A second-order blind equalization method robust to ill-conditioned SIMO FIR channels |
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| Affiliation: | 1. School of Information Technology, Deakin University, Burwood, VIC 3125, Australia;2. School of Computer Science and Educational Software, Guangzhou University, Guangzhou 510006, China;3. Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, China;4. Faculty of Automation, Guangdong University of Technology, Guangzhou 510006, China;1. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA;2. Sandia National Laboratories, Livermore, CA, USA;1. School of Electrical Engineering, Korea University, Seoul, Republic of Korea;2. College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China;3. College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia;4. Department of Electronics Convergence Engineering, Wonkwang University, Iksan, Republic of Korea;1. Division of Gastroenterology, Washington University School of Medicine, St. Louis, Missouri;3. Duke University School of Medicine and the Durham VA Medical Center, Durham, North Carolina;4. The First Hospital of Jilin University, Changchung, Jilin, China |
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| Abstract: | This paper deals with blind equalization of single-input–multiple-output (SIMO) finite-impulse-response (FIR) channels driven by i.i.d. signal, by exploiting the second-order statistics (SOS) of the channel outputs. Usually, SOS-based blind equalization is carried out via two stages. In Stage 1, the SIMO FIR channel is estimated using a blind identification method, such as the recently developed truncated transfer matrix (TTM) method. In Stage 2, an equalizer is derived from the estimate of the channel to recover the source signal. However, this type of two-stage approach does not give satisfactory blind equalization result if the channel is ill-conditioned, which is often encountered in practical applications. In this paper, we first show that the TTM method does not work in some situations. Then, we propose a novel SOS-based blind equalization method which can directly estimate the equalizer without knowing the channel impulse responses. The proposed method can obtain the desired equalizer even in the case that the channel is ill-conditioned. The performance of our method is illustrated by numerical simulations and compared with four benchmark methods. |
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| Keywords: | Blind equalization Blind identification SIMO FIR channel Second-order statistics |
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