Coarse Location Information Research Articles

Destination-Feedback Free Distributed Transmit Beamforming Using Guided Directionality

Distributed transmit beamforming enables cooperative radios to act as one virtual antenna array, extending their communications’ range beyond the capabilities of a single radio. Most existing distributed beamforming approaches rely on the destination radio sending feedback to adjust the transmitters’ signals for coherent combining. However, relying on the destination radio’s feedback limits the communications range to that of a single radio. Existing destination-feedback-free approaches rely on phase synchronization and knowing the node locations with sub-wavelength accuracy, which becomes impractical for radios mounted on high-mobility platforms like UAVs. In this work, we propose and demonstrate a destination-feedback-free distributed beamforming approach that leverages the radio’s mobility and coarse location information in a dominant line-of-sight channel. In the proposed approach, one radio acts as a guide and moves to point the beam of the remaining radios towards the destination. We specify the radios’ position requirements and verify their relation to the combined signal at the destination using simulations. A proof of concept demo was implemented using software defined radios, showing up to 9 dB SNR improvement in the beamforming direction just by relying on the coarse placement of four radios.

Fingerprint-Based Localization and Channel Estimation Integration for Cell-Free Massive MIMO IoT Systems

In this article, we propose a novel localization and channel estimation integration framework for cell-free massive multiple-input–multiple-output (MIMO) Internet of Things (IoT) systems, in which position information supports accurate channel estimation and accurate channel information can, in turn, improve positioning accuracy. Under this integration framework, we propose a two-phase fingerprint-based localization method consisting of both initial and accurate localization phases and a coarse-location-based (CLB) pilot reassignment scheme. The coarse location information for pilot reassignment is obtained in the initial localization phase of the two-phase localization method, and the fingerprint information used in the accurate localization phase is extracted through channel estimation based on the CLB scheme. Furthermore, for localization, two different fingerprint similarity criteria are proposed to meet the requirements of the different localization phases. Simulation results demonstrate that our proposed two-phase fingerprint-based localization method achieves better positioning performance than existing methods, although there is a slight increase in computational complexity compared to the initial localization. Moreover, our proposed CLB pilot reassignment scheme outperforms the conventional pilot assignment schemes in the comprehensive performance considering both channel estimation performance and complexity.

From small sets of GPS trajectories to detailed movement profiles: quantifying personalized trip-dependent movement diversity

ABSTRACT The ubiquity of personal sensing devices has enabled the collection of large, diverse, and fine-grained spatio-temporal datasets. These datasets facilitate numerous applications from traffic monitoring and management to location-based services. Recently, there has been an increasing interest in profiling individuals' movements for personalized services based on fine-grained trajectory data. Most approaches identify the most representative paths of a user by analyzing coarse location information, e.g., frequently visited places. However, even for trips that share the same origin and destination, individuals exhibit a variety of behaviors (e.g., a school drop detour, a brief stop at a supermarket). The ability to characterize and compare the variability of individuals' fine-grained movement behavior can greatly support location-based services and smart spatial sampling strategies. We propose a TRip DIversity Measure --TRIM – that quantifies the regularity of users' path choice between an origin and destination. TRIM effectively captures the extent of the diversity of the paths that are taken between a given origin and destination pair, and identifies users with distinct movement patterns, while facilitating the comparison of the movement behavior variations between users. Our experiments using synthetic and real datasets and across geographies show the effectiveness of our method.

New Approach for Privacy-Aware Location-Based Service Communications

Location-based services (LBS) are very popular for personal communications in the mobile Internet. In such applications, users make use of the mobile devices to obtain the information of the nearest gas stations, restaurants, banks etc from service provider (SP), as well as identification of the optimal route to reach destination according to user position. Obviously, location data is effective for service provisioning. Therefore, the privacy threat is the inherent problem in LBS. Previous known solutions for privacy-preserving LBS require to blind the location data to SP. Consequently, it certainly suffers from a privacy/quality of service trade-off. We present a new approach to handle such problem for privacy-aware LBS communications. In our protocol, the user submits the exact location to SP to obtain the high quality service, while his location data and the communication transcript cannot be the evidence to be obtained by any third party. Hence the privacy of this user is preserved. We take the deniable (ring) authentication as the building blocks. In this way, it is not necessary for the user to provide coarse location information which would degrade the service quality certainly.

Probabilistic Approach for Visual Homing of a Mobile Robot in the Presence of Dynamic Obstacles

An autonomous mobile robot returns back to a reference (home) position using just the visual information in the visual homing task. Challenges in this autonomous task involve efficient information extraction from images and executing motion based on this information. This paper aims to develop visual homing technique by extracting coarse location information with respect to the reference position using a novel bit encoding approach. Coarse information is used in probabilistic framework to build stronger beliefs on the robot's location with successive movement of the robot. The changes in visual information due to the presence of dynamic obstacles are accounted in likelihood information using bit encoding. Novel information encoding and proposed probability distribution develop sensor model. The action model aims for building stronger beliefs with successive movement, when limited number of commands are used. Experiments are performed using Fire Bird XI robot equipped with a multiple camera system for capturing panoramic view at the robot's location. Multiple experiments show that the robot reaches the reference position without the knowledge of initial location and changing environment conditions. This paper also reports experimental results in the presence of dynamic obstacles.

Dual-Resolution Friend Locator System With Privacy Enhancement Through Polygon Decomposition

Online social networks have become increasingly popular. One of the interesting applications is the friend locator, in which the application server informs a user through a mobile device if some of his/her listed friends are close enough in terms of geographical locations. However, in such services, it is challenging to protect the privacy of the individual users. Previous solutions for the friend locator do not guarantee a high level of privacy and do not maintain efficiency. In this paper, we propose a dual-resolution system structure to guarantee both strong privacy and efficiency. Additionally, we use the polygon decomposition method to achieve both accuracy and flexibility. To be more specific, in the coarse resolution level, each regular mobile user uploads his/her encrypted coarse location information to a central server periodically for comparisons. If a regular mobile user is found to be in the same grid block as an active mobile user, then the friend locator procedure with a higher resolution level will be conducted. Finally, through numerical analysis and simulations, we show that the proposed system design and algorithm can achieve high privacy, efficiency, accuracy, and flexibility.

Image segmentation with pulse-coupled neural network and Canny operators

In this paper, a Canny operator-based method using PCNN (Pulse-Coupled Neural Network) is proposed for color image segmentation. The coarse location information of the salient object and the background is first estimated based on the distribution of the detected key-points. An image is then over-segmented into super-pixels and their histograms are computed. The saliency of a super-pixel is obtained according to the maximum of variance ration and Shannon entropy. Color image segmentation is implemented using PCNN based on Canny operator edge detection method. The proposed method is compared with state-of-the-art methods on the widely used dataset, and the experiments show that it overall obtains more accurate results.

The temporal evolution of coarse location coding of objects: evidence for feedback.

Objects occupy space. How does the brain represent the spatial location of objects? Retinotopic early visual cortex has precise location information but can only segment simple objects. On the other hand, higher visual areas can resolve complex objects but only have coarse location information. Thus coarse location of complex objects might be represented by either (a) feedback from higher areas to early retinotopic areas or (b) coarse position encoding in higher areas. We tested these alternatives by presenting various kinds of first- (edge-defined) and second-order (texture) objects. We applied multivariate classifiers to the pattern of EEG amplitudes across the scalp at a range of time points to trace the temporal dynamics of coarse location representation. For edge-defined objects, peak classification performance was high and early and thus attributable to the retinotopic layout of early visual cortex. For texture objects, it was low and late. Crucially, despite these differences in peak performance and timing, training a classifier on one object and testing it on others revealed that the topography at peak performance was the same for both first- and second-order objects. That is, the same location information, encoded by early visual areas, was available for both edge-defined and texture objects at different time points. These results indicate that locations of complex objects such as textures, although not represented in the bottom-up sweep, are encoded later by neural patterns resembling the bottom-up ones. We conclude that feedback mechanisms play an important role in coarse location representation of complex objects.

An efficient segmentation method using saliency object detection

Automatic co-segmentation is a challenging task because it lacks of prior cues. In this paper, an efficient region contrast based method is proposed for salient object detection and segmentation. The coarse location information of the salient object and the background is first estimated based on the distribution of the detected key-points. Histograms of the estimated foreground and background are calculated as their features. An image is then over-segmented into super-pixels and their histograms are computed. The saliency of a super-pixel is obtained according to the similarity coefficients between the super-pixel and the estimated foreground/background. With the saliency map, the salient object in the image is extracted using a graph cut based optimized framework. The proposed method is compared with state-of-the-art methods on the widely used dataset, and the experiments show that it overall obtains more accurate results.

Location-Aided Fast Distributed Consensus in Wireless Networks

Existing works on distributed consensus explore linear iterations based on reversible Markov chains, which contribute to the slow convergence of the algorithms. It has been observed that by overcoming the diffusive behavior of reversible chains, certain nonreversible chains lifted from reversible ones mix substantially faster than the original chains. In this paper, we investigate the idea of accelerating distributed consensus via lifting Markov chains, and propose a class of Location-Aided Distributed Averaging (LADA) algorithms for wireless networks, where nodes' coarse location information is used to construct nonreversible chains that facilitate distributed computing and cooperative processing. First, two general pseudo-algorithms are presented to illustrate the notion of distributed averaging through chain-lifting. These pseudo-algorithms are then respectively instantiated through one LADA algorithm on grid networks, and one on general wireless networks. For a $k\times k$ grid network, the proposed LADA algorithm achieves an $\epsilon$-averaging time of $O(k\log(\epsilon^{-1}))$. Based on this algorithm, in a wireless network with transmission range $r$, an $\epsilon$-averaging time of $O(r^{-1}\log(\epsilon^{-1}))$ can be attained through a centralized algorithm. Subsequently, we present a fully-distributed LADA algorithm for wireless networks, which utilizes only the direction information of neighbors to construct nonreversible chains. It is shown that this distributed LADA algorithm achieves the same scaling law in averaging time as the centralized scheme. Finally, we propose a cluster-based LADA (C-LADA) algorithm, which, requiring no central coordination, provides the additional benefit of reduced message complexity compared with the distributed LADA algorithm.

A generic IP paging architecture and protocol

Mobile communication systems are increasingly adopting Internet Protocol solutions for mobility management. Taking into account that an increasing number of mobile devices communicate actively for only a fraction of the time, location tracking costs must be appropriate for active and idle devices. Compelling all devices to maintain detailed location information in the network causes unnecessary signaling overhead and mobile battery drainage. Contemporary cellular mobile communication systems deploy technology-specific paging, which supports the maintenance of a mobile terminal’s coarse location information and to request its exact location when a call comes in. IP paging goes beyond that by targeting heterogeneous access in IP-based mobile communication networks, and by contributing towards meeting IP mobility management requirements on the scalability of future systems. This paper describes a generic IP paging architecture and protocol for heterogeneous mobile communication systems that integrates modularly into various IP-based mobility protocols. At the same time efficient integration of various access technologies and associated utilization of technology specific power save mechanisms is supported. The concept facilitates flexible paging area design and the deployment of enhanced paging strategies aimed at optimizing overall signaling costs. The concept is analyzed with regard to its characteristics to save signaling costs and compared with a different paging concept (P-MIP). Design and associated performance characteristics are evaluated based on the topological structure of a domain’s access network. To enhance power saving efficiency in Wireless-LAN-enabled networks, the integration of the IEEE802.11 access technology with the proposed paging protocol including the efficient utilization of the standard’s Power Save Mode is described. The complete paging system’s delay characteristics are evaluated analytically to estimate dependencies of the session blocking probability on the network’s link delay and IEEE802.11 specific power saving parameter settings.

Effects of spatial and symbolic precues on localization performance.

One of the fundamental properties of spatial vision is the ability to localize objects in space. According to a recent proposal, accurate localization performance involves the operation of two systems: the attention system and the eye movement system. Upon stimulus presentation, attention is shifted to the target area: this provides coarse location information. Subsequently, a saccadic eye movement is executed: this provides fine location information. In this study we tested predictions derived from this model concerning the effects of precue information on localization performance. In a series of five experiments we manipulated duration of precue (71, 400, and 1,000 ms) and type of precue (spatial versus symbolic). Results showed that very short duration (i.e., 71 ms) spatial precues improved localization performance whereas very short duration symbolic precues did not. In contrast, the 1,000 ms duration precue condition showed similar amounts of precuing benefit for the spatial and symbolic precues. This pattern of differential precuing effects corroborated the two-process model of localization performance.

The interaction of objective and subjective organizations in a localization search task.

We investigated how both objective and subjective organizations affect perceptual organization and how this perceptual organization, in turn, influences observers' performance in a localization search task. Two groups of observers viewing exactly the same stimuli (objective organization) performed in significantly different ways, depending on how they were induced to parse the display (subjective organization). In Experiments 1 and 2, the observers were asked to describe the location of a tilted target among a varying number of vertical or horizontal distractors. Subjective organization was induced by instructing observers to parse the display into either three horizontal regions (rows) or three vertical regions (columns). The position of the target was critical: location performance, as assessed by reaction time and errors, was consistently impaired at the locations adjacent to the boundaries defining the regions, producing what we refer to as the subjective boundary effect. Furthermore, the extent of this effect depended on whether the stimulus-driven and conceptually driven information concurred or conflicted. This made location information more or less accessible. In Experiment 1, the strength of objective grouping was a function of the proximity of the items (near or far conditions) and their orientation in a 6 x 6 matrix. In Experiment 2, the strength of objective grouping was a function of similarity of color (items were color coded by rows or by columns) and the orientation of the items in a 9 x 9 matrix. The subjective boundary effect was more pronounced when the display promoted grouping in the direction orthogonal to that of the task (e.g., when observers parsed by rows but vertical distractors were closer together [Experiment 1] or color coded [Experiment 2] to induce global columns). In contrast, this effect decreased when the direction of both objective and subjective organizations was parallel (e.g., when observers parsed by rows and horizontal distractors were closer together [Experiment 1] or were color coded [Experiment 2] to induce global rows). A localization search task proved to be an ideal forum in which objective and subjective organizations interacted. We discuss how these results indicated that observers' performance in a localization task was determined by the interaction of objective and subjective organizations, and that the resulting perceptual organization constrained coarse location information.

Density effects in conjunction search: Evidence for a coarse location mechanism of feature integration.

Four experiments used the visual search paradigm to examine feature integration mechanisms. Reaction time to determine the presence or absence of a conjunctive target is relatively fast and exhaustive for low-density displays. Search rate is slow and self-terminating for high-density displays. Density effects do not arise when the target is defined by a unique feature. Two mechanisms are proposed for feature integration. A fast mechanism integrates features on the basis of coarse location information coded with the initial registration of the features. This coarse location mechanism requires that display items be spaced apart. A second, slower mechanism is used when objects are clumped together. The 2-mechanism hypothesis provides a resolution to conflicting findings in the visual search and illusory-conjunction literature. A possible interpretation of the findings with a single guided search mechanism for feature integration is also discussed.

Density effects in conjunction search: Evidence for a coarse location mechanism of feature integration.

Four experiments used the visual search paradigm to examine feature integration mechanisms. Reaction time to determine the presence or absence of a conjunctive target is relatively fast and exhaustive for low-density displays. Search rate is slow and self-terminating for high-density displays. Density effects do not arise when the target is defined by a unique feature. Two mechanisms are proposed for feature integration. A fast mechanism integrates features on the basis of coarse location information coded with the initial registration of the features. This coarse location mechanism requires that display items be spaced apart. A second, slower mechanism is used when objects are clumped together. The 2-mechanism hypothesis provides a resolution to conflicting findings in the visual search and illusory-conjunction literature. A possible interpretation of the findings with a single guided search mechanism for feature integration is also discussed.

Illusory conjunctions inside and outside the focus of attention.

This article addresses 2 questions that arise from the finding that visual scenes are first parsed into visual features: (a) the accumulation of location information about objects during their recognition and (b) the mechanism for the binding of the visual features. The first 2 experiments demonstrated that when 2 colored letters were presented outside the initial focus of attention, illusory conjunctions between the color of one letter and the shape of the other were formed only if the letters were less than 1 degree apart. Separation greater than 2 degrees resulted in fewer conjunction errors than expected by chance. Experiments 3 and 4 showed that inside the spread of attention, illusory conjunctions between the 2 letters can occur regardless of the distance between them. In addition, these experiments demonstrated that the span of attention can expand or shrink like a spotlight. The results suggest that features inside the focus of attention are integrated by an expandable focal attention mechanism that conjoins all features that appear inside its focus. Visual features outside the focus of attention may be registered with coarse location information prior to their integration. Alternatively, a quick and imprecise shift of attention to the periphery may lead to illusory conjunctions among adjacent stimuli.