Adaptive Maximum-Likelihood Receiver for Carrier-Modulated Data-Transmission Systems

Abstract

A new look is taken at maximum-likelihood sequence estimation in the presence of intersymbol interference. A uniform receiver structure for linear carrier-modulated data-transmission systems is derived which for decision making uses a modified version of the Viterbi algorithm. The algorithm operates directly on .the output signal of a complex matched filter and, in contrast to the original algorithm, requires no squaring operations; only multiplications by discrete pulse-amplitude values.are needed. Decoding of redundantly coded sequences is included in the consideration. The reason and limits for the superior error performance of the receiver over a conventional receiver employing zero-forcing equalization and symbol-by-symbol decision making are explained. An adjustment algorithm for jointly approximating the matched filter by a transversal filter, estimating intersymbol interference present at the transversal filter output, and controlling the demodulating carrier phase and the sample timing, is presented.

Time-selective signaling and reception for communication over multipath fading channels

“…We first derive the optimal maximum-likelihood sequence detector [18]- [20]. Conditioned on the channel coefficients and 2 A pilot signal may be used to estimate these channel coefficients.…”

“…the symbol sequence, the log-likelihood function can be written as (9) where . Neglecting the terms independent of the symbol sequence, we can reduce this expression to obtain an iterative metric given by [18], [20] (10)…”

“…The output block (of multipath-Doppler components) corresponding to a symbol of interest (say th symbol) is corrupted by a noise vector that is Gaussian , where is the block of corresponding to the th symbol. The noise-whitening operation is performed as given by (17) and (18). The bit-error probability after combining these diversity branches is given by [21], [22], [25] (20)…”

Maximum likelihood sequence estimation from the lattice viewpoint

“…The upper bound is tight for moderate-to-large signal-to-noise ratio (SNR). In order to understand the optimal performance of the VA and the important concept of error event, we repeat Forney's performance analysis on the VA below (see also [61]). …”

“…Based on this lattice viewpoint, the 2 MLSE problem can be transformed into the closest lattice point problem. Making use of the regular structure of a lattice, we propose very efficient MLSE algorithms whose complexities are essentially independent of the number of transmit levels m. Obviously, these algorithms significantly simplify the implementation of an optimal receiver, especially for multi-level modulation schemes, as compared with the other algorithms known so far [27], [61], [1]. Nonetheless, the performance of our algorithms does depend on m. As an interesting result, unlike the VA whose complexity increases rapidly with m, the new algorithms favor m to be as large as possible.…”