Doctor of Philosophy

dissertationIn wireless sensor networks, knowing the location of the wireless sensors is critical in many remote sensing and location-based applications, from asset tracking, and structural monitoring to geographical routing. For a majority of these applications, received signal strength (RSS)-based localization algorithms are a cost effective and viable solution. However, RSS measurements vary unpredictably because of fading, the shadowing caused by presence of walls and obstacles in the path, and non-isotropic antenna gain patterns, which affect the performance of the RSS-based localization algorithms. This dissertation aims to provide efficient models for the measured RSS and use the lessons learned from these models to develop and evaluate efficient localization algorithms. The first contribution of this dissertation is to model the correlation in shadowing across link pairs. We propose a non-site specific statistical joint path loss model between a set of static nodes. Radio links that are geographically proximate often experience similar environmental shadowing effects and thus have correlated shadowing. Using a large number of multi-hop network measurements in an ensemble of indoor and outdoor environments, we show statistically significant correlations among shadowing experienced on different links in the network. Finally, we analyze multihop paths in three and four node networks using both correlated and independent shadowing models and show that independent shadowing models can underestimate the probability of route failure by a factor of two or greater. Second, we study a special class of algorithms, called kernel-based localization algorithms, that use kernel methods as a tool for learning correlation between the RSS measurements. Kernel methods simplify RSS-based localization algorithms by providing a means to learn the complicated relationship between RSS measurements and position. We present a common mathematical framework for kernel-based localization algorithms to study and compare the performance of four different kernel-based localization algorithms from the literature. We show via simulations and an extensive measurement data set that kernel-based localization algorithms can perform better than model-based algorithms. Results show that kernel methods can achieve an RMSE up to 55% lower than a model-based algorithm. Finally, we propose a novel distance estimator for estimating the distance between two nodes a and b using indirect link measurements, which are the measurements made between a and k, for k ? b and b and k, for k ? a. Traditionally, distance estimators use only direct link measurement, which is the pairwise measurement between the nodes a and b. The results show that the estimator that uses indirect link measurements enables better distance estimation than the estimator that uses direct link measurements

Simulating mobile ad hoc networks: a quantitative evaluation of common MANET simulation models

Because it is difficult and costly to conduct real-world mobile ad hoc network experiments, researchers commonly rely on computer simulation to evaluate their routing protocols. However, simulation is far from perfect. A growing number of studies indicate that simulated results can be dramatically affected by several sensitive simulation parameters. It is also commonly noted that most simulation models make simplifying assumptions about radio behavior. This situation casts doubt on the reliability and applicability of many ad hoc network simulation results. In this study, we begin with a large outdoor routing experiment testing the performance of four popular ad hoc algorithms (AODV, APRL, ODMRP, and STARA). We present a detailed comparative analysis of these four implementations. Then, using the outdoor results as a baseline of reality, we disprove a set of common assumptions used in simulation design, and quantify the impact of these assumptions on simulated results. We also more specifically validate a group of popular radio models with our real-world data, and explore the sensitivity of various simulation parameters in predicting accurate results. We close with a series of specific recommendations for simulation and ad hoc routing protocol designers

Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered

Cross-Layer Theoretical Analysis of NC-aided Cooperative ARQ Protocols in Correlated Shadowed Environments

In this paper, we propose a cross-layer analytical model for the study of network coding (NC)-based Automatic Repeat reQuest (ARQ) medium access control (MAC) protocols in correlated slow-faded (shadowed) environments, where two end nodes are assisted by a cluster of relays to exchange data packets. The goal of our work is threefold: 1) to provide general physical-layer theoretical expressions for estimating crucial network parameters (i.e., network outage probability and expected size of the active relay set), applicable in two-way communications; 2) to demonstrate how these expressions are incorporated into theoretical models of the upper layers (i.e., MAC); and 3) to study the performance of a recently proposed NC-aided cooperative ARQ (NCCARQ) MAC protocol under correlated shadowing conditions. Extensive Monte Carlo experiments have been carried out to validate the efficiency of the developed analytical model and to investigate the realistic performance of NCCARQ. Our results indicate that the number of active relays is independent of the shadowing correlation in the wireless links and reveal intriguing tradeoffs between throughput and energy efficiency, highlighting the importance of cross-layer approaches for the assessment of cooperative MAC protocols

Measurement Based Channel Characterization and Modeling for Vehicle-to-Vehicle Communications

Vehicle-to-Vehicle (V2V) communication is a challenging but fast growing technology that has potential to enhance traffic safety and efficiency. It can also provide environmental benefits in terms of reduced fuel consumption. The effectiveness and reliability of these applications highly depends on the quality of the V2V communication link, which rely upon the properties of the propagation channel. Therefore, understanding the properties of the propagation channel becomes extremely important. This thesis aims to fill some gaps of knowledge in V2V channel research by addressing four different topics. The first topic is channel characterization of some important safety critical scenarios (papers I and II). Second, is the accuracy or validation study of existing channel models for these safety critical scenarios (papers III and IV). Third, is about channel modeling (paper V) and, the fourth topic is the impact of antenna placement on vehicles and the possible diversity gains. This thesis consists of an introduction and six papers: Paper I presents a double directional analysis of vehicular channels based on channel measurement data. Using SAGE, a high-resolution algorithm for parameter estimation, we estimate channel parameters to identify underlying propagation mechanisms. It is found that, single-bounce reflections from static objects are dominating propagation mechanisms in the absence of line-of-sight (LOS). Directional spread is observed to be high, which encourages the use of diversity-based methods. Paper II presents results for V2V channel characterization based on channel measurements conducted for merging lanes on highway, and four-way street intersection scenarios. It is found that the merging lane scenario has the worst propagation condition due to lack of scatterers. Signal reception is possible only with the present LOS component given that the antenna has a good gain in the direction of LOS. Thus designing an antenna that has an omni-directional gain, or using multiple antennas that radiate towards different directions become more important for such safety critical scenarios. Paper III presents the results of an accuracy study of a deterministic ray tracing channel model for vehicle-to-vehicle (V2V) communication, that is compared against channel measurement data. It is found that the results from measurement and simulation show a good agreement especially in LOS situations where as in NLOS situations the simulations are accurate as far as existing physical phenomena of wave propagation are captured by the implemented algorithm. Paper IV presents the results of a validation study of a stochastic NLOS pathloss and fading model named VirtualSource11p for V2V communication in urban street intersections. The reference model is validated with the help of independent channel measurement data. It is found that the model is flexible and fits well to most of the measurements with a few exceptions, and we propose minor modifications to the model for increased accuracy. Paper V presents a shadow fading model targeting system simulations based on channel measurements. The model parameters are extracted from measurement data, which is separated into three categories; line-of-sight (LOS), LOS obstructed by vehicles (OLOS), and LOS blocked by buildings (NLOS), with the help of video information recorded during the measurements. It is found that vehicles obstructing the LOS induce an additional attenuation in the received signal power. The results from system level vehicular ad hoc network (VANET) simulations are also presented, showing that the LOS obstruction affects the packet reception probability and this can not be ignored. Paper VI investigates the impact of antenna placement based on channel measurements performed with four omni-directional antennas mounted on the roof, bumper, windscreen and left-side mirror of the transmitter and receiver cars. We use diversity combining methods to evaluate the performance differences for all possible single-input single-output (SIMO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) link combinations. This investigation suggests that a pair of antennas with complementary properties, e.g., a roof mounted antenna together with a bumper antenna is a good solution for obtaining the best reception performance, in most of the propagation environments. In summary, this thesis describes the channel behavior for safety-critical scenarios by statistical means and models it so that the system performance can be assessed in a realistic manner. In addition to that the influence of different antenna arrangements has also been studied to exploit the spatial diversity and to mitigate the shadowing effects. The presented work can thus enable more efficient design of future V2V communication systems

Stochastic Signal Processing and Power Control for Wireless Communication Systems

This dissertation is concerned with dynamical modeling, estimation and identification of wireless channels from received signal measurements. Optimal power control algorithms, mobile location and velocity estimation methods are developed based on the proposed models. The ultimate performance limits of any communication system are determined by the channel it operates in. In this dissertation, we propose new stochastic wireless channel models which capture both the space and time variations of wireless systems. The proposed channel models are based on stochastic differential equations (SDEs) driven by Brownian motions. These models are more realistic than the time invariant models encountered in the literature which do not capture and track the time varying characteristics of the propagation environment. The statistics of the proposed models are shown to be time varying, and converge in steady state to their static counterparts. Cellular and ad hoc wireless channel models are developed. In urban propagation environment, the parameters of the channel models can be determined from approximating the band-limited Doppler power spectral density (DPSD) by rational transfer functions. However, since the DPSD is not available on-line, a filterbased expectation maximization algorithm and Kalman filter to estimate the channel parameters and states, respectively, are proposed. The algorithm is recursive allowing the inphase and quadrature components and parameters to be estimated on-line from received signal measurements. The algorithms are tested using experimental data, and the results demonstrate the method’s viability for both cellular and ad hoc networks. Power control increases system capacity and quality of communications, and reduces battery power consumption. A stochastic power control algorithm is developed using the so-called predictable power control strategies. An iterative distributed algorithm is then deduced using stochastic approximations. The latter only requires each mobile to know its received signal to interference ratio at the receiver

SAI: safety application identifier algorithm at MAC layer for vehicular safety message dissemination over LTE VANET networks

Vehicular safety applications have much significance in preventing road accidents and fatalities. Among others, cellular networks have been under investigation for the procurement of these applications subject to stringent requirements for latency, transmission parameters, and successful delivery of messages. Earlier contributions have studied utilization of Long-Term Evolution (LTE) under single cell, Friis radio, or simplified higher layer. In this paper, we study the utilization of LTE under multicell and multipath fading environment and introduce the use of adaptive awareness range. Then, we propose an algorithm that uses the concept of quality of service (QoS) class identifiers (QCIs) along with dynamic adaptive awareness range. Furthermore, we investigate the impact of background traffic on the proposed algorithm. Finally, we utilize medium access control (MAC) layer elements in order to fulfill vehicular application requirements through extensive system-level simulations. The results show that, by using an awareness range of up to 250 m, the LTE system is capable of fulfilling the safety application requirements for up to 10 beacons/s with 150 vehicles in an area of 2 × 2 km2. The urban vehicular radio environment has a significant impact and decreases the probability for end-to-end delay to be ≤100 ms from 93%–97% to 76%–78% compared to the Friis radio environment. The proposed algorithm reduces the amount of vehicular application traffic from 21 Mbps to 13 Mbps, while improving the probability of end-to-end delay being ≤100 ms by 20%. Lastly, use of MAC layer control elements brings the processing of messages towards the edge of network increasing capacity of the system by about 50%