Papers by Mohammad Reza Gholami
Casting Signal processing to Real-World data
Detta är en databas som innehåller referenser till publikationer i lärosäten.
Innovative Signal Processing Techniques for Wireless Positioning
Satellite and Terrestrial Radio Positioning Techniques, 2012
216715 NEWCOM Deliverable Number: DB. 2 Progress Report I on Advanced Localization and Positioning Techniques: Fundamental Techniques and Theoretical Limits
Abstract: Theoretical limits play a fundamental role in position estimation as guidelines and ben... more Abstract: Theoretical limits play a fundamental role in position estimation as guidelines and benchmarks of new developed algorithms. When designing practical positioning techniques the main focus is on reducing the gap between theoretical and real performance and keeping the complexity of the estimator at reasonable level. This report presents the results related to position estimation techniques obtained in the first eighteen months of activity of NEWCOM++ WPR. B. Most of the material represents the outcome of joint activities ...
216715 NEWCOM Deliverable Number: DB. 4 Final Report: Seamless Positioning Techniques in Wireless Communications
Abstract: The present deliverable reports research results on seamless positioning techniques dev... more Abstract: The present deliverable reports research results on seamless positioning techniques developed in the framework of the work package WPR. B on Localization and Positioning within the NEWCOM++ NoE. These results address a wide range of cutting-edge topics starting from measurements, channel modeling, parameter estimation, cognitive and cooperative positioning techniques, and arriving to Bayesian methods for data fusion and integration of hybrid positioning systems (eg, GNSS/terrestrial, radio/inertial ...
The performance of several existing and partly new algorithms for positioning of sensor node base... more The performance of several existing and partly new algorithms for positioning of sensor node based on distance estimate is compared when the distance estimates are obtained from a measurement campaign. The distance estimates are based on time-of-arrival measurements done by ultrawideband devices in an indoor office environment. Two different positioning techniques are compared: statistical and geometrical. In statistical category, distributed
Characterizing the Worst-Case Position Error in Bearing-Only Target Localization
The worst-case position error provides valu- able information for efficiently designing location ... more The worst-case position error provides valu- able information for efficiently designing location based services in wireless networks. In this study, a technique based on a geometric approach is investigated for deriving a reasonable upper bound on the position error in bearing- only target localization. Assuming bounded measurement errors, it is first observed that the target node location belongs to a polytope. When a single estimate of the target location is available, the maximum distance from the estimate to extreme points of the polytope gives an upper bound on the position error. In addition, a technique based on outer approximation is proposed to confine the location of the target node to an ellipsoid. Simulation results show that the proposed upper bound is tight in many situations. It is also observed that the proposed techniques can be effectively used to derive sets containing the location of target nodes.
Clock synchronization is a crucial issue for mobile ad hoc networks due to the dynamic and distri... more Clock synchronization is a crucial issue for mobile ad hoc networks due to the dynamic and distributed nature of these networks. In this paper, employing affine models for local clocks, a random broadcast based distributed consensus clock synchronization algorithm is proposed. In the absence of transmission delays, we theoretically prove the convergence of the proposed scheme, which is further illustrated by numerical results. In addition, it is concluded from simulations that the proposed scheme is scalable and robust to transmission delays as well as different accuracy requirements.
This paper investigates the clock synchronization problem for Device-to-Device (D2D) communicatio... more This paper investigates the clock synchronization problem for Device-to-Device (D2D) communication without infrastructure. Employing affine models for local clocks, it is proposed a random broadcast based distributed consensus clock synchronization algorithm. In the absence of transmission delays, we theoretically prove the convergence of the proposed scheme, which is further illustrated by the numerical evaluations. On the other hand, when the delays are also taken into account, the proposed approach still performs well. Besides, it is further concluded from the simulations that the proposed scheme is robust against dynamic topologies and scalable to the increased number of devices, and has a fast speed regarding the synchronization error decrease.
We investigate the range estimate between two wireless
nodes without time stamps exchanging. Con... more We investigate the range estimate between two wireless
nodes without time stamps exchanging. Considering practical
aspects of oscillator clocks, we propose a new model
for ranging in which the measurement errors include the
sum of two distributions, namely, uniform and Gaussian.
We then derive an approximate maximum likelihood estimator
(AMLE), which poses a difficult global optimization
problem. To avoid the difficulty in solving the complex
AMLE, we propose a simple estimator based on the
method of moments. Numerical results show a promising
performance for the proposed technique.
T In many fields, and especially in the medical and
social sciences and in recommender systems, d... more T In many fields, and especially in the medical and
social sciences and in recommender systems, data are gathered
through clinical studies or targeted surveys. Participants are
generally reluctant to respond to all questions in a survey
or they may lack information to respond adequately to the
questions. The data collected from these studies tend to lea
d
to linear regression models where the regression vectors ar
e
only known partially: some of their entries are either missing
completely or replaced randomly by noisy values. In this work,
we examine how a connected network of agents, with each
one of them subjected to a stream of data with incomplete
regression information, can cooperate with each other through
local interactions to estimate the underlying model parameters
in the presence of missing data. We explain how to adjust
the distributed diffusion through (de)regularization in order to
eliminate the bias introduced by the incomplete model. We also
propose a technique to recursively estimate the (de)regularization
parameter and examine the performance of the resulting strategy.
We illustrate the results by considering two applications: one
dealing with a mental health survey and the other dealing with
a household consumption survey
TW-TOA Based Positioning in the Presence of Clock Imperfections
This paper studies the positioning problem based on two-way time-of-arrival (TW-TOA) measurements... more This paper studies the positioning problem based on two-way time-of-arrival (TW-TOA) measurements in asynchronous wireless sensor networks. Since the optimal estimator for this problem involves difficult nonconvex optimization, we propose two suboptimal estimators based on squared-range least squares and least absolute mean of residual errors. The former approach is formulated as a general trust region subproblem which can be solved exactly under mild conditions. The latter approach is formulated as a difference of convex functions programming (DCP), which can be solved using a concave-convex procedure. Simulation results illustrate the high performance of the proposed techniques, especially for the DCP approach.
Diffusion Estimation over Cooperative Networks with Missing Data
Wireless Sensor Network Positioning Techniques
Upper bounds on position error of a single location estimate in wireless sensor networks
This work aims to estimate multiple node positions in the presence of unknown turn-around times w... more This work aims to estimate multiple node positions in the presence of unknown turn-around times within the context of cooperative sensor network localization. In the adopted scheme, each target can communicate with a set of anchors (probably not in sufficient numbers) and a set of other targets. Two-Way Times-of-Arrival between them are measured, which includes unknown processing delays at both channel endpoints. Since finding the Maximum Likelihood Estimates (MLE) of the positions and turn-around times given those measurements poses a difficult nonconvex optimization problem, it is approximated by a Nonlinear Least Squares problem. Then, the positions and turn-around times of multiple targets are estimated jointly by solving an Euclidean Distance Matrix completion problem. Simulations show that the localization accuracy of the proposed method is good, providing an initial point that subsequently enables MLE to attain the Cramér-Rao Lower Bound for all considered scenarios.
We deal with the positioning problem based on two-way time-ofarrival (TW-TOA) measurements in asy... more We deal with the positioning problem based on two-way time-ofarrival (TW-TOA) measurements in asynchronous wireless sensor networks. The optimal estimator for this problem poses a difficult global optimization problem. To avoid the drawbacks in solving the optimal estimator, we use approximations and derive linear models, which facilitate efficient solutions. In particular, we employ the least squares method and solve a general trust region subproblem to find a coarse estimate. To further refine the estimate, we linearize the measurements and obtain a linear model which can be solved using regularized least squares. Simulation results illustrate that the proposed approaches asymptotically attain the Cramér-Rao lower bound.
This paper studies the received signal strength based localization problem when the transmit powe... more This paper studies the received signal strength based localization problem when the transmit power or path-loss exponent is unknown. The corresponding maximum likelihood estimator (MLE) poses a difficult nonconvex optimization problem. To avoid the difficulty in solving the MLE, we use suitable approximations and formulate the localization problem as a general trust region subproblem, which can be solved exactly under mild conditions. Simulation results show a promising performance for the proposed methods, which also have reasonable complexities compared to existing approaches.
Abstract: Accurate information on position of wireless users is crucial not only for emerging loc... more Abstract: Accurate information on position of wireless users is crucial not only for emerging location-based services and applications but also for network optimization. In order to develop accurate positioning algorithms, environmental characterization of basic radio propagation mechanisms carries significant importance. In the first part of this report, a measurement campaign performed within the NEWCOM++ WPR.
216715 NEWCOM Deliverable Number: DB. 4 Final Report: Seamless Positioning Techniques in Wireless Communications
Abstract: The present deliverable reports research results on seamless positioning techniques dev... more Abstract: The present deliverable reports research results on seamless positioning techniques developed in the framework of the work package WPR. B on Localization and Positioning within the NEWCOM++ NoE.
216715 NEWCOM Deliverable Number: DB. 2 Progress Report I on Advanced Localization and Positioning Techniques: Fundamental Techniques and Theoretical Limits
Abstract: Theoretical limits play a fundamental role in position estimation as guidelines and ben... more Abstract: Theoretical limits play a fundamental role in position estimation as guidelines and benchmarks of new developed algorithms. When designing practical positioning techniques the main focus is on reducing the gap between theoretical and real performance and keeping the complexity of the estimator at reasonable level. This report presents the results related to position estimation techniques obtained in the first eighteen months of activity of NEWCOM++ WPR. B.
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Papers by Mohammad Reza Gholami
nodes without time stamps exchanging. Considering practical
aspects of oscillator clocks, we propose a new model
for ranging in which the measurement errors include the
sum of two distributions, namely, uniform and Gaussian.
We then derive an approximate maximum likelihood estimator
(AMLE), which poses a difficult global optimization
problem. To avoid the difficulty in solving the complex
AMLE, we propose a simple estimator based on the
method of moments. Numerical results show a promising
performance for the proposed technique.
social sciences and in recommender systems, data are gathered
through clinical studies or targeted surveys. Participants are
generally reluctant to respond to all questions in a survey
or they may lack information to respond adequately to the
questions. The data collected from these studies tend to lea
d
to linear regression models where the regression vectors ar
e
only known partially: some of their entries are either missing
completely or replaced randomly by noisy values. In this work,
we examine how a connected network of agents, with each
one of them subjected to a stream of data with incomplete
regression information, can cooperate with each other through
local interactions to estimate the underlying model parameters
in the presence of missing data. We explain how to adjust
the distributed diffusion through (de)regularization in order to
eliminate the bias introduced by the incomplete model. We also
propose a technique to recursively estimate the (de)regularization
parameter and examine the performance of the resulting strategy.
We illustrate the results by considering two applications: one
dealing with a mental health survey and the other dealing with
a household consumption survey