocation Method Using Dueling Double Deep Q-Network in Vehicular Networks

The communication between vehicle-to-vehicle (V2V) with high frequency, group sending, group receiving and periodic lead to serious collision of wireless resources and limited system capacity, and the rapid channel changes in high mobility vehicular environments preclude the possibility of collecting accurate instantaneous channel state information at the base station for centralized resource management. In addition, road and traffic safety have very strict requirements for low-latency, high-reliability communication, and information transmission is only valuable within a certain range, and requires timeliness. For the Internet of Vehicles (IoV), it is a fundamental challenge to achieve low latency and high reliability communication for real-time data interaction over short distances in a complex wireless propagation environment, as well as to attenuate and avoid inter-vehicle interference through a reasonable spectrum allocation. To solve the above problems, this paper proposes a resource allocation (RA) method using dueling double deep-Q network reinforcement learning (RL) with low-latitude fingerprints and soft-update architecture (D3QN-LS) while constructing a multi-agent model based on a Manhattan grid layout urban virtual environment, with communication links between V2V links acting as agents to reuse vehicle-to-infrastructure (V2I) spectrum resources. These agents work in concert, interact with the environment, receive appropriate observations, rewards, and ultimately learn to improve power and spectrum allocation to provide a better entertainment experience and safer driving environment for users. We also address the shortcomings in existing literature studies. Firstly, the low upper limit of transmitted data volume; Secondly, the artificial assumption that the spectrum is consistent with the number of V2V links, which is insufficient for future applications in spectrum shortage sections. We accordingly extend the amount of transmitted data while adding a scenario where the spectrum resources are relatively short, i.e., the number of V2V links is significantly larger than the amount of spectrum. Experimental results show that with proper training mechanism and reward function construction, multiple intelligence can cooperate effectively. Therefore, the total link capacity of the V2I link and the success rate of periodic security information transmission are further improved.

Feasibility study of eigenmode propagation through 2D models of vegetation

PurposeThis study aims to model and investigate low-loss wave-propagation modes across random media. The objective is to achieve better channel properties for applying radio links through random vegetation (e.g. forest) using a beamforming approach. Thus, obtaining the link between the statistical parameters of the media and the channel properties.Design/methodology/approachA beamforming approach is used to obtain low-loss propagation across random media constructed of long cylinders, i.e. a simplified two dimensional (2D) model of agroforests. The statistical properties of the eigenmode radio wave propagation are studied following a Monte Carlo method. An error quantity is defined to represent the robustness of an eigenmode, and it is shown that it follows a known Lognormal statistical distribution, thereby providing a base for further statistical investigations.FindingsIn this study, it is shown that radio wave propagation eigenmodes exist based on a mathematical model. The algorithm presented can find such modes of propagation that are less affected by the statistical variation of the media than the regular beams used in radio wave communication techniques. It is illustrated that a sufficiently chosen eigenmode waveform is not significantly perturbed by the natural variation of the tree trunk diameters.Originality/valueAs a new approach to obtain low-loss propagation in random media at microwave frequencies, the presented mathematical model can calculate scattering-free wave-propagation eigenmodes. A robustness quantity is defined for a specific eigenmode, considering a 2D simplified statistical forest example. This new robustness quantity is useful for performing computationally low-cost optimization problems to find eigenmodes for more complex vegetation models.

POWER SUPPLY OF RING ANTENNA USING DIRECTIONAL COUPLERS

Context. The circular polarization of radio waves is used in various electronic systems. This includes, for example, space communications stations, some radio relay communication systems, radar stations, data transmission systems and others. The characteristics of radio wave propagation are studied by using electromagnetic waves separated by circular orthogonal polarization in radiomonitoring and radiocontrol systems. Compared to other antenna types, circularly polarized antennas, such as rings, have superior design simplicity and excellent electrodynamics properties.
 Objective. The objective of this study is to analyse the characteristics and application of directional microstrip couplers for supplying power to ring antennas.
 Method. To better the performance of microstrip ring antennas, the reasons for their limited operating frequency range are analysed. These causes include the frequency-dependent parameters of the coupler, errors in calculating the directional coupler circuit, and radiation from asymmetric strip lines. To understand how supply lines, affect antenna characteristics, correlations between radiation fields determined in both its coordinate system and that of the primary axis are taken into account.
 Results. An analysis of the dependence graphs of the main characteristics of ring microstrip antennas with intricate power supply circuits for directional couplers and comparison with similar characteristics for simple circuits revealed that the shape of the radiation pattern in the higher radiation hemisphere became symmetrical about the axis, especially when symmetrically supplying the ring with branch-line couplers. The frequency band has also widened, at which there was an acceptable degree of deviation in the ellipticity coefficient from unity.
 Conclusions. The simulation results of microstrip ring antennas with power lines connected to directional couplers of different types showed that supplying the ring antenna with electricity via the directional coupler ensures circular polarization for the emitted electromagnetic waves. Additionally, the range of operating frequencies where there is only a small discrepancy in ellipticity coefficient remains at an acceptable level of –3 dB is quite broad. By utilizing directional branch-line couplers to power a ring antenna, it is possible to simultaneously emit both right and left circularly polarized waves with the same antenna.

Investigating a Solar Wind Stream Interaction Region using Interplanetary Spacecraft Radio Signals: A Magnetohydrodynamic Simulation Study

Stream interaction regions (SIRs) are spiral heliospheric structures that arise at the interface between fast and preceding slow solar wind regions. SIR enhancements of density and magnetic field intensity, often with magnetic polarity inversion, are potentially geoeffective and therefore important in the analysis of space weather. We studied an MHD heliospheric simulation containing a well-defined SIR using a new instrument concept based on trans-heliospheric radio sensing: Faraday Effect Tracker of Coronal and Heliospheric structures (FETCH). FETCH uses line-of-sight radio propagation techniques to measure Faraday rotation and electron column density. Analysis of the simulated FETCH observations clearly demonstrated density and magnetic field enhancements, and magnetic polarity reversal, all of which were confirmed in Wind spacecraft measurements at 1 au. FETCH provided 4.5–5.7 days lead times for predicting the arrival of SIR features at Earth. The SIR radial speed was estimated to be 350–390 km s−1. These initial results hold promise that FETCH will be valuable in detecting and characterizing the inner heliosphere SIR properties well ahead of their presentation in the local geospace environment.

A novel relay placement method for smart energy IoT systems in offices with genetic algorithm

<p>Smart energy in large offices and organizations is an important research area of the Internet of Things (IoT). The energy efficiency of buildings is vital for the environment and global sustainability. To achieve satisfactory performance for this goal, WiFi access point (AP) indoor coverage is of high importance. As it costs a lot to add more WiFi to have good coverage in all parts of the office’s buildings, we consider relay node (RN) instead of adding more APs. So in this paper, we propose a novel RN placement in order to improve the indoor coverage of offices considering the signal attenuation using a path-loss model as the main measure for determining positions. The main problem is the placement of these RNs and the required number of them by considering existing APs. At first, we obtain the radio propagation model parameters by considering the data that are collected from the AP. Then based on these parameters, the proposed solution uses a genetic algorithm (GA) for RN placement optimization problem. The experimental results display the effectiveness of the proposed solution for the RN placement problem.</p>

ED based spectrum sensing over IRS-assisted Rayleigh-FTR fading channels

A recent study has revealed that incorporating intelligent reflecting surfaces (IRS) into wireless systems improves their performance within various signal propagation conditions. This research paper focuses on evaluating the spectrum-sensing abilities of cognitive radio in wireless environments enhanced by IRS technology. To achieve this, the paper develops a statistical model to describe the connections between the primary user (PU) and IRS, as well as between IRS and the secondary user (SU). This model calculates a precise approximation of the probability density function (PDF) of the end-to-end instantaneous signal-to-noise ratio (SNR). The SNR considers both the PU-to-IRS link, which follows a Rayleigh fading distribution, and the IRS-to-SU link, which follows an FTR fading distribution. By utilizing this PDF distribution, the paper derives analytical expressions for the average probability of detection (APD) for single and cooperative secondary users. These APD expressions are then employed to establish the exact closed-form expression for the average area under the receiver operating characteristics (AUC), system throughput, and transmission probability of the SU. To validate these theoretical findings, the paper conducts Monte Carlo simulations. The results from these simulations indicate an improved detection probability when operating in an IRS-enhanced wireless propagation environment. Consequently, the study suggests that incorporating IRS technology can significantly enhance the reliability of communication systems based on cognitive radio principles.

Effect of spacecraft attitude on radio wave polarization measurements for the radio Receiver instrument on Swarm-E

The characteristics of a polarized radio wave detected by an antenna onboard a spacecraft depend on the relative positions of the transmitting source and the spacecraft, the orientation of the satellite antenna with respect to the wave propagation direction, the electric field of the incident wave, and the properties of the medium traversed by the wave. Precise knowledge of the radio wave propagation direction and the receiver antenna orientation is needed for resolving the received signal properties. In this work, the focus is on the coordinated experiments between the Radio Receiver Instrument (RRI) on Swarm-E and the Natural Resources Canada Ottawa transmitter (45.4°N, 75.6°W). Three experiments, in which the RRI boresight was along the ram (13 December 2017), nadir (20 December 2017) and slew-to-target (21 December 2017) directions were selected for detailed investigations and comparisons. The deviation of the RRI boresight direction from the propagation direction of the wave vector was up to 10° in the slewed pass and varied between 0° and 180° in the two other passes. The effects of the antenna pointing direction were pronounced in the observed powers on each dipole and affected the observed (apparent) polarization characteristics. The observations were not sufficient for describing the polarization state of the original signal during one third of the RRI-ram experiment when only one dipole was receiving the signal with optimal geometry. The methods developed lay the foundation for mitigating the attitude effects to determine the true polarization characteristics of the radio wave.

Acceleration of Tensor Interpolation-Based Radio Map Estimation

The radio map of wireless communications should be surveyed in advance when installing base stations to efficiently utilize radio waves. Generally, this is calculated using radio wave propagation simulation. Because the simulation is time-consuming, a tensor-rank minimization-based interpolation method has been proposed as fast method. However, this method interpolates the radio map using an iterative algorithm. The number of iterations required for further acceleration should be reduced; therefore, we propose a tensor interpolation using rank minimization that considers the characteristics of radio wave propagation. Furthermore, we proved that the proposed method could interpolate with fewer iterations than the existing method.

An Entropy Weight‐Based Method for Path Loss Predictions for Terrestrial Services in the VHF and UHF Bands

AbstractVHF and UHF are widely used frequency bands, and accurate path loss prediction in these bands is of great significance. In order to improve the prediction accuracy and stability of radio wave propagation, we propose a combined modeling method based on the entropy weight method. This method assigns appropriate weights to the predicted values of sub‐models using entropy, and calculates the final predicted value through weighted aggregation. To validate the feasibility of our proposed method, we conduct modeling using data from Denver, Colorado. We compare our method with the ITU‐R models and a model established using the coefficient of variation method. The results demonstrate that our proposed model outperforms the compared models. Specifically, the root‐mean‐square error (RMSE) of our proposed model is reduced by 5.94 and 5.51 dB compared to the ITU‐R P.1546 and 2001 models, respectively. Moreover, our proposed model exhibits better stability than the ITU‐R models. We also use the improvement percentage (γ) to evaluate the degree of improvement of our model over the sub‐models, which is 49.13% and 47.86% for the ITU‐R P.1546 and 2001 models, respectively. Additionally, by comparing the RMSE and absolute error, we find that the entropy weight‐based method outperforms the coefficient of variation‐based method. This research demonstrates the superiority of the entropy weight‐based modeling method, providing a valuable channel modeling approach for path loss prediction and supporting the regional assimilation of radio propagation prediction methods.

Coverage Improvements for Sub-Terahertz Systems Under Shadowing Conditions

Radio propagation in the millimeter wave and sub-terahertz domain is heavily affected by shadowing conditions. The communication link is blocked without any additional technical means being used. Coverage improvements can be provided by using reflectors, RIS arrays, and repeaters to direct radio waves around corners or obstacles. These concepts show different performance and complexity levels affecting their network deployment. This paper investigates the achievable radio range or the received power to compare specific deployment concepts under realistic propagation conditions. Overall, the repeater solution provides either the largest radio range or the lowest necessary total transmit power compared to reflectors or RIS arrays and, thereby, is the most sustainable approach. A RIS array requires an additional centralized signal processing capacity for calculating optimized RIS settings and results in the highest level of network deployment complexity.

Tracking multiple dynamic objects by a combination of laser ranging and UHF RFID phase information

Radio Frequency Identification (RFID) achieves the identification of objects through electromagnetic waves and has wide applications in many areas. The system reports a list of tags in proximity without any knowledge about distance or bearing of the object. This paper presents an approach to integrate RFID phase and laser range information for the tracking of dynamic objects in an environment. The proposed system determines locations of objects by comparing the velocities estimated from two different systems. In particular, the laser range data is segmented into clusters using DBSCAN (Density-based spatial clustering of applications with noise). We compute the radial velocities of these clusters and compare them to the radial velocity estimated from RFID phase difference. The particle filtering is used to fuse the ambiguous phase measurements and to track moving objects with multiple hypothesis. The proposed approach uses the commercial off the shelf RFID devices and does not require the modelling of radio signal propagation. Experiments were conducted with a SCITOS G5 robot to verify the feasibility of the approach. The results showed that our approach can achieve a positioning accuracy of approx. 0.37 meters in a complex environment.

Energy-Efficient Service-Aware Multi-Connectivity Scheduler for Uplink Multi-Layer Non-Terrestrial Networks

This paper introduces the concept of energy efficiency (EE) in the uplink with the capability of multi-connectivity (MC) in a multi-orbit non-terrestrial network (NTN), where user terminals (UTs) can be simultaneously served by more than one satellite to achieve higher peak throughput at reduced energy consumption. This concept also considers the service classification of the users, so that network dimensioning is performed in order to satisfy the quality of service (QoS) requirement of users. MC can increase throughput, but this entails increased power consumption at user terminal for uplink transmissions. To this end, an energy-efficient service-aware multi-connectivity (EE-SAMC) scheduling algorithm is developed in this paper to improve the EE of uplink communications. EE-SAMC uses available radio resources and propagation information to intelligently define a dynamic resource allocation pattern, that optimally routes traffic so as to reduce the energy consumption at the UT while ensuring QoS is maximized. EE-SAMC is designed based on the formulation of a non-convex combinatorial problem, it is solved in two ways involving firstly an optimization solution and secondly a heuristic approach. The effectiveness of EE-SAMC is compared with random allocation, round robin and heuristic schedulers in terms of EE, throughput and delay; EE-SAMC outperforms all schedulers.

Frequency extension of radio propagation model using fine-tuning

Frequency extension of radio propagation model using fine-tuning

Prediction of indoor radio propagation using deep neural network

Prediction of indoor radio propagation using deep neural network