Techniques for Wireless Channel Modeling in Harsh Environments

With the rapid growth in the networked environments for different industrial, scientific and defense applications, there is a vital need to assure the user or application a certain level of Quality of Service (QoS). Environments like the industrial environment are particularly harsh with interference from metal structures (as found in the manufacturing sector), interference generated during wireless propagation, and multipath fading of the radio frequency (RF) signal all invite novel mitigation techniques. The challenge of achieving the benefits like improved energy efficiency using wireless is closely coupled with maintaining network QoS requirements. Assessment and management of QoS needs to occur, allowing the network to adapt to changes in the RF, information, and operational environments. The capacity to adapt is paramount to maintaining the required operational performance (throughput, latency, reliability and security). This thesis address the need for accurate radio channel modeling techniques to improve the performance of the wireless communication systems. Multiple different channel modeling techniques are considered including statistical models, ray tracing techniques, finite time-difference technique, transmission line matrix method (TLM), and stochastic differential equation-based (SDE) dynamic channel models. Measurement of ambient RF is performed at several harsh industrial environments to demonstrate the existence of uncertainty in channel behavior. Comparison of various techniques is performed with metrics including accuracy, applicability, and computational efficiency. SDE- and TLM-based methods are validated using indoor and outdoor measurements. Fast, accurate techniques for modeling multipath fading in harsh environments is explored. Application of dynamic channel models is explored for improving QoS of wireless communication system. The TLM-based models provide accurate site-specific path loss calculations taking into consideration materials and propagation characteristics of propagating environment. The validation studies confirm the technique is comparable with existing channel models. The TLM-based channel models is extended to compute the site-specific multipath characteristics of the radio channel eliminating the need for experimental measurement. The TLM-based simulator is also integrated with packet-level network simulator to perform end to end-to-end site specific calculation of wireless network performance. The SDE-channel models provide accurate online estimations of the channel performance along with accurate one-step prediction of the signal strength. The validation studies confirm the accuracy of the technique. Application of the SDE-based models for adaptive antenna control is formulated using online recursive estimation

A Study of the Impact of Various Geometric Factors on the Capacity of Short Range Indoor MIMO Communications Channels

MIMO antenna array systems have been proposed as a means of increasing the spectral efficiency of wireless systems. However, their performance is likely to be sub-optimal if typical uniform antenna array structures are arbitrarily positioned; as they depend on spatial multiplexing. This is particularly true for indoor environments in which transmission ranges are short resulting in a strong correlation of the main propagation paths, especially the line-of-sight components. This makes it difficult to achieve successful spatial multiplexing which depends on a decorrelated set of signal components. Thus, the physical propagation channel and geometry of the antenna arrays, especially the inter-element spacing, can determine how effectively spatial multiplexing can be realised. This thesis investigates MIMO communications channels involving a single transmitter and receiver operating in a simple indoor environment using a ray-tracing simulation model. The results and analysis provide system designers with an understanding of the limits of MIMO system performance in the context of both the geometric properties of the arrays and the propagation conditions. These results serve to explain the often contradictory results that appear in the wider literature on MIMO systems. Guidelines for the deployment of standard array structures in an indoor environment are provided. An original solution to optimising MIMO system performance by adjusting the geometry of uniform linear arrays is described. This is done using an iterative search method based on the Metropolis algorithm in which individual array elements are repositioned. It is demonstrated through computer simulation that capacity levels, similar to those predicted by the theory for ideal Rayleigh channels, are possible to achieve with realistic modifications to uniform linear arrays

Experimental L-band SST satellite communications/surveillance terminal study. Volume 1 - Study summary

Study of design for experimental L band supersonic transport communications/surveillance termina

Wideband mobile propagation channels: Modelling measurements and characterisation for microcellular environments

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

The Multi-Input Multi-Output (MIMO) Channel Modeling, Simulation and Applications

This thesis mainly focus on the Multi-Input Multi-Output (MIMO) channel modeling, simulation and applications. There are several ways to design a MIMO channel. Most of the examples are given in Chapter 2, where we can design channels based on the environments and also based on other conditions. One of the new MIMO channel designs based on physical and virtual channel design is discussed in Unitary-Independent- Unitary (UIU) channel modeling. For completeness, the different types of capacity are discussed in details. The capacity is very important in wireless communication. By understanding the details behind different capacity, we can improve our transmission efficiently and effectively. The level crossing rate and average duration are discussed.One of the most important topics in MIMO wireless communication is estimation. Without having the right estimation in channel prediction, the performance will not be correct. The channel estimation error on the performance of the Alamouti code was discussed. The design of the transmitter, the channel and the receiver for this system model is shown. The two different types of decoding scheme were shown - the linear combining scheme and the Maximum likelihood (ML) decoder. Once the reader understands the estimation of the MIMO channel, the estimation based on different antenna correlation is discussed. Next, the model for Mobile-to-Mobile (M2M) MIMO communication link is proposed. The old M2M Sum-of-Sinusoids simulation model and the new two ring models are discussed. As the last step, the fading channel modeling using AR model is derived and the effect of ill-conditioning of the Yule-Walker equation is also shown. A number of applications is presented to show how the performance can be evaluated using the proposed model and techniques

Viability and Performance of RF Source Localization Using Autocorrelation-Based Fingerprinting

Finding the source location of a radio-frequency (RF) transmission is a useful capability for many civilian, industrial, and military applications. This problem is particularly challenging when done “Blind,” or when the transmitter was not designed with finding its location in mind, and relatively little information is available about the signal before-hand. Typical methods for this operation utilize the time, phase, power, and frequency viewable from received signals. These features are all less predictable in indoor and urban environments, where signals undergo transformation from multiple interactions with the environment. These interactions imprint structure onto the received signal which is dependent on the transmission path, and therefore the initial location. Using a received signal, a signal characteristic known as the autocorrelation can be computed which will largely be shaped by this information. In this research, RF source localization using finger-printing (a technique involving matching to a known database) with signal autocorrelations is explored. A Gaussian-process-based method for autocorrelation based fingerprinting is proposed. Performance of this method is evaluated using a ray-tracing-based simulation of an indoor environment

Efficient Channel Modeling Methods for Mobile Communication Systems

Siirretty Doriast