Mark Fimoff

Best linear unbiased channel estimation for frequency selective multipath channels with long delay spreads

We provide an iterative channel impulse response (CIR) estimation algorithm for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols. This iterative procedure calculates the (semi-blind) best linear unbiased estimate (BLUE) of the CIR. We first provide a formulation of the received data and correlation processing with the adjacent information symbol correlation taken into account, and we then present the connections of the correlation based CIR estimation scheme to the ordinary least squares CIR estimation. Simulation results are provided to demonstrate the performance of the novel algorithm.

A novel channel estimation method: Blending correlation and least-squares based approaches

In this paper we introduce a novel channel estimation method which uses symbol rate sampled signals, based on blending the least squares based channel estimation and the correlation based channel estimation methods. We first overview the shortcomings of the least squares and the correlation based channel estimation algorithm, where a training sequence is utilized in both cases. The performance of the new channel estimation method will be demonstrated, such that the channel estimation will be more robust, and the overall quality of the estimate will be improved by recovering the pulse shape which is naturally embedded in the overall channel impulse response. We will demonstrate how both methods can be combined effectively to minimize the problems associated with the effective channel delay spread being longer than the known training sequence can support.

Enhanced 8-VSB transmission for North-American HDTV terrestrial broadcast

We present a new robust backward compatible 8-VSB transmission system for HDTV terrestrial broadcast. The new transmission system allows better reception of signals for portable, mobile and indoor receivers. In the proposed system a scalable fraction of the main service is used to transmit robustly encoded data. The robust service has at least a 6 dB fade margin advantage over the main service. In addition, the data allocated to the robust stream can also be used at the receiver to improve the reception of the normal stream. The robust data is utilized by the normal stream receiver as randomly distributed training symbols which can be used in the equalizer to improve the receiver performance for dynamic multipath channels.

Decision feedback equalizers with constrained feedback taps for reduced error propagation

Error propagation is a serious concern when a decision feedback equalizer (DFE) is used in a communication system. This paper describes a method of mitigating the effects of error propagation by constraining the feedback tap coefficients. It is shown that the most natural method of constraining the feedback taps is to constrain the 1-norm of the tap vector. The paper also considers a constraint on the 2-norm of the feedback tap vector. The proposed method is demonstrated using the trellis coded 8-VSB system used by the ATSC terrestrial broadcast standard for digital television. Results show that the constraints do reduce error propagation in the DFE, but the performance is considerably better when a zero delay trellis decoder is used to determine the decisions in the feedback filter.

Structured channel estimation based decision feedback equalizers for sparse multipath channels with applications to digital TV receivers

In this paper, we investigate the performance of channel estimation based equalizers. We introduce two different channel estimation algorithms. Our first channel estimation scheme is a novel structured channel impulse response (CIR) estimation method for sparse multipath channels. The novel CIR estimation method was called blended least squares (BLS) which uses symbol rate sampled signals, based on blending the least squares based channel estimation and the correlation and thresholding based channel estimation methods. The second CIR estimation is called Variable thresholding (VT), and is based on improving the output of the correlation and thresholding based channel estimation method. We then use these two CIR estimates to calculate the decision feedback equalizer (DFE) tap weights. Simulation examples are drawn from the ATSC digital TV 8-VSB system. The delay spread for digital TV systems can be as long as several hundred times the symbol duration; however, digital TV channels are, in general, sparse where there are only a few dominant multipaths.

Approximate best linear unbiased channel estimation for frequency selective multipath channels with long delay spreads

We provide an iterative and a non-iterative channel impulse response (CIR) estimation algorithm for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols. The iterative procedure calculates the (semi-blind) best linear unbiased estimate (BLUE) of the CIR. The non-iterative version is an approximation to the BLUE CIR estimate, achieving almost similar performance, with much lower complexity. We first provide a formulation of the received data and correlation processing with the adjacent symbol correlation taken into account, and we then present the connections of the correlation based CIR estimation scheme to the ordinary least squares CIR estimation, and the BLUE CIR estimation. Simulation results are provided to demonstrate the performance of the novel algorithms for 8-VSB ATSC digital TV systems.

E-VSB-an 8T-VSB compatible system with improved white noise and multipath performance

Enhanced VSB (E-VSB) is a flexible, compatible outer coding enhancement to ATSC 8-VSB which trades payload bit rate for improved white noise and multipath performance when properly equipped receivers are utilized. It is transparent to legacy ATSC receivers. The coding method and experimental results are described.

Conjugate-gradient-based decision feedback equalization with structured channel estimation for digital Television

In this paper, we show how the convergence time of equalizers for 8-VSB based on the conjugate gradient (CG) algorithm can be considerably improved through initialization based on a channel estimate. We derive real and complex minimum mean-square error (MMSE) equalizers and implement them adaptively using the conjugate gradient, recursive least squares (RLS), and least mean squares (LMS) algorithms. We show that both CG and RLS have similar convergence times --- both are much faster than LMS. Since the CG algorithm is easily initialized, we compare several methods of initialization to determine how each affects convergence and then apply the best methods to initialize equalizers using channel estimates. We find that initializing the correlation matrices and filling the feedback taps with training symbols greatly speeds convergence of the CG adaptive equalizer, potentially approaching the rate of convergence when running the algorithm on the matrix equations using the actual channel.

Decision feedback equalizer design for insensitivity to decision delay

In this paper, we use an alternative approach to derive the minimum mean-square error decision feedback equalizer. This derivation yields insight which allows the equalizer to be designed so that its SINR performance is relatively insensitive to variations in the decision delay (also known as the cursor). The design, while generally applicable to the DFE, is illustrated using 8-level vestigial sideband modulation as used in the ATSC digital television standard. We simulate several channels and show that the SINR varies little across a relatively wide band of decision delays.

Computation of a constrained decision feedback equalizer for reduced error propagation

It has been previously shown that the effects of error propagation in a decision feedback equalizer may be reduced by constraining the 2-norm of the feedback filter. This paper describes three algorithms for calculating the constrained equalizer based on a channel estimate. An iteration function is derived for the Karush-Kuhn-Tucker multiplier and the algorithms are designed to quickly find a fixed point of this function. The algorithms include a modified regula falsi algorithm known as the Pegasus iteration, a modified secant algorithm, and a nonlinear fit to the iteration function. At each iteration, the conjugate gradient algorithm is used to solve the resulting linear equations. The algorithms are demonstrated on the 8-VSB terrestrial broadcast digital TV system. While all three algorithms exhibit good convergence characteristics, the nonlinear fit converges the fastest.