Channel Matrix Recursion for Blind Effective Channel Order Estimation

Date

2011-04-01

Author

Karakutuk, Serkan
Tuncer, Temel Engin

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

112
views

0
downloads

Channel order estimation is a critical task for blind system identification. The performance of the blind system identification algorithms depends on the accuracy and robustness of the channel order estimation. In this paper, a new effective channel order estimation algorithm with high accuracy and robustness is proposed for single-input multi-output (SIMO) systems. The proposed algorithm is guaranteed to find the true channel order for the noise-free case and it performs significantly better than the alternative algorithms for noisy observations. This algorithm shows a consistent performance when the number of observations, channels and channel order are changed. The proposed algorithm is integrated with the least squares smoothing (LSS) algorithm for blind identification of the channel coefficients. Comparisons are done with a variety of different algorithms including linear prediction (LP) based methods. It is shown that significant gain can be obtained compared to the alternative approaches in effective channel order estimation.

Subject Keywords

Signal Processing, Electrical and Electronic Engineering

URI

https://hdl.handle.net/11511/46145

Journal

IEEE TRANSACTIONS ON SIGNAL PROCESSING

DOI

https://doi.org/10.1109/tsp.2010.2100384

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Tracker-aware adaptive detection: An efficient closed-form solution for the Neyman-Pearson case Aslan, Murat Samil; Saranlı, Afşar; Baykal, Buyurman (Elsevier BV, 2010-09-01) A promising line of research for radar systems attempts to optimize the detector thresholds so as to maximize the overall performance of a radar detector-tracker pair. In the present work, we attempt to move in a direction to fulfill this promise by considering a particular dynamic optimization scheme which relies on a non-simulation performance prediction (NSPP) methodology for the probabilistic data association filter (PDAF), namely, the modified Riccati equation (MRE). By using a suitable functional appr...
Matched filtering for CMA-based blind channel estimation Baykal, Buyurman (Institution of Engineering and Technology (IET), 2003-08-21) A novel blind matched filter receiver (MFR) is presented. The development depends on rearrangement of the optimum MFR and the use of the constant modulus algorithm (CMA) to estimate the matched filter. Using the blind MFR and CMA together, a novel blind channel estimation technique is presented.
Blind channel estimation via combining autocorrelation and blind phase estimation Baykal, Buyurman (Institute of Electrical and Electronics Engineers (IEEE), 2004-06-01) Symbol spaced blind channel estimation methods are presented which can essentially use the results of any existing blind equalization method to provide a blind channel estimate of the channel. Blind equalizer's task is reduced to only phase equalization (or identification) as the channel autocorrelation is used to obtain the amplitude response of the channel. Hence, when coupled with simple algorithms such as the constant modulus algorithm (CMA) these methods at baud rate processing provide alternatives to ...
Block-based methods for the reconstruction of finite-length signals from nonuniform samples Tuncer, Temel Engin (Institute of Electrical and Electronics Engineers (IEEE), 2007-02-01) Two novel block-based algorithms are presented for the reconstruction of uniform samples given the nonuniform samples. The first algorithm uses a sinc interpolator whereas the second one uses a DFT-based interpolator. It is shown that the proposed algorithms are stable and the error due to noise and sampling jitter is bounded by the corresponding error norms of noise and jitter, respectively. We show that both of the block-based algorithms provide nearly perfect reconstruction for a class of practically tim...
Target Tracking With Particle Filters Under Signal Propagation Delays Orguner, Umut (Institute of Electrical and Electronics Engineers (IEEE), 2011-06-01) Signal propagation delays are hardly a problem for target tracking with standard sensors such as radar and vision due to the fact that the speed of light is much higher than the speed of the target. This contribution studies the case where the ratio of the target and the propagation speed is not negligible, as in the case of sensor networks with microphones, geophones or sonars for instance, where the signal speed in air, ground and water causes a state dependent and stochastic delay of the observations. Th...

Citation Formats

S. Karakutuk and T. E. Tuncer, “Channel Matrix Recursion for Blind Effective Channel Order Estimation,” IEEE TRANSACTIONS ON SIGNAL PROCESSING, pp. 1642–1653, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46145.