One of the biggest challenges facing wireless designers is determining how to configure multiple-input-multipleoutput (MIMO) antennas in underground-environments, such as mines, so that they deliver best performance. Here, we showed that angular dispersion of the signal, a phenomenon that greatly impacts channel capacity, can be accurately predicted in both near-field and far-field of underground tunnels using a multimode waveguide. Not only this analytical model is much faster than other methods, but also it does not have other shortcomings of measurement-based modeling (e.g., poor resolution for far distances in the tunnel). Further, we characterized angular-spread for different tunnel sizes and showed that the power-azimuthspectrum can be modeled by a zero-mean Gaussian distribution whose standard-deviation (angular-spread) is dependent on the tunnel dimension and the transmitter-receiver distance. Angular-spread is found to be a decreasing function of axial distance. After a certain distance, it becomes very small (about 4°) and independent of tunnel transverse dimension. Our results are useful for design of MIMO systems in underground tunnels and sufficient to permit the correlation-matrix required to extend the IEEE 802.11n MIMO channel model to underground environments.

A primary ad-hoc network working in parallel with a secondary ad-hoc network is considered. The main challenge in operating cognitive ad-hoc networks is the lack of a centralized controller performing resource allocation for different users in the network. In this paper, a distributed power allocation scheme is considered for secondary users and its performance is analyzed when time average channel gains are substituted for instantaneous channel gains. In this way, it is not necessary to exchange instantaneous channel information; however, users' allocated power will be perturbed. It is of interest to analyze mathematically this perturbation and to show how it affects the network performance. In particular, an upper bound on perturbation of each user's allocated power, rate, and interference caused to a primary receivers by the secondary users is obtained. Then, it is shown that how this perturbation affects the transmission rate and the probability of interference constraint violation by the secondary users.

In this paper, the reflection characteristics of the house flooring construction materials at millimeter-wave (MMW) frequencies are studied. Since this investigation is performed for North American housing, the 57-64 GHz frequency band is considered. In this study, three common flooring materials: hardwood, vinyl and carpet (cut- and loop-pile) are chosen. The reflection characteristics of the aforementioned materials are also measured when the supporting materials, i.e. plywood and underpad, exist. A continues wave (CW) transmit-receive measurement setup with measuring possibility of entire range of 57-64 GHz is employed. The reflection coefficient for all available incident angle and transmission loss for face-to-face antenna direction are measured for the chosen flooring materials. The relative permittivity associated to these materials based on the Fresnel's reflection formula are found. Moreover, the results reveal the frequency dependence of the flooring materials within 57-64 GHz.

Abstract This paper describes the design and implementation of a solar‐powered wireless motion sensor surveillance network. Commercially available systems with similar functionality which exist today have several disadvantages including single points of failure and requires (semi) constant personnel attention as well as an elaborate power system. These systems require a lot of time to set up, they cannot be used in remote areas where a main power supply is unavailable, and are quite costly. Therefore, there is a need to develop a system which is portable, easy to set up, and is energy efficient. The wireless motion surveillance network described in this paper is designed to be portable, economically inexpensive, and energy efficient. The network is created using the IEEE 802.15.4 ZigBee wireless standard by implementing multiple Microchip PICDEM Z nodes. Each node in the network is equipped with a Direction Sensing Infrared Motion Detector (DSIMD) and a solar power unit (SPU). The DSIMD allows for detection of humans and animals alike moving into or out of the network. The system is powered by solar energy that makes it quite adaptable for remote applications. The network is able to cover an area of radius 30 m. By developing a low‐cost system, which is portable, easy to set up, and has an unlimited power supply, this technology is made accessible to a wider range of applications. The implementation of a CMOS camera is discussed at the end which can be used to take a snapshot of the detected object. Copyright © 2007 John Wiley & Sons, Ltd.

Breast cancer, with the exception of lung cancer, is the leading cause of cancer deaths in women. It is also one of the few cancers that can be controlled by using asymptomatic screening method, followed by effective treatments. One recent screening modality under development, microwave tomography, uses the apparent dielectric property contrasts between different breast tissues at microwave frequencies. Microwave tomography uses a numerical model and the image reconstruction consists of iteratively searching the breast structures, applying the numerical model to the breast structures, and matching measured data with computation results of the model. This paper focuses on finite-difference time-domain (FDTD) for the numerical model and genetic algorithm (GA) for the iterative searches. FDTD and GA are time-consuming, yet they are data parallel in nature. In this paper, a parallel algorithm integrating GA and FDTD for detecting tumors using microwave tomography technique is presented. The algorithm is implemented on distributed memory machines using MPI.

Different technologies have been used for breast cancer detections clinically. But they have weaknesses in terms of sensitivity and specificity. Microwave imaging technique, on the contrary, uses the apparent dielectric property contrasts between different breast tissues at microwave frequencies and is a prospective direction to find small tumor at their early stage. Microwave tomography falls in one category of microwave imaging technique. There are two main components in microwave tomography to detect abnormalities in breasts: genetic algorithm (GA) and finite-difference time-domain (FDTD). Both GA and FDTD are time-consuming, but, they are data-parallel in nature. In this paper, we have designed a parallel framework for microwave tomography: parallel GA combined with parallel FDTD. The algorithms are implemented on distributed memory machines running MPI. The execution time of the sequential algorithm (GA and FDTD combined) is 10,131 seconds. The total execution time obtained on 16 processors which is approximately 2000 seconds surpasses the sequential algorithm.