Apostolia Papapostolou

WIFE: Wireless Indoor Positioning Based on Fingerprint Evaluation

Location awareness of a user or a device has always been considered as a key element for enhancing network performance and improving user experience by enabling efficient mobility and innovative location-based services. In this paper, we present our proposal named WIFE (Wireless Indoor positioning based on Fingerprint Evaluation), a user-based location determination system which utilizes the information of the Signal Strength (SS) received from the surrounding Access Points (APs) inside a building. We focus on a WiFi environment for its low cost and ease of deployment and study fingerprint-based deterministic techniques for their simplicity and reduced processing time and resource requirements. We first address the inherent impairments of an indoor environment which prevent a positioning system from being accurate and then describe our proposed methodology for mitigating them.

Scene analysis indoor positioning enhancements

The emergence of innovative location-oriented services and the great advances in mobile computing and wireless networking motivated the development of positioning systems in indoor environments. However, despite the benefits from location awareness within a building, the implicating indoor characteristics and increased user mobility impeded the implementation of accurate and time-efficient indoor localizers. In this paper, we consider the case of indoor positioning based on the correlation between location and signal intensity of the received Wi-Fi signals. This is due to the wide availability of WLAN infrastructure and the ease of obtaining such signal strength (SS) measurements by standard 802.11 cards. With our focus on the radio scene analysis (or fingerprinting) positioning method, we study both deterministic and probabilistic schemes. We then describe techniques to improve their accuracy without increasing considerably the processing time and hardware requirements of the system. More precisely, we first propose considering orientation information and simple SS sample processing during the training of the system or the entire localization process. For dealing with the expanded search space after adding orientation-sensitive information, we suggest a hierarchical pattern matching method during the real-time localization phase. Numerical results based on real experimental measurements demonstrated a noticeable performance enhancement, especially for the deterministic case which has additionally the advantage of being less complex compared to the probabilistic one.

Exploiting multi-modality and diversity for localization enhancement: WiFi & RFID usecase

The proliferation of wireless technologies, mobile computing and Internet have spurred the development of innovative location-oriented services. For accomplishing this, an accurate and time-efficient location determination system is required. For indoor positioning, WiFi-based solutions are prominent due to the widespread availability of WLANs (wireless LANs). More recently, the RFID (Radio Frequency Identification) technology has also been suggested for its own key prospects. However, both of them suffer from their own limitations. In this paper, we propose the integration of both technologies for carrying out simultaneous tracking of users with multi-modal devices but with diverse capabilities. Taking advantage of this multi-modality but also diversity is investigated for enhancing the system accuracy. Results based on extensive simulations validate the superiority of our proposed hybrid scheme over its stand-alone counterparts.

Integrating RFID and WLAN for indoor positioning and IP movement detection

Location awareness in an indoor environment and wireless access to Internet applications are major research areas towards the overwhelming success of wireless and mobile communications. However, the unpredictable indoor radio propagation and handover latency due to node mobility are the main challenging issues that need to be addressed. For tackling efficiently both problems of indoor localization and handover management, we propose combining key benefits of two outstanding wireless technologies, i.e. radio frequency identification (RFID) and a wireless local area network (WLAN) infrastructure. WLANs, such as IEEE 802.11 (WiFi), are now very common in many indoor environments for providing wireless communication among WiFi-enabled devices by accessing an Access Point (infrastructure mode) or through peer to peer connections (ad hoc mode). However, the small cell size of the Access Points (APs) in a WiFi-based network drives the need for frequent handovers leading to increased latency. RFID is an emerging technology consisting of two basic components, a tag and a reader, and its main purpose is the automatic identification of tagged objects by a reader. However, in the presence of multiple readers, RFID suffers from the so-called reader collision problem, mainly due to the inability for direct communication among them. In this paper, we propose a hybrid RFID and WLAN system; the RFID technology is employed for collecting information that is used for both localization and handover management within the WLAN, whereas the WLAN itself is utilized for controlling and coordinating the RFID reading process. In our system architecture, tag IDs of a RFID tag deployment are correlated with both location and topology information in order to determine the position and predict the next subnetwork of a Mobile Node (MN) with a reader attached to its mobile device. The role of the WLAN is to coordinate the readers when accessing the RFID channel for retrieving tags’ IDs, hence compensating the persisting RFID collision problem among multiple readers. Numerical results based on extensive simulations validate the efficiency of the proposed hybrid system in providing accurate and time efficient localization and reducing the IP handover latency.

Orientation-based radio map extensions for improving positioning system accuracy

Indoor positioning has gained more and more interest lately since it offers the possibility of using the location information in several network functionalities improvement or user services deployment. In this paper, we consider the case of WLAN-based indoor positioning for its simplicity and ease of deployment. With our focus on scene analysis methods, we study both deterministic and probabilistic schemes and try to improve their accuracy performance without increasing the processing and hardware requirements of the system. More precisely, orientation-based sampling of WiFi signal strength (SS) measurements and simple pre-processing of these samples are proposed for mitigating the inherent impairments of the wireless medium. Results based on real experimental measurements showed a considerable accuracy increase especially for the deterministic case.

Simulation-Based Analysis for a Heterogeneous Indoor Localization Scheme

In this paper, we focus on the indoor localization problem and we explore positioning solutions which are based on two popular wireless technologies, namely the wireless LAN (WLAN) and the radio frequency identification (RFID). WLAN-based localizers are easily deployed but suffer from lImited accuracy. On the other hand, RFID-based solutions are more accurate for tracking a single user but are not effiCient in populated environments due to the interference among users. Thus, a technology synergy is proposed for supplementmg their limitations. A simulation-based analysis is provided for evaluating the performance of RFID-based positioning schemes under different environmental conditions and for demonstratmg the potential performance enhancement of each stand-alone solution after being supported from the other.

Handoff Management Relying on RFID Technology

Handoff management is the main research challenge encountered for providing mobility support over the wireless Internet. Actually, during the migration of a mobile node (MN) among different network domains, its IP traffic is interrupted due to the latency delay introduced by the handoff process. The main source of such latency is attributed to the Movement Detection (MD) stage, whereby the MN becomes aware of its new IP network. In this paper, we propose a novel MD scheme relying on the Radio Frequency IDentification (RFID) technology aiming to reduce this latency. The main concept of our proposal is to predict the next point of attachment (PoA) of an RFID-enabled MN by using topology information provided by the network with the collaboration of an RFID system. The proposed scheme is fast, introduces low message overhead and is independent of the underlying radio access technology. An analytical model for its time behavior is firstly derived and finally simulation-based results validate its performance in detecting fast and accurately the MNs movement.

RFID-Assisted Movement Detection Improvement in IP Mobility

The current trend towards all-IP networks and the tremendous growth of wireless access technologies have sparked a significant research interest for enhancing the IP functionality. User mobility is one of the main concerns and Mobile IP is the standard protocol for supporting it, through a process named handover (HO). However, during HO the mobile node (MN)s session is disturbed due to the HO latency. The movement detection procedure, whereby the MN becomes aware of its new IP network has been proposed for reducing the HO latency and the packet loss. Often layer 3 HOs are supposed to be driven by layer 2 triggers, making Mobile IP dependent of lower layer technologies and difficult to implement in heterogenous networks. In this paper, we propose a novel movement detection scheme based on the RFID (Radio Frequency IDentification) technology. The idea behind our proposal is to predict the next point of attachment of an RFID-enabled MN using topology information provided by an RFID system. The proposed scheme is simple, does not interrupt the main communication channel and is independent of the underlying radio access technology. Simulationbased results validate its performance in predicting accurately the next MNs movement.

Considerations for RFID-Based Indoor Simultaneous Tracking

Context-aware applications is not just a vision. Advances in wireless communications and mobile capabilities have revolutionized the way services are brought to users, i.e. adapted to their context. Location is a key attribute of the term context and thus, an accurate location determination system is of paramount importance. RFID (Radio Frequency IDentification) is an emerging technology and recently has been explored for its applicability in location sensing systems. In this paper, we focus on an RFID-based localization approach in an indoor multi-user environment and model its most adverse implicating factors, that is collisions among its main components and interference from indoor characteristics. Extensive simulations are conducted to characterize and evaluate the performance behavior of the proposed scheme in environments with different levels of severity.

Cooperative fingerprint-based indoor localization using Self-Organizing Maps

Indoor positioning techniques based on radio fingerprints outstand over other localization methods because of their independence from radio propagation models and cost-effectiveness in terms of hardware and deployment requirements. However, their reported best achieved accuracy is bounded due to the random environmental changes which cause the inconsistency between the stored fingerprints and the current radio behavior. In order to overcome this limitation, we propose a cooperative localization scheme, whereby users exchange their real-time signal measurements in order to update and improve their estimated location. The update process relies on a modified version of the neural network structure of Self-Organizing Maps by considering the signal relationship between users. Performance evaluation results demonstrate accuracy improvement over the baseline fingerprinting technique while keeping the communication and complexity overheads low.