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- Reza Abdolee, Benoît Champagne
- 2011 International Conference on Distributed…
- 2011

In this paper, we propose diffusion-based least mean square (LMS) algorithms that are robust against fading phenomena in wireless channels. The proposed algorithms, developed by combining diffusion LMS and classical estimation approaches, are able to estimate and update the underlying system parameters at each node by exploiting the sensor measurements and… (More)

In this paper, we propose and study the distributed blind adaptive algorithms for wireless sensor network applications. Specifically, we derive distributed forms of the blind least mean square (LMS) and recursive least square (RLS) algorithms based on the constant modulus (CM) criterion. We assume that the inter-sensor communication is single-hop with… (More)

- Reza Abdolee, Benoît Champagne
- IEEE/ACM Transactions on Networking
- 2016

We investigate the performance of distributed least-mean square (LMS) algorithms for parameter estimation over sensor networks where the regression data of each node are corrupted by white measurement noise. Under this condition, we show that the estimates produced by distributed LMS algorithms will be biased if the regression noise is excluded from… (More)

- Reza Abdolee, Benoît Champagne, Ali H. Sayed
- IEEE Transactions on Signal Processing
- 2014

We study the problem of distributed adaptive estimation over networks where nodes cooperate to estimate physical parameters that can vary over both space and time domains. We use a set of basis functions to characterize the space-varying nature of the parameters and propose a diffusion least mean-squares (LMS) strategy to recover these parameters from… (More)

- Reza Abdolee, Benoît Champagne, Ali H. Sayed
- ICC
- 2013

We propose a modified diffusion strategy for parameter estimation in sensor networks where nodes exchange information over fading wireless channels. We show that the effect of fading can be mitigated by incorporating local equalization coefficients into the diffusion process. We explain how the equalization coefficients are chosen and show that the (mean)… (More)

- Reza Abdolee, Benoît Champagne, Ali H. Sayed
- 2012 Proceedings of the 20th European Signal…
- 2012

We study distributed least-mean square (LMS) estimation problems over adaptive networks, where nodes cooperatively work to estimate and track common parameters of an unknown system. We consider a scenario where the input and output response signals of the unknown system are both contaminated by measurement noise. In this case, if standard distributed… (More)

- Reza Abdolee, Mohd Tamizi Ali, T. A. Rahman, Mohd Radzi Tarmizi
- 2007

Sidelobes cancellation is challenging task in beamforming and beam steering in smart antenna systems. The high level of sidelobes can significantly degrade the system performance as well as antenna power efficiency. In this paper, we present the new decimal genetic algorithm to reduce the sidelobe and at the same time create the nulls toward interferers and… (More)

- Reza Abdolee, Benoît Champagne, Ali H. Sayed
- 2012 IEEE Statistical Signal Processing Workshop…
- 2012

We develop a least mean-squares (LMS) diffusion strategy for sensor network applications where it is desired to estimate parameters of physical phenomena that vary over space. In particular, we consider a regression model with space-varying parameters that captures the system dynamics over time and space. We use a set of basis functions such as sinusoids or… (More)

- Reza Abdolee
- 2007

Channel estimation algorithms have a key role in signal detection in MIMO-OFDM systems. In this system, the number of channel components which need to be estimated is much more than conventional SISO wireless systems. Consequently, the computational process of channel estimation is highly intensive. In addition, the high performance channel estimation… (More)

- Reza Abdolee, Benoît Champagne, Ali H. Sayed
- IEEE Transactions on Mobile Computing
- 2016

We study the performance of diffusion least-mean squares algorithms for distributed parameter estimation in multi-agent networks when nodes exchange information over wireless communication links. Wireless channel impairments, such as fading and path-loss, adversely affect the exchanged data and cause instability and performance degradation if left… (More)