Investigating the Limitations of Wireless Localization Based on Signal Strength in Complex Indoor Environments


Student thesis: Doctoral Thesis

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Award date30 Dec 2019


Low power wireless communication technology has enabled tiny sensors to network together by forming an Internet of Thing (IoT) network, which has led to wide range of novel indoor and outdoor applications. As humans spend substantial amount of their time in indoor environments, applications pertaining to address the needs in complex indoor structures, such as rooms, homes, offices and buildings, are in high demand. Most of the IoT application are deployed to provide different services which are tied with the location of the target entity. Therefore, the location of the target entity is of prime importance. However, locating targets in complex indoor environments with signal strength of low energy signals is a challenging task. This dissertation is a comprehensive study of the practical limitations of the localization system based on signal strength in complex indoor environments. This dissertation explores the most commonly used low energy wireless technologies (such as, IEEE 802.15.4 based Bluetooth Low Energy (BLE) and related technologies), for localization with wireless algorithms, such as trilateration and fingerprinting in complex indoor environments. It highlights the practical problems and limitations of the signal strength and addresses important aspects of security issues involved in proximity based authentications with WILS for IoT applications.

The first part of the dissertation is the study of the viability of wireless signal strength of BLE based Wireless Indoor Localization Systems (WILS) that operates on multiple transmission power levels with trilateration and fingerprint localization algorithms in complex indoor environments. The efficacy of the WILS depends on two important factors i.e. localization accuracy and precision which estimated by quantifying the signal strength. The wireless signal strength depends on a number of factors, such as signal transmission intervals, device orientation, presence of Line of Sight (LOS) and Non-Line of Sight (NLOS) and other noise factors due to the motion of different clutters present in an indoor environment that limits the performance of the WILSs. All these factors causes the signal strength to vary large proportions and results in large errors in localization. Since wireless signal strength is used for localization, multiple transmission power levels is one approach of addressing the signal strength variation issue but at the cost of battery lifetime of the devices. In this regard, the performance of the WILS evaluated to highlight the implications of varying different (high, default and low) transmission power levels on localization accuracy and precision. Initially, a non-filter based approach is evaluated by analyzing effects of different transmission power levels on WILS in context of localization accuracy and precision by using classical trilateration based localization model. Later, a filter-based approach is evaluated in which Low Pass Filter and Kalman Filter along with trilateration based localization model is used to analyze the effects of different transmission power levels on localization accuracy and precision of WILS. The main focus of the study is to understand the strengths and weaknesses along with different target estimation approaches which can aid in designing a WILS with high accuracy and precision.

The second part of the dissertation highlights the security issues in wireless proximity based authentication mechanisms used in WILS for complex indoor (industrial) environments. With an accurate and efficient estimation of the target entity, it is equally important that the location information should be secure as well. This part of dissertation aims to research different aspects of the security threats present in complex (industrial) indoor environments and review various proximity based authentication mechanisms that can be used in the Industrial Internet of Things (IIoT) applications. We seek to identify and highlight from a holistic point of view which mechanisms can enable proximity based authentication for the IIoT devices. In addition, we identify which upcoming proximity based authentication mechanisms are most important for the proliferation of the IIoT, and highlight major obstacles that remain unsolved with regard to authentication. In answering this, we present seven mechanisms for proximity based authentication (i.e. wire, radio, acoustics, light, image, gesture and biometrics) and discuss each mechanism in perspective of their vulnerability to different kind of attacks (such as eavesdropping, impersonation and denial of service attacks etc.) and their usability (such as proximity range, hardware requirement and ease of use) in terms of the practicality in IIoT environment. The problem of wireless fingerprint duplication also highlights an important security vulnerability in WILS in which the adversaries can position themselves in close proximities to match the wireless fingerprints in order to authenticate themselves and gain access to the useful information. In this context, we explore the feasibility of CIR based wireless fingerprints for wireless proximity based authentication mechanism in WILS.

The third part of the dissertation presents the problem of wireless fingerprint duplication in fingerprinting based indoor localization. A wireless fingerprint is a feature (such as Received Signal Strength (RSS), RSS-Spread, Path-Loss or Data Rate) that is derived from the collection of wireless signal samples of the Access Points (APs) at different Reference Points (RPs) in an indoor environment. Wireless fingerprints, maps the most likely locations of the targets. The most important aspect of the fingerprinting technique is the distinct wireless fingerprints that represent different RPs. However, different factors such as equal distance of multiple RPs from an AP, may lead to wireless fingerprint duplication, i.e. multiple RPs may have similar wireless fingerprints. This problem of similar wireless fingerprints is referred to as the problem of wireless fingerprint duplication. This problem is crucial as it can result in false localization. In this context, this part of dissertation discusses the fingerprint duplication with different fingerprint metrics extracted from the physical layer of the wireless standard i.e. RSS fingerprint, RSS-Spread fingerprint, Path-loss fingerprint and Data Rate fingerprint, used in fingerprinting based localization. To address this problem, the multiple transmission power level approach aided to step towards the solution in which RSS spread varied from high to low transmission power level. Therefore, RSS spread based wireless fingerprint is proposed in conjunction with different fingerprint metrics (i.e. RSS, RSS-Spread, Path-Loss or Data Rate) to differentiate among RPs in complex LOS and NLOS settings of an indoor environment. Additionally, we explore the viability of Channel Impulse Response (CIR), a parameter extracted from the physical layer of an AP, to be used as wireless fingerprint to map different RPs in complex indoor environments. CIR comprises of the multi-paths generated from the signal transmitted from an AP to different RPs. A wireless fingerprint formulated from the CIR accounts the static surrounding settings, which is expected to be different and unique for all RPs and avoiding the possibility of wireless fingerprint duplication affiliated with RPs located at similar distance from the APs in WILS.

    Research areas

  • Internet of Things, Wireless localization, Localization theory, Localisation Security, Wireless LANs, Bluetooth Low Energy