Equalization In Data Transmission Research Articles

Joint MAP equalization and channel estimation for frequency-selective and frequency-flat fast-fading channels

This paper presents a new fractionally-spaced maximum a posteriori (MAP) equalizer for data transmission over frequency-selective fading channels. The technique is applicable to any standard modulation technique. The MAP equalizer uses an expanded hypothesis trellis for the purpose of joint channel estimation and equalization. The fading channel is estimated by coupling minimum mean square error techniques with the (fixed size) expanded trellis. The new MAP equalizer is also presented in an iterative (turbo) receiver structure. Both uncoded and conventionally coded systems (including iterative processing) are studied. Even on frequency-flat fading channels, the proposed receiver outperforms conventional techniques. Simulations demonstrate the performance of the proposed equalizer.

A reduced-state soft-statistics-based MAP/DF equalizer for data transmission over long ISI channels

In this contribution, a novel version of the reduced-state maximum a posteriori probability/decision-feedback (MAP/DF) equalizer for intersymbol interference channels with long impulse responses is presented. The main feature of the proposed equalizer is that the soft statistics generated by the MAP receiver are employed to recursively compute a suitable index of the actual reliability of the (soft) decisions feeding the feedback filter. Therefore, in the presented equalizer, the usual (over-optimistic) assumption of error-free decisions at the input of the feedback filter is relaxed and improved performances are experienced, especially on channels with long impulse responses.

小特集 波形等化技術 ４． 通信・音響への応用 ４‐１ データ伝送用自動等化器

小特集 波形等化技術 ４． 通信・音響への応用 ４‐１ データ伝送用自動等化器

Recursive Equalization in Data Transmission--A Design Procedure and Performance Evaluation

A design procedure for the receiver of a pulse amplitude modulation system is developed for data transmission in the presence of intersymbol interference and noise. In the receiver, an estimate of each source symbol is made based on the WienerKolmogorov theory of minimum variance estimation for stationary time series. The resulting structure is called a recursive equalizer and its taps are obtained by taking the canonical factorization of the spectral density function followed by the operations of polynomial multiplication and division. The performance of the system is evaluated by calculating the probability of error versus signal-signal-to-noise ratio and Comparing it to the performance of a conventional tapped delay line equalizer. The specific example presented uses raised-cosine signaling through a channel with slope-attenuation distortion and a zero phase characteristic. For this example, the recursive equalizer is shown to exhibit superior-performance.

Optimum Timing Phase for an Infinite Equalizer

A digital equalizer for data transmission linearly combines a sequence of samples [b(r + kt), k = 0, ± 1, ···] of the received data wave to mitigate the effects of intersymbol interference and noise. A natural question is, How will the performance of such a system depend on the timing phase τ, 0 ≦ τ ≦ T? We examine this problem in considerable detail for an infinite equalizer using a mean-square measure of performance. Excess bandwidth results in a significant difference in performance between the best and worst timing phase. Under practical noise conditions, it is estimated that the excess bandwidth must be down to 1 or 2 percent before the timing effect becomes insignificant. With a 10-percent roll-off, a 3-dB penalty can be incurred by choosing a bad timing epoch. Our main result is that under conditions likely to be encountered on channels similar to voiceband telephone channels, the optimum sampling instants will be accurately approximated by the consecutive maxima and minima of the sine wave that result when an alternating sequence of positive and negative pulses (dotting sequence) is transmitted. There are no additional local minima of the minimum mean-square error as the timing phase is varied.

Recursive equalization in data transmission (Ph.D. Thesis abstr.)

Recursive equalization in data transmission (Ph.D. Thesis abstr.)

Relationship between source coding, channel coding, and equalization in data transmission

For data communication through a time-dispersive channel, the optimum channel decoder is shown to be a network which is matched to the channel encoder. In this context, channel decoding precedes equalization in the receiver hierarchy.