-  Power system state estimation is a central component in energy management systems of power system. The goal of state estimation is to determine the system status and power flow of transmission lines. This paper presents an advanced state estimation algorithm based on weighted least square (WLS) criteria by introducing virtual meters. For each bus of network, except slack bus, a virtual meter...

Channel estimation is one of the most significant technologies in orthogonal-frequency-divisionmultiplexing(OFDM) . Inter-carrier-interference (ICI) occurs in OFDM which must be removed. There are various methods to reduce ICI in OFDM . Channel estimation techniques are used to investigate to reduce ICI in OFDM .In this paper we will discuss Channel estimation methods and DFT based channel esti...

In this study, compressed channel estimation method for sparse multipath two-way relay networks is investigated. Conventional estimation methods, e.g., Least Square (LS) and Minimum Mean Square Error (MMSE), are based on the dense assumption of relay channel and cannot exploit channel sparsity which has been verified by lots of channel measurements. Unlike the previous methods, we propose a com...

Channel estimation problem is one of key technical issues in time-variant multiple-input multiple-output (MIMO) communication systems. To estimate the MIMO channel, least mean square (LMS) algorithm was applied to adaptive channel estimation (ACE). Since the MIMO channel is often described by sparse channel model, such sparsity could be exploited and then estimation performance could be improve...

Least mean square (LMS) type adaptive algorithms have attracted much attention due to their low computational complexity. In the scenarios of sparse channel estimation, zero-attracting LMS (ZA-LMS), reweighted ZA-LMS (RZA-LMS) and reweighted -norm LMS (RL1-LMS) have been proposed to exploit channel sparsity. However, these proposed algorithms may hard to make tradeoff between convergence speed ...

A robust sparse least-mean mixture-norm (LMMN) algorithm is proposed, and its performance is appraised in the context of estimating a broadband multi-path wireless channel. The proposed algorithm is implemented via integrating a correntropy-induced metric (CIM) penalty into the conventional LMMN algorithm to modify the basic cost function, which is denoted as the CIM-based LMMN (CIM-LMMN) algor...

This paper presents a combined approach to channel estimation for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM). It uses both time domain and frequency domain information in the received signal to estimate the channel. Initial estimate of the channel is obtained using pilot assisted least square (LS) channel estimation. The estimate is further enhanced ...

This paper is about the improvement in the system performance of STBC MIMO System with the help of channel estimation technique based Block coding using pilot carriers and also to investigate the performance of STBC MIMO system in a multipath fading channel. These techniques are carried out with conventional Least Square (LS) & Minimum Mean Square (MMSE) estimation algorithms. The performance o...

In this paper, a model identification method for the unknown environments has been developed. By the interactions between a mobile manipulator and the unknown object, a nonholonomic cart, the sensory information has been collected to estimate the model parameters of the cart, which are used to control the cart. Since the raw data are contaminated by noise that can not be modeled statistically, ...

With the advancement in wireless communication, the desire to achieve data transmission at high speed is also increasing. But accomplishing high data rate transmission over broadband wireless channel seems a challenging task. Multiple-input-multiple-output (MIMO) communication when combined with OFDM System allows reliable transmission of data. The pilot based channel estimation is one of the m...