Single-output Finite Impulse Response Research Articles

A CS Recovery Algorithm for Model and Time Delay Identification of MISO-FIR Systems

This paper considers identifying the multiple input single output finite impulse response (MISO-FIR) systems with unknown time delays and orders. Generally, parameters, orders and time delays of an MISO system are separately identified from different algorithms. In this paper, we aim to perform the model identification and time delay estimation simultaneously from a limited number of observations. For an MISO-FIR system with many inputs and unknown input time delays, the corresponding identification model contains a large number of parameters, requiring a great number of observations for identification and leading to a heavy computational burden. Inspired by the compressed sensing (CS) recovery theory, a threshold orthogonal matching pursuit algorithm (TH-OMP) is presented to simultaneously identify the parameters, the orders and the time delays of the MISO-FIR systems. The proposed algorithm requires only a small number of sampled data compared to the conventional identification methods, such as the least squares method. The effectiveness of the proposed algorithm is verified by simulation results.

An improved least squares blind channel identification algorithm for linearly and affinely precoded communication systems

Certain linear and affine precoders introduce enough algebraic redundancy to enable the receiver to identify a. single-input single-output finite-impulse response channel without making any statistical assumptions on the source sequence. However, quite surprisingly, the traditional steepest descent least squares algorithm for estimating the channel often fails to converge, even in the absence of noise. This article explains why this is the case and derives a novel steepest descent algorithm on complex projective space that is guaranteed to converge. The complex projective space formulation also provides a standard framework for understanding different performance measures proposed in the literature.