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20152024
most citedOn Distributed Vector Estimation for Power and Bandwidth Constrained Wireless Sensor Networks

55 citations · 106 across the 22 of their papers we have counts for

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Showing 2017Show all

6 papers · 1 filter

eess.SP2017

Sensor Selection and Power Allocation via Maximizing Bayesian Fisher Information for Distributed Vector Estimation

Mojtaba Shirazi, Alireza Sani, Azadeh Vosoughi

In this paper we study the problem of distributed estimation of a Gaussian vector with linear observation model in a wireless sensor network (WSN) consisting of K sensors that tran…

eess.SP2017

On the Combined Effect of Directional Antennas and Imperfect Spectrum Sensing upon Ergodic Capacity of Cognitive Radio Systems

Hassan Yazdani, Azadeh Vosoughi

We consider a cognitive radio system, consisting of a primary transmitter (PUtx), a primary receiver (PUrx), a secondary transmitter (SUtx), and a secondary receiver (SUrx). The se…

eess.SP2017

On Power Allocation for Distributed Detection with Correlated Observations and Linear Fusion

Hamid R. Ahmadi, Nahal Maleki, Azadeh Vosoughi

We consider a binary hypothesis testing problem in an inhomogeneous wireless sensor network, where a fusion center (FC) makes a global decision on the underlying hypothesis. We ass…

cs.IT2017★ 25 cited

On Distributed Linear Estimation With Observation Model Uncertainties

Alireza Sani, Azadeh Vosoughi

We consider distributed estimation of a Gaussian source in a heterogenous bandwidth constrained sensor network, where the source is corrupted by independent multiplicative and addi…

cs.IT2017

On M-ary Distributed Detection for Power Constraint Wireless Sensor Networks

Zahra Hajibabaei, Jalil Modares, Azadeh Vosoughi

We consider a wireless sensor network (WSN), consisting of several sensors and a fusion center (FC), which is tasked with solving an M-ary hypothesis testing problem. Sensors make…

cs.IT2017

On Bayesian Fisher Information Maximization for Distributed Vector Estimation

Mojtaba Shirazi, Azadeh Vosoughi

We consider the problem of distributed estimation of a Gaussian vector with linear observation model. Each sensor makes a scalar noisy observation of the unknown vector, quantizes…