Analytical blind channel identification
نویسندگان
چکیده
In this paper, a novel analytical blind single-input single-output (SISO) identification algorithm is presented, based on the noncircular second-order statistics of the output. It is shown that statistics of order higher than two are not mandatory to restore identifiability. Our approach is valid, for instance, when the channel is excited by phase shift keying (PSK) inputs. It is shown that the channel taps need to satisfy a polynomial system of degree 2 and that identification amounts to solving the system. We describe the algorithm that is able to solve this particular system entirely analytically, thus avoiding local minima. Computer results eventually show the robustness with respect to noise and to channel length overdetermination. Identifiability issues are also addressed.
منابع مشابه
An Analytical Solution for 2nd Order Statistics Based Blind Mimo Channel Identification
We address the problem of blind identification of multiple-input multiple-output (MIMO) channels, based only on second-order statistics. We complement the theoretical study of a previously introduced closed-form solution derived within a correlative coding framework. This consists in pre-filtering the stationary random data processes, in order to attain diversity in the respective spectral powe...
متن کاملBlind multivariable ARMA subspace identification
In this paper, we study the deterministic blind identification of multiple channel state-space models having a common unknown input using measured output signals that are perturbed by additive white noise sequences. Different from traditional blind identification problems, the considered system is an autoregressive system rather than an FIR system; hence, the concerned identification problem is...
متن کاملIdentifiability Conditions for Blind and Semi-blind Multiuser Multichannel Identification
We explore the identifiability conditions for blind and semi-blind multiuser multichannel identification. Starting with the deterministic approach, we compare the identifiability conditions on the channel and the sources of training sequence based channel identification, blind and semi-blind channel identification. Further on, we use the stochastic approach with Gaussian priors for the source s...
متن کاملBlind MIMO channel identification from second order statistics using rank deficient channel convolution matrix
For multiuser systems, several direct blind identification algorithms require that the linear multiple-input multiple-output (MIMO) system have a full rank convolution matrix. This condition requires that the system transfer function be irreducible and column reduced. We show that this restrictive identification condition can be relaxed for some direct blind identification methods to accommodat...
متن کاملLocal convergence of the Sato blind equalizer and generalizations under practical constraints
An early use of recursive identification in blind adaptive channel equalization is an algorithm developed by Sato. An important generalization of the Sat0 algorithm with extensive analysis appears in the work of Benveniste, Goursat, and Ruget. These generalized algorithms have been shown to possess a desirable global convergence property under two idealized conditions. The convergence propertie...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- IEEE Trans. Signal Processing
دوره 50 شماره
صفحات -
تاریخ انتشار 2002