Ahmad Hatami

Handoff in hybrid mobile data networks

With the emergence of a variety of mobile data services with variable coverage, bandwidth, and handoff strategies, and the need for mobile terminals to roam among these networks, handoff in hybrid data networks has attracted tremendous attention. This article presents an overview of issues related to handoff with particular emphasis on hybrid mobile data networks. Issues are logically divided into architectural and handoff decision time algorithms. The handoff architectures in high-speed local coverage IEEE 802.11 wireless LANs, and low-speed wide area coverage CDPD and GPRS mobile data networks are described and compared. A survey of traditional algorithms and an example of an advanced algorithm using neural networks for PTO decision time in homogeneous networks are presented. The HO architectural issues related to hybrid networks are discussed through an example of a hybrid network that employs GPRS and IEEE 802.11. Five architectures for the example hybrid network, based on emulation of GPRS entities within the WLAN, mobile IP, a virtual access point, and a mobility gateway (proxy), are described and compared. The mobility gateway and mobile IP approaches are selected for more detailed discussion. The differences in applying a complex algorithm for HO decision time in a homogeneous and a hybrid network are shown through an example.

Indoor geolocation in the absence of direct path

Severe multipath in indoor areas causes undetected direct path (UDP) conditions, which pose a serious challenge to the design of robust precision indoor geolocation systems. Based on a scenario on the third floor of the Atwater Kent Laboratory at the Worcester Polytechnic Institute, we explain the reason for frequent absence of direct path, and introduce and analyze the effectiveness of two novel approaches to mitigating the large ranging errors caused by UDP conditions. The first technique exploits nondirect paths for ranging, while the second approach relies on cooperative localization for wireless sensor and ad hoc networks

A comparative performance evaluation of RSS-based positioning algorithms used in WLAN networks

The wireless local area network (WLAN) has been an emerging technology in the residential and enterprise market by providing high data rates at low cost. Future trends in the WLAN industry are targeted towards new applications with higher data rates, wider coverage, and increased QoS requirements. A user tracking system based on the WLAN infrastructure is a new service that helps network operators to monitor different aspects of their networks in addition to providing location aware services to their customers. We provide an overview of traditional location sensing algorithms and compare their performance with the new distance variance (DV) algorithm. These algorithms use the existing IEEE 802.11 infrastructure to locate a terminal. The newly introduced DV algorithm uses indoor radio propagation models to reduce the complexity of the calibration process used in conventional algorithms. The performances of the existing and new algorithm are compared using Monte Carlo simulations based on IEEE 802.11 channel models.

Performance Comparison of RSS and TOA Indoor Geolocation Based on UWB Measurement of Channel Characteristics

Recently, variety of algorithms using received signal strength (RSS) or time of arrival (TOA) has been examined for precise indoor localization. The performance of the TOA based systems is sensitive to bandwidth and occurrence of undetected direct path (UDP) conditions, which degrade the localization performance significantly. The performance of the RSS based systems is less sensitive to the bandwidth and occurrence of UDP conditions. This paper uses UWB measurements in a repeatable framework representing a typical office building to compare the performance of four different algorithms and analyze the effect of the system bandwidth. Two of the algorithms are assisted with the ray tracing (RT) simulated channel behaviour. These algorithms are the newly introduced RT assisted TOA closest neighbor (RT-TOA-CN) and RT assisted RSS closest neighbor (RT-RSS-CN). The other two algorithms are traditional least square TOA (LS-TOA) and closest neighbor with TOA grid (CN-TOAG), previously introduced in the literature. We show that under certain radio propagation conditions and bandwidth requirements the localization performance of a simple to implement RSS based algorithm can be close to the more sophisticated TOA based technique

Comparative statistical analysis of indoor positioning using empirical data and indoor radio channel models

Indoor geolocation using maximum likelihood algorithms applied to the measured reference radio map of the received signal strength (RSS) in indoor areas has attracted tremendous attention in the recent published literature. In this paper we examine generation of reference radio maps using two different radio propagation models to replace on site measurements for calibration of these indoor geolocation systems. The first model used for radio propagation is a statistical model recommended by the IEEE 802.11 standardization committee and the second model is a simple building-specific two dimensional ray tracing algorithm. The empirical reference radio map of the RSS from seven access points in 257 locations is collected in the first floor of the Atwater Kent Laboratory, Worcester Polytechnic Institute which represents a typical indoor office area. Using the empirical radio map and the radio map generated from the results of radio propagation modeling, the performance of the nearest neighbor and maximum likelihood location estimation techniques are compared.

On RSS and TOA based indoor geolocation - a comparative performance evaluation

Recently wireless positioning using existing network infrastructure has become an attractive value added application in campus and local area networks. However, many complexities, intrinsic to indoor radio propagation create technical challenges for the localization algorithms to meet indoor positioning requirements. Variety of algorithms using received signal strength (RSS) or time of arrival (TOA) has been used for this purpose. There is a literature gap in performance and system bandwidth requirement comparison between RSS and TOA based techniques used for indoor geolocation. In this paper we present experimental results that demonstrate a systematic comparison between these two techniques. Using a 2D ray tracing (RT) software to create a common repeatable framework for performance evaluation, we present a comparison among two RSS based and two TOA based indoor positioning algorithms in a typical office environment

In-building intruder detection for WLAN access

In recent years wireless local area network (WLAN) has become a popular choice for local area networking in both enterprise and home networking. Increased data rate and price reduction in IEEE 802.11b-g devices has made WLANs even more attractive in these markets. User mobility has opened a new market for location aware, and pervasive computing applications. As a service to these new applications, security and user authentication plays a more important role in a wireless environment compared to the conventional wired systems. In the corporate WLAN environment, since a mobile wireless networks intruder can access the network without physical presence inside the buildings, the solutions for intruder detection has attracted considerable attention by the research community. In this paper we first provide an overview of the traditional location sensing and intruder detection algorithms that are using the existing IEEE 802.11 infrastructure. Then we introduce a new algorithm targeted for intruder detection and authentication in a WLAN network. The new algorithm uses indoor radio propagation modeling to reduce complexity of the calibration process used in the existing algorithms. The performance of the existing and the new algorithm in the first floor of the Atwater Kent Laboratory at the Worcester Polytechnic Institute is used as a basis to compare the performances.

QRPp1-5: Hybrid TOA-RSS Based Localization Using Neural Networks

Recently considerable attention has been given to indoor geolocation using WLAN and WPAN technologies. With respect to positioning, the difference between the two technologies is the system bandwidth, which is around 25 MHz for IEEE 802.11 WLAN devices and at least 500 MHz for IEEE 802.15.3a WPAN devices employing UWB technology. Various algorithms using Received Signal Strength (RSS) or Time of Arrival (TOA) have been implemented for indoor positioning using these technologies. The performance of the TOA based system is sensitive to bandwidth and occurrence of undetected direct path (UDP) conditions, which degrade performance significantly. The performance of the RSS systems is less sensitive to the bandwidth and occurrence of UDP conditions. This paper presents a new hybrid RSS-TOA based localization algorithm using neural networks. The performance of this algorithm is compared with traditional TOA and RSS based algorithms in a common repeatable framework, representing a typical office environment.