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Prior Artificial Magnetic Conductor (AMC) designs using Genetic Programming (GP) showed that GP-based designs are competitive and often exceed those based on human expertise. However, the resultant...

In this paper, we report the results of a field measurement campaign carried out inside a pedestrian tunnel at 24 GHz in two conditions, namely, empty tunnel scenario and busy tunnel scenario with pedestrian movement. The experiment measures the fading effects of various groups of pedestrian crowds using directional antennas at the transmitter and receiver for millimeter-wave radio communications. Having presented and analyzed the measurement data in several diverse scenarios, we have further investigated human scattering effects in the crowded pedestrian tunnel and performed ray-tracing simulation for an empty pedestrian tunnel condition. Because tunnel is an enveloped scenario that is not bound by any geographic areas, the results of this study can be applied to a wider scenario like other pedestrian tunnels across the globe. Above all, these findings contribute towards ensuring wireless connectivity for everyone even in a remote scenario like underground passages.

Genetic programming (GP) is developed to design an antenna array with new topologies resulting in improved performance. Three elements of a coplanar waveguide continuous transverse stub (CPW-CTS) antenna are synthesized and optimized by GP. These antenna elements are placed in series to create a 3-element frequency scanning linear array. The fitness function used to design the CPW-CTS elements accounts for impedance bandwidth, radiation pattern, cross polarization, and transmission coefficient. Simulation results are verified experimentally. The GP designed CPW-CTS antenna array was able to achieve nearly 4 times the bandwidth of a conventional CPW-CTS array design. The GP designed array maintains the array's gain when compared with the published CPW-CTS antenna array design.

We study the problem of finding the minimum energy beamforming that satisfies the users' signal-to-noise ratio requirements. Traditional transform based beamforming uses heuristics to determine the radiation pattern first, and then calculates the beamforming vector. Recent optimization based beamforming optimizes the beamforming vector directly and greatly outperforms the transform based beamforming. However, optimization based beamforming has prohibitively high complexity due to the semidefinite programming to be solved. In this paper, we propose to solve the optimal beamforming problem by the alternating direction method of multipliers (ADMM). We can achieve near optimal performance while greatly reducing the computational complexity. Simulations demonstrate the advantages of our proposed algorithm over transform based beamforming in terms of performance (e.g., 4 dB reduction in transmit power), and over optimization based beamforming in terms of computation time (e.g., 10 times reduction in computation time).

In this paper, we discuss an advanced base station system with smart algorithms operating on its multiple directional antenna arrays to provide seamless full-directional wireless connectivity and present its simulation result for 5G using Matlab. The system has six-sectors for communication and a scanning array for user discovery. Based on angle-of-arrival (AoA) estimation, optimized beamforming algorithm is employed to establish communication link between respective sector with optimized beams and the identified users. This system modifies the physical layer without affecting other layers and can be installed on the existing infrastructure. All the standards for WiFi, LTE and 5G radios are kept intact. The initial results of simulation show that continued connectivity and tracking with high data rate in multiuser LTE and 5G environment can be achieved.

The expansion of a hybrid genetic program's (HGP) functionality to allow for the development of broadband two-dimensional metamaterials designs with advanced characteristics is presented. Artificial magnetic conductor (AMC) ground planes and a tunable terahertz absorber generated by the HGP are compared with designs available in the literature. The HGP is shown to produce human-competitive results. The AMC ground planes synthesized by the HGP were found to produce improved results including wider bandwidths and larger reflection coefficient magnitudes than that of the human designs. For one of the designed AMCs, the HGP's bandwidth is 73.3% larger and the minimum reflection magnitude is 1.0% larger than the reference AMC. Similarly, the absorber synthesized by the HGP has larger bandwidths than that of a recently published absorber optimized by random hill climbing. Three bias voltages were tested with the tunable absorber. The bandwidths of the HGP absorber are 23.1%, 37.6%, and 400% larger than the reference absorber, for biases of 4, 2, and 0.5 V/nm, respectively. Four example designs are discussed together with comparative results to illustrate the advantages of the developed HGP-enabled design method.

Path loss characteristics in four cities (New York, Chicago, Munich, and Salt Lake City) are investigated using ray-tracing methods. These cities represent different sizes, heights of buildings, and surrounding environments (mountains). The mean propagation path loss and the loss exponent (the n values) are represented as a function of length of streets, number of side streets, transmitting antenna heights, as well the presence of unique site topologies such as hills or mountains. It is shown that for these cities and for transmitters much higher than most of the buildings, the n values are similar to those of free-space propagation. For transmitters located at heights lower than most of the buildings and for streets farther away from transmitters, the n values are three times larger than those extracted from the Hata model. As for the effect of mountains or hills, it is shown that their reflections have minimal influences (0.38 dB) except when transmitters are placed on mountains and receivers are near these mountains (3 dB).

This paper investigates the impacts that open-trench drains make on the accuracy of radio propagation prediction in an urban city environment. Compared with conventional prediction styles that assume the ground to be flat, in this paper, we have considered for the first time the real scenario in many Asian cities to make open-trench drains inclusive in radio propagation modeling. The aims of this paper are twofold. First, to scrutinize one narrow L-shaped structure, modeled after an open-trench drain, by means of comparing ray-tracing simulation results with the actual field measurement results at 2.4 and 5.8 GHz. Second, to compare one city model built without and with the inclusion of open-trench drains for running ray-tracing simulation in yielding radio propagation prediction results. The findings from this paper are especially beneficial to the improvement of mobile communications in extraordinary environments such as open-trench drains, caves, coal mines, underground passageway, and others. Besides, they provide a unique insight into how the presence of the open-trench drains may affect radio wave propagation in an urban city environment.

We study the problem of estimating angle-of-arrival (AoA) using practical antenna arrays. In practical antenna arrays, the antenna elements have nonuniform radiation patterns. However, most existing AoA estimation algorithms are developed based on the assumption that antenna elements are isotropic sources with uniform radiation patterns. Hence, the performance of existing algorithms can be significantly degraded when they are deployed on practical antenna arrays. To overcome the difficulty from nonuniform radiation patterns, we propose a fundamentally different approach of AoA estimation, where we train a neural network to learn the mapping from received signals to AoAs. Since we can generate a large amount of training data from propagation models of electromagnetic waves, our neural network can achieve high estimation accuracy (e.g., 10% estimation errors), which greatly improves the performance of state-of-the- art algorithms (e.g., up to 30% estimation errors). Moreover, by training with data generated from different radiation patterns, our neural network is agnostic of the specific radiation patterns of antenna elements. Since most computation is done in the training phrase, our trained neural network can perform AoA estimation in real time and can be used for tracking AoAs of mobile targets.

The fabrication and measurement of previously proposed artificial magnetic conductor (AMC) designs are presented in this paper. The AMC ground planes were synthesized by a hybrid genetic program (HGP) and were compared with AMC designs found in the literature. The HGP designed AMCs outperformed those in the literature. The performance was determined from full-wave electromagnetic simulations. We also validate the performance of the HGP designed AMCs through fabrication and measurement.

An automatic procedure is developed to extract the water content in lungs based on the computerized tomography (CT) scans of the human torso. Image processing techniques such as watershed segmentation are used to isolate the lungs from rest of the organs in the torso. The water contents of 60 sets (patients) of CT scans are calculated with a mean values similar to the values in the literature.

In this communication genetic programming (GP) is applied to optimize the coverage of wireless networks in rural areas. Three locations in the Hawaiian Islands were studied: Kohala area on Hawaii, the North Shore on Oahu, and the populated area on Maui between West Maui Mountains and Haleakala. Omnidirectional and directional base station scenarios were optimized and simulated. For all three locations studied directional base stations provided better coverage than omnidirectional base stations. For the Maui and Oahu locations directional base stations provided significantly more coverage.

Measuring lung water change is invaluable for monitoring patients with heart failure and pulmonary diseases and assessing their responses to the treatment. Sensors for such measurement have been developed in Hawaii Advanced Wireless Technologies Institute (HAWTI) and clinical trials have been carried out. In this paper, we use numerical simulations to obtain the signals received by the sensors as a function of lung water content and sensor locations on the human torso. The data are interpolated to obtain a finer distribution of signals on the chest. The higher resolution data are used to train the support vector regression (SVR) machine to establish a prediction model for lung water content as a function of received signal and location of the sensors. The interpolation and SVR methods can save significant simulation time and will be used for building a database for lung water prediction for various human torsos.

Radio propagation modeling and prediction play an important role in the understanding of electromagnetic (EM) wave propagation in complex environments, as well as in the design of wireless communications and radar systems.

As terrestrial wireless communication systems become more ubiquitous, there is a rising need to study the propagation characteristics of every habitable environment so that effective communication systems can be established. Past research showed that open-trench drains, whose presence is prevailing in many Asian cities, make up an additional channel in which radio signal can adequately travel. In this letter, we have further our studies in the propagation characteristics of an open-trench drain to delve into areas that have not been previously reported. Specifically, we present field measurement results of an open-trench drain for line-of-sight (LoS) and non-line-of-sight (NLoS) portions at three frequencies (900 MHz, 2.4 and 5.8 GHz) for three different polarizations, namely, vertical-vertical (VV), horizontal-horizontal (HH), and horizontal-vertical (HV) polarizations. Subsequently, we have adopted K-means clustering approach to process the obtained data in deriving path loss exponent $n$ and their associated standard deviation. Comparison is made of the $n$ values, as well as the standard deviation values, before and after employing K-means clustering.

Techniques of radio propagation modeling and simulation are briefly reviewed, and the advantages of ray tracing methods are discussed. Spatial division methods are employed to accelerate the ray tracing algorithms and achieve computational efficiency and accuracy for propagation modeling. Algorithms extracting 3D models from geospatial resources are developed to establish realistic models for propagation environments. Terrain features such as ridges in mountainous regions are important elements characterizing the propagation of electromagnetic waves. Simple methods are introduced to extract these features. Different levels of detail of propagation environment are examined to gain insight of their effect on the efficiency and accuracy of propagation simulation. Computer hardware acceleration using graphics processing units (GPUs) is applied to the propagation simulation over terrains and a significant speedup is achieved. For source localization applications using ray tracing simulations, two methods (time reversal and machine learning) are discussed and their performances are investigated. A perspective of propagation modeling in the near future is given, and it points out that ray tracing methods will play a more significant role in providing accurate simulation results in real time for dynamic environments.

A fundamental approach in the optimal design of wireless communication systems is a proper comprehension of radio wave propagation through wireless channels. As wireless communications become more ubiquitous, new propagation environments emerge and the propagation mechanisms therein are being constantly investigated. The objectives of this chapter are twofold: firstly, to give a succinct review of new and emerging complex environments that require fine-tuning of the propagation models since traditional propagation models that simplify the propagation environment by ignoring the small and fine structures are no longer valid for such complex environments and, secondly, to recount the fundamental concepts of radio propagation modeling and its significance, as well as the basic propagation mechanisms and ray-tracing image method. These fundamental working principles of ray-tracing image method can be utilized both for indoor and outdoor environments because these two settings are governed in essence by the same propagation mechanisms.

In this paper, a smart physical layer based directional communication networking approach is described. It consists of “smart nodes,” equipped with multiple directional antennas and propagation modeling capabilities. This approach brings more “intelligence” (digital logic) in the physical layer to enable full directional communication networking operation without requiring changes in the upper OSI layers. Smart nodes consist of six-sectors, each having a scanning array for user discovery and a dynamic beamforming array for maintaining communication with users. Procedures are developed to enable seamless full-directional link between mobile users and smart nodes, within WiFi and LTE set standards. Simulations are performed using Matlab, and obtained results show successful tracking and continued maintenance of high data rate communication with mobile users.

Digital terrain elevation data (DTED) is usually represented in raster form where the elevations are given at each cell (or point) in a regular grid. Raster forms are simple and widely used for radio propagation modeling. But a raster form does not explicitly have some key terrain features which are important to propagation modeling, such as peaks and ridges. In this paper, we propose a vector form terrain model which directly represents three-dimensional terrain structures (e.g., ridges) and can provide more accurate description of the propagation environments. It can also improve the accuracy for the calculation of diffracted field due to mountainous structures. The advantages and drawbacks of the vector form terrain model are discussed.

Advanced Nodes are the main components of Physical Layer based fully-directional networks. They consist of sets of appropriately programmed antenna arrays that enable them to conform to the standards of the radio being used. This paper provides an in-depth comparison of advanced nodes implementations for the two main choices of radios: 3GPP's Long Term Evolution (LTE) and IEEE 802.11 (WiFi). Component-by-component comparison is carried out, investigating several implementation aspects as well as estimated performance (in terms of standard performance metrics such as bit error rate, data rate, capacity, coverage radius) for the two radios. Based on the comparison, the associated implementation trade-offs are analyzed which help in choosing between the two radios.

The propagation characteristics of indoor multi-floor environments have been studied extensively and empirical models for many scenarios are available. These studies usually do not concern about stair structures. In this paper we study radio propagation in four typical stairwells through measurement at two frequencies (2.4 GHz and 5.8 GHz). Values of path loss exponent n have been derived for vertical and horizontal polarizations. These n-values for stairwells are found to be higher than the n-values for multi-floor environments. We also propose a new path loss model based on the so-called “accumulative distance” the receiver has traveled, in addition to the conventional separation distance between transmitting and receiving antennas. The new path loss model has lower n values and, most importantly, smaller standard deviation and can thus be considered a better model fitting the measurement data. The results in this study can be useful for designers of small cell wireless communications system such as pico- and femto-cells.

The full spatial covariance matrix of the multiple-input multiple-output channel is an important quantity that is used in channel modeling, communication system signal processing, and performance analysis. This paper formulates a closed-form expression for this covariance matrix based on the average multipath propagation characteristics and the radiation patterns of the antennas in the transmit and receive arrays. Simplifications to the formulation are established for cases where the propagation can be represented using discrete plane waves or where the power angular spectrum can be modeled using clusters that satisfy uniform, truncated Gaussian, or truncated Laplacian distributions. Numerical studies demonstrate application of the formulation as well as its accuracy under different scenarios.

This paper presents propagation results in large urban environments using ray tracing simulations. We focus on the region around transmit antenna with ranges of kilometers. The effect of buildings, the number of streets, the height of the transmit antennas, and terrain on propagation characteristics is discussed.

In this paper, Geospatial assets (such as Google Earth) and Genetic Algorithm are used to optimally determine the distribution of base stations over Maui Island, Hawaii. Link budget calculations are performed to obtain a path gain threshold that is used in computing the cost function for the Genetic Algorithm. In the simulations, we compare the coverage of omnidirectional base stations with that of base stations equipped with directional antennas. The results show that four omnidirectional base stations (5 dBi gain) cover ∼ 91% of the Maui region. In comparison, this same cellular coverage is shown to be achievable with the use of only two base stations equipped with directional antennas (19 dBi gain).

In this paper, the performance of an existing Multiuser Wireless Communication System is analyzed using accurate site specific propagation modelling data (such as path gain, angle of arrival/departure and delay spread) of a typical urban environment. For optimal utilization of realistic temporal, spectral and spatial data, obtained from the available ray-tracing tools, a novel multiple detail-level adaptive cognitive communication system is proposed. Desirable system performance in terms of bit-error rate and capacity is shown to be achievable using only AoA and path gain information of as little as 5 paths in generating the channel matrix. As a result, significant savings (85%) in computational cost are achieved, thus emphasizing the potential practical implementation of the proposed approach in cognitive communication applications.

Emerging homeland security applications require low-cost and fast, deployable, high-frequency (HF) radar systems and the ability to operate in challenging terrain environments. With the need to cover as many border and coastal areas as possible, taking advantages of available transmitter resources to track targets using passive radar technologies is yet another area of research of considerable interest. In this paper, we describe the development of an HF radar system that meets these operational challenges, and we also highlight some recent implementation of the passive radar technology for homeland security applications. Specifically, we describe the design of a novel, electrically small HF antenna system consisting of three helical elements, one connected to the feed port while the other two are folded arms terminated with switchable loads. The antenna is 0.90-m (ka range from 0.44 at 30 MHz down to 0.08 at 5.7 MHz. The achieved bandwidths range from 1.4% up to 12% and associated efficiencies range from 66.2% to 76% within the HF band (3‐30 MHz). As for the operational requirement in challenging terrain environments, a setup in a hilltop-type environment with a slope terrain and surface roughness was considered. A propagation modeling and ray-tracing approach was used to evaluate the impact of such terrain conditions on the effective interelement spacing of an HF radar antenna array and the subsequent impact on its beamforming and beam steering performance. It is shown that while the effect of the slope on the effective interelement spacing of the array could be very significant, diffraction effects from surface roughness resulted in a much smaller, but significant, error of about 18°. Results from some initial work on the implementation of passive radar technology, with focus on addressing the bandwidth requirement to ensure practical resolution values, are also described. It is shown that signals from wide-band transmitters (e.g., High Definition Television [HDTV] signals) rather than those from radio stations are required to provide acceptable range resolution. These as well as simulation and experimental results of the antenna design, and results from beamforming simulations illustrating the effect of a rough hilltop terrain on the HF radar performance are described.

The detection and classification of buried targets such as unexploded ordnance (UXO) using ground penetrating radar (GPR) technology involves complex qualitative features and 2-D scattering images. These processes are often performed by human operators and are thus subject to error and bias. Artificial intelligence (AI) technologies, such as neural networks (NN) and fuzzy systems, have been applied to develop autonomous classification algorithms and have shown promising results. Genetic programming (GP), a relatively new AI method, has also been examined for these classification purposes. In this letter, the results of a comparison between the classification performances of NN versus the GP techniques for GPR UXO data are presented. Simulated 2-D scattering patterns from one UXO target and four non-UXO objects are used in this comparison. Different levels of noise and cases of untrained data are also examined. Obtained results show that GP provides better performance than NN methods with increasing problem difficulty. Genetic programming also showed robustness to untrained data as well as an inherent capability of providing global optimal searching, which could minimize efforts on training processes.

Emerging homeland security applications require low-cost and rapid installation of HF radar systems in challenging terrain environments. One example concerns hills with natural slope and surface irregularity and roughness. In this letter, through the investigation of radio-wave propagation in such an environment, we examine the effect of the slope and surface roughness of the terrain on the performance of HF radars. It is shown that the slope and surface irregularity affect the effective electrical spacing between array elements and cause beamforming and scanning errors, which lead to misdetection of targets. It is also shown by an investigation of an actual HF radar site in the area of Koko Head in Hawaii that scattering from surface roughness of the terrain adds extra error to the phase difference between antenna array elements (~30°), hence degrades the radar performance further.

A method for extracting the three-dimensional (3D) building structures using their single-view images available on the Internet/cyberspace is described. Height measurement technique is combined with two-dimensional (2D) projective transformation to obtain the 3D building information. It is shown that the reconstruction method is accurate for path-loss calculations using ray-tracing algorithms. Simulated path losses/gains are compared to results in literature, and good agreement is observed. The effect of building footprint and height inaccuracies on path-loss calculations is also examined and is found to result in errors within the common error range between experimental measurements and ray-tracing predictions.

This letter presents a method for determining the required number and locations of transmit antennas to optimize wireless propagation coverage in a given indoor environment. The ray-tracing method is employed to calculate the field distribution due to one or more transmitting antennas and the genetic algorithm (GA) is used to determine the required number and the locations of these antennas to achieve optimized wireless coverage in a given area. In the ray-tracing method, detailed parameters such as thickness, dielectric constant, and the conductivity of individual walls are assigned for realistic field calculations. Obtained simulation results illustrate the feasibility of using the integrated ray-tracing/GA method in determining the optimized coverage of a wireless network.

Phased array antennas have and will continue to be a critically important component in the development of future wireless systems with applications in communications, radar, and satellite technologies. In spite of the significant advances in the design of modern phased array antennas, there continue to be significant and growing need for developing high performance systems that are also low cost and with beam steering capabilities. In this paper we describe some of the antenna array designs that focus on achieving this goal. We will start with one approach that is based on an analog phase-shifting approach and involves an integrated use of ferroelectric materials and the Continuous Transverse Stub (CTS) antenna array technologies. A complementary design which is based on digital beamforming and the utilization of the Hybrid Smart Antenna technique recently developed by our group will then be described. This will be followed with comments regarding the trade-off between the analog and digital phase shifting techniques. We will conclude the chapter with a description of a novel ultra-wideband and low profile ground plane which is based on a hybrid ferrite and Electromagnetic Band Gap (EBG) materials design. In all cases simulation results and experimental validation, whenever available, will be presented and aspects of the required future work to fully enable these technologies will be discussed.

Propagation-prediction and site-planning software for wireless communication networks has been developed. The software has a user-friendly graphical user interface (GUI), and provides calculations for large-scale and small-scale propagation parameters, including path loss (or received power) and delay profiles. Angles of arrival/departure, which are useful for the design of wireless systems employing multiple antennas, are also provided in the simulation. Some of the main features of the software include the use of a computationally efficient ray-tracing approach for simulating propagation in wireless environments, and the fact that users can upload AutoCAD .dxf files for indoor or outdoor environments. Both a single-building floor plan or an entire city layout can be simulated, and the user is provided with the ability to assign wall geometries and electrical parameters. User-defined realistic antenna radiation patterns for both the transmitting and receiving antennas are incorporated in the simulation. Broadband as well as polarization-dependent simulations are also included in the software.

Robust spectrum sensing and efficient cognitive communication networking (C2N) operation in various terrain environments require that the cognitive radio be proactive and dynamic in selecting the optimal sensing parameters for the current and future locations of mobile units. In spectrum sensing, the detector performance is characterized in terms of detection probability (the rate of C2N correctly sensing a busy channel and avoiding to use it), P d and false alarm probability (the rate at which a free channel is mistakenly identified as busy), P fa parameters. It is worth mentioning that providing higher detection probability should take precedence over providing lower false alarm rates, because a low P d leads to harmful interference which, in turn, adversely affects other mobile devices whereas a high P fa results in the C2N not using that specific channel.