Enhanced distance-based location management of mobile communication systems using a cell coordinates approach

In managing the locations of mobile users in mobile communication systems, the distance-based strategy has been proven to have better performance than other dynamic strategies, but is difficult to implement. In this paper, a simple approach is introduced to implement the distance-based strategy by using the cell coordinates in calculating the physical distance traveled. This approach has the advantages of being independent of the size, shape, and distribution of cells, as well as catering for the direction of movement in addition to the speed of each mobile terminal. An enhanced distance-based location management strategy is proposed to dynamically adjust the size and shape of location area for each individual mobile terminal according to the current speed and direction of movement. It can reduce the location management signaling traffic of the distance-based strategy by half when mobile terminals have predictable directions of movement. Three types of location updating schemes are discussed, namely, Circular Location Area, Optimal Location Area, and Elliptic Location Area. Paging schemes using searching techniques such as expanding distance search based on the last reported location and based on the predicted location, and expanding direction search are also explored to further reduce paging signal traffic by partitioning location areas into paging areas.published_or_final_versio

K-Means Fingerprint Clustering for Low-Complexity Floor Estimation in Indoor Mobile Localization

Indoor localization in multi-floor buildings is an important research problem. Finding the correct floor, in a fast and efficient manner, in a shopping mall or an unknown university building can save the users' search time and can enable a myriad of Location Based Services in the future. One of the most widely spread techniques for floor estimation in multi-floor buildings is the fingerprinting-based localization using Received Signal Strength (RSS) measurements coming from indoor networks, such as WLAN and BLE. The clear advantage of RSS-based floor estimation is its ease of implementation on a multitude of mobile devices at the Application Programming Interface (API) level, because RSS values are directly accessible through API interface. However, the downside of a fingerprinting approach, especially for large-scale floor estimation and positioning solutions, is their need to store and transmit a huge amount of fingerprinting data. The problem becomes more severe when the localization is intended to be done on mobile devices which have limited memory, power, and computational resources. An alternative floor estimation method, which has lower complexity and is faster than the fingerprinting is the Weighted Centroid Localization (WCL) method. The trade-off is however paid in terms of a lower accuracy than the one obtained with traditional fingerprinting with Nearest Neighbour (NN) estimates. In this paper a novel K-means-based method for floor estimation via fingerprint clustering of WiFi and various other positioning sensor outputs is introduced. Our method achieves a floor estimation accuracy close to the one with NN fingerprinting, while significantly improves the complexity and the speed of the floor detection algorithm. The decrease in the database size is achieved through storing and transmitting only the cluster heads (CH's) and their corresponding floor labels.Comment: Accepted to IEEE Globecom 2015, Workshop on Localization and Tracking: Indoors, Outdoors and Emerging Network

Initial Access in 5G mm-Wave Cellular Networks

The massive amounts of bandwidth available at millimeter-wave frequencies (roughly above 10 GHz) have the potential to greatly increase the capacity of fifth generation cellular wireless systems. However, to overcome the high isotropic pathloss experienced at these frequencies, high directionality will be required at both the base station and the mobile user equipment to establish sufficient link budget in wide area networks. This reliance on directionality has important implications for control layer procedures. Initial access in particular can be significantly delayed due to the need for the base station and the user to find the proper alignment for directional transmission and reception. This paper provides a survey of several recently proposed techniques for this purpose. A coverage and delay analysis is performed to compare various techniques including exhaustive and iterative search, and Context Information based algorithms. We show that the best strategy depends on the target SNR regime, and provide guidelines to characterize the optimal choice as a function of the system parameters.Comment: 6 pages, 3 figures, 3 tables, 15 references, submitted to IEEE COMMAG 201

Implementing a map based simulator for the location API for J2ME

The Java Location API for J2METM integrates generic positioning and orientation data with persistent storage of landmark objects. It can be used to develop location based service applications for small mobile devices, and these applications can be tested using simulation environments. Currently the only simulation tools in the public domain are proprietary mobile device simulators that are driven by GPS data log files, but it is sometimes useful to be able to test location based services using interactive map-based tools. In addition, we may need to experiment with extensions and changes to the standard API to support additional services, requiring an open source environment. In this paper we describe the implementation of an open source map-based simulation tool compatible with other commonly used development and deployment tools

RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home systems.Comment: 18 pages, 2 figures, 3 table

Mass-Market Receiver for Static Positioning: Tests and Statistical Analyses

Nowadays, there are several low cost GPS receivers able to provide both pseudorange and carrier phase measurements in the L1band, that allow to have good realtime performances in outdoor condition. The present paper describes a set of dedicated tests in order to evaluate the positioning accuracy in static conditions. The quality of the pseudorange and the carrier phase measurements let hope for interesting results. The use of such kind of receiver could be extended to a large number of professional applications, like engineering fields: survey, georeferencing, monitoring, cadastral mapping and cadastral road. In this work, the receivers performance is verified considering a single frequency solution trying to fix the phase ambiguity, when possible. Different solutions are defined: code, float and fix solutions. In order to solve the phase ambiguities different methods are considered. Each test performed is statistically analyzed, highlighting the effects of different factors on precision and accurac