Ihsan Alshahib Lami

Seamless Outdoors-Indoors Localization Solutions on Smartphones: Implementation and Challenges

The demand for more sophisticated Location-Based Services (LBS) in terms of applications variety and accuracy is tripling every year since the emergence of the smartphone a few years ago. Equally, smartphone manufacturers are mounting several wireless communication and localization technologies, inertial sensors as well as powerful processing capability, to cater to such LBS applications. A hybrid of wireless technologies is needed to provide seamless localization solutions and to improve accuracy, to reduce time to fix, and to reduce power consumption. The review of localization techniques/technologies of this emerging field is therefore important. This article reviews the recent research-oriented and commercial localization solutions on smartphones. The focus of this article is on the implementation challenges associated with utilizing these positioning solutions on Android-based smartphones. Furthermore, the taxonomy of smartphone-location techniques is highlighted with a special focus on the detail of each technique and its hybridization. The article compares the indoor localization techniques based on accuracy, utilized wireless technology, overhead, and localization technique used. The pursuit of achieving ubiquitous localization outdoors and indoors for critical LBS applications such as security and safety shall dominate future research efforts.

OBPSR: A multi-signal receiver based on the orthogonal and bandpass sampling techniques

Multi-signal receivers with integrated functions in the receive/transmit chain are desired in Wireless technology devices such as Smartphones, due to processing time, cost and size saving. This paper proposes a new multi-signal receiver design that formats signals orthogonally for processing by a single Costas Quadrature Phase-Locked-Loop CQPLL; thus allowing the digital processor to switch from tracking/decoding anyone of the received signals to the other without losing phase lock or time. Our receiver utilizes a Hilbert Transform for shifting one of the signals by 90° to prevent overlapping before using Bandpass sampling to fold the two signals to the same frequency in the First Nyquist Zone. The resultant orthogonal kernels are fed to a single CQPLL for tracking and demodulation. Matlab simulations prove our new technique that also reduces the sampling frequency to a rate proportional to the maximum bandwidth, instead of the summation of bandwidths, of the input signals.

GPS, Galileo and Glonass L1 signal detection algorithms based on bandpass sampling techniques

This paper proposes two GNSS signal detection front-end algorithms for GNSS receivers, thus saving valuable resources in chasing signals that are not available. These algorithms can also be used to develop a fast multi-signal GNSS software receiver. With the planed completion of Galileo and Glonass CDMA systems, a GNSS receiver can take advantage of these and GPS signals to aid localization in bad reception areas such as urban-canyons. Such receivers deploy all available resources to find signals even when signals are not available. This paper proposes two approaches that can rapidly detect, in a single view, any GNSS signal power present. The first approach analysis the three signals excitations to a nonlinear bandpass sampling (BPS) receiver that folds these three signals, with their harmonics, to their first Nyquist zone (FNZ). Then, it analyzes their behavior model based on a Volterra algorithm to obtain kernels of these three GNSS signals, if available. Because all three GNSS signals are transmitted with the same carrier frequency, the second approach filters out the right-side/lobe of the Glonass signal and the left-side/lobe of the Galileo signal. This will enable none overlapped folding, based on BPS, of these two signals with the 3rd GPS harmonic in FNZ. These approaches make any GNSS receiver well-informed of available signals, and so devote appropriate resources to acquire and track available signals only. Matlab simulation results prove these two approaches and show that much valuable overall processing time, especially on Smartphones, can be saved by adopting these approaches.

Integrating Cancellable Biometrics with Geographical Location for Effective Unattended Authentication of Users of Mobile Devices

5.2 billion is forecasted as the market size of cloud computing services (CCS) on mobile devices such as Smartphones and Tablets. Mobile cloud computing services (MCCS) has incited an innovative surge of advancement in the fast emerging pervasive computing. Although a number of studies have been carried out in the area of mobile technology, the subject of the readiness of the mobile operating systems, such as Android, IOS and Windows Mobile in MCCS is immensely being unexplored. Challenges and architecture for a suitable MCCS have been defined in this paper. It goes to develop criteria to measure the various Mobile Operating System (MOS) offerings to identify the additional features that should be implemented on MOS to enable and/or enhance that efficient MCCS. This paper also analyses the readiness of MOS to meet the challenges of offering these MCCSs. An in-depth study of the current requirements and challenges are identified, hence criteria is formed that is used to compare these current Smartphone MOS. This paper concludes that mobile virtualisation and security needs to be explored by MOS providers in order to enhance license IP separation, portability, reliability, security, and the consolidation of hardware amongst Smartphones, mobile network operators and MCCS providers. This will aid widening the scope for defining Smartphones as the CCS platform.

Dynamic clock-model of Wi-Fi access-points to help indoors localisation of smartphones

Over the past decade, security and privacy concerns about the growing deployment of biometrics as a proof of identity have motivated researchers to investigate solutions such as cancellable biometrics to enhance the security of biometric systems. However, the open nature of newly emerged mobile authentication scenarios has made these solutions impractical and necessitated the need for new innovative solutions. This paper proposes an effective authentication scheme for remote users on mobile-handsets. The proposal incorporates cancellable biometrics with actual mobile-handset location to produce a one-time authentication token. For added security, the location is obtained and verified via two independent sources, and the authentication token is robustly stamped by the transaction time to guarantee the liveliness. This makes the proposed scheme immune against replay and other remote fraudulent attacks. Trials and simulations based on using biometric datasets and real GPS/Cellular measurements show the viability of our scheme for unattended and mobile authentication. 

Novel dictionary decomposition to acquire GPS signals using compressed sensing

Smartphones contain both Wi-Fi and GPS technologies. When outdoors, the GPS receiver onboard the Smartphone can define its location and provides accurate GPS time. This capability is lost when the Smartphone is indoors. In another vain, Wi-Fi Access Points (WAPs) can be used to locate Smartphones indoors, using Trilateration techniques. However, WAPs contains low accuracy clocks [1] that would produce large position errors when used to locate any Smartphone indoors [2]. By using GPS time, obtained from when the Smartphone was insight of GPS signals, the Smartphone can virtually synchronise in time with any available WAPs. This time delay/offset knowledge will then be used to determine the Smartphones position indoors more accurately, and also to provide seamless outdoors-indoors positioning. To help develop localization hypothesis and simulate various scenarios, based on multiple Smartphones and WAPs, this paper proposes an accurate WAPs clock model that can be used for such simulations. The model uses GPS time as the reference clock, together with WAP clock offset and accurate clock drift model based on real noise factors such as white noise, flicker noise and random walk noise. Our clock model is designed to be dynamic to accommodate various WAPs hardware and their position. Simulation results, using MATLAB, show that our model achieves higher location accuracy of up to 41.33 nanosecond than existing approaches; resulting in average of 12.4 meter position error improvements. Furthermore, our clock synchronization experiments show that our WAP clock model achieves 11.8 nanosecond of clock time error delay improvement over any existing clock model.

OCBPSR: Orthogonal Complex BandPass Sampling Receiver

When acquiring any wireless signal such as GPS, there is a strong association between the amount of integration, correlation or matching performed by the receiver with the strength of the signal, depending on the acquisition technique used. The Compressive Sensing technique (CS) does reduce the computation by up to 60% over correlators based method, yet still maintains acquisition integrity. This paper proposes a new method for implementing the dictionary matrix required for CS and achieving a further saving of more than 80% in the signal acquisition process without loss of the integration between the code and frequency irrespective of the signal strength. This is achieved by removing the generated Doppler shifts from the “overcomplete” dictionary matrix, while keeping the carrier frequency fixed for all these generated shifted SV codes. Our MATLAB simulation for various signal condition scenarios proves that up to 90% of computational complexity and memory space can saved.

Location-assured, multifactor authentication on smartphones via LTE communication

Second-order/Complex BandPass Sampling Receivers (CBPSR) are attractive for acquiring multi-signals for SDR/CR applications. One of the issues caused by the implementation of such receivers is the signals IQ mismatch. This paper proposes a CBPSR implementation that eliminates this IQ mismatch by reformatting the received signals in an orthogonal analytic form (thus named OCBPSR). Our implementation will also reduce the required sampling frequency to below the Nyquist rate, and so reducing the processing time to recover the signals. This is achieved by folding the upper-side of the received signals to the same fold-frequency in the baseband domain without overlapping, by making the signals orthogonal. MATLAB simulation is used to evaluate the performance of our OCBPSR using various scenarios of harsh signal environment, including Doppler and multipath effects.

Galileo Signals Acquisition Using Enhanced Subcarrier Elimination Conversion and Faster Processing

With the added security provided by LTE, geographical location has become an important factor for authentication to enhance the security of remote client authentication during mCommerce applications using Smartphones. Tight combination of geographical location with classic authentication factors like PINs/Biometrics in a real-time, remote verification scheme over the LTE layer connection assures the authenticator about the client itself (via PIN/biometric) as well as the client’s current location, thus defines the important aspects of “who”, “when”, and “where” of the authentication attempt without eaves dropping or man on the middle attacks. To securely integrate location as an authentication factor into the remote authentication scheme, client’s location must be verified independently, i.e. the authenticator should not solely rely on the location determined on and reported by the client’s Smartphone. The latest wireless data communication technology for mobile phones (4G LTE, Long-Term Evolution), recently being rolled out in various networks, can be employed to enhance this location-factor requirement of independent location verification. LTE’s Control Plane LBS provisions, when integrated with user-based authentication and independent source of localisation factors ensures secure efficient, continuous location tracking of the Smartphone. This feature can be performed during normal operation of the LTE-based communication between client and network operator resulting in the authenticator being able to verify the client’s claimed location more securely and accurately. Trials and experiments show that such algorithm implementation is viable for nowadays Smartphone-based banking via LTE communication.