Mohammad Reza Gholami

In this study, optimal jamming of wireless
localization systems is investigated. Two optimal power
allocation schemes are proposed for jammer nodes in the
presence of total and peak power constraints. In the first
scheme, power is allocated to jammer nodes in order to
maximize the average Cramer-Rao lower bound (CRLB) of ´
target nodes whereas in the second scheme the power allocation
is performed for the aim of maximizing the minimum
CRLB of target nodes. Both schemes are formulated as
linear programs, and a closed-form expression is obtained
for the first scheme. Also, the full total power utilization
property is specified for the second scheme. Simulation
results are presented to investigate performance of the
proposed schemes

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.

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. 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, 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

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.

Abstract The problem of positioning targets based on distance estimates is studied for cooperative wireless sensor networks when there is limited a priori information about measurements noise. To solve this problem, two different methods of positioning are considered: statistical and geometrical. Based on a geometric interpretation, we show that the positioning problem can be rendered as finding the intersection of a number of convex sets.

In this semi-tutorial paper, the positioning problem is formulated as a convex feasibility problem (CFP). To solve the CFP for non-cooperative networks, we con- sider the well-known projection onto convex sets (POCS) technique, and study its properties for positioning. We also study outer-approximation (OA) methods to solve CFP problems. We then show how the POCS estimate can be upper bounded by solving a non-convex optimization problem. Moreover, we introduce two tech- niques based on OA and POCS to solve the CFP for cooperative networks and obtain two new distributed algorithms. Simulation results show that the proposed algorithms are robust against non-line-of-sight conditions.

Mixed HZ/@ Estimation: Posteriori and Priori Adaptive Filtering. ... Javad Mohammadpour-Velnit , MJYazdanpanah , Mohammad Reza Gholami ... Department of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Campus No.2, North Kargar ...

Abstract OFDM modulation technique has been recently considered for high bit rate powerline communication (PLC) due to robustness against multipath frequency selective fading, impulsive and narrowband noise as well as simple spectrum shaping and low-complexity implementation. Sampling clock offset caused by non-synchronized analogue to digital converter (ADC) is one of the major problems that affects each OFDM systems severely. In this paper, a new clock offset timing recovery approach based on symmetrical ...

Abstract In this paper we consider the blind equalization in the transform domain. For blind equalization, multimodulus algorithm (MMA), which is known to be very efficient, is used. To improve the rate of convergence, we used the band-partitioning property of transform domain (TD). In fact, the TD causes the channel output samples to be uncorrelated and this increases the rate of convergence. Also, to further improve the rate of convergence, an optimal time variant step size is used. Simulation results are presented to show the fast ...