High-performance VLSI architecture of adaptive decision feedback equalizer based on predictive parallel branch slicer (PPBS) scheme

A parallel adaptive decision feedback equalizer (ADFE) architecture is proposed. It allows adaptation at every sample to effectively equalize intersymbol interference for applications that operate at high sampling rates and require fast tracking capability. It is shown that if the effect of error propagation is small, the filter coefficients of the parallel ADFE will be exactly the same as those of a serially adapting ADFE. Simulation confirms that the parallel ADFE effectively tracks a time-varying channel with typical signal-to-noise ratios at a sampling rate four times higher than that of a serial ADFE, while under the same channel condition a previously proposed block ADFE fails to converge and becomes unstable.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A novel PAM4 receiver with adaptive threshold voltage, adaptive decision feedback equalizer and fixed linear equalizer has been presented. The proposed techniques enable threshold voltage to be adjusted automatically depending on data rate, signal swing and loss of channel. Consequently the receiver can be used in various situations without being manually calibrated. Adaptive decision feedback equalizer for PAM4 signaling is proposed, incorporated with sign-sign least mean square algorithm. Simulation results across lossy channel show proper convergence of threshold voltage and decision feedback equalizer values with the proposed receiver.

This paper presents a 6.25Gb/s adaptive decision feedback equalizer (DFE) for high speed backplane communication, which consists of a high-speed DFE and an adaptation engine based on Sign-Sign LMS algorithm. Half-rate structure and current mode logic are employed to pursue a high operating speed. The adaptation engine is composed of sense amplifiers (SA), a 5-bit up/down counter and a 5-bit DAC, which are implemented in CMOS logic at 781.25MHz. Designed in 0.18µm CMOS process, the equalizer has an area of 0.6×0.55mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> including I/O pads, and the static power consumption is 45.9mW under 1.8V power supply. Measurement results show that the proposed equalizer can adapt to signals achieved from PCB channels of different lengths, and the data rate can be up to 6.8Gb/s with horizontal eye opening of outputs larger than 0.8UI.

A 50Gb/s all-digital adaptive noise-suppression (NS) feed-forward equalizer (AFFE) and adaptive decision feedback equalizer (ADFE) for 2-level pulse amplitude modulation (2-PAM) serial link systems is presented. Based on a parallel extended incremental coefficients-lookahead scheme (EICL), we propose a Dual Data-paths Self-Lookahead Filter (DD-SLF) for ADFE. DD-SLF architecture has better energy efficiency and hardware area than an original SLF architecture due to the number of delay elements in the feedback loop is reduced. Furthermore, gated clock technique with the design idea of register file architecture is used to replace the pipelined delay elements to save power. The whole equalizer which operates at 1GHz system clock rate with 50 parallelisms is implemented in 40nm CMOS technology with a 0.38mm2 core area. The equalizer with 50Gb/s throughput rate achieves 2.6pJ/bit energy efficiency under 0.81V supply measurement results.

This brief presents a 1.62-to-10-Gb/s receiver for next generation video interconnected with an adaptive decision-feedback equalizer (DFE). The adaptive DFE facilitates the best bit error rate (BER) performance for various losses of video cables. A differential-pair stage is added to the DFE for extending an effective DFE range, presetting a minimum data level, and calibrating a mismatch offset. Circuit techniques are proposed to relax timing constraints for the direct-feedback DFE architecture. A referenceless frequency acquisition is performed during a dedicated clock recovery phase. The measured BER at 10 Gb/s is lower than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-12</sup> with a 23-dB loss cable. The RMS jitter and the peak-to-peak jitter of a recovered clock are measured as 2.38 ps and 17.5 ps, respectively. The prototype chip is implemented in 65-nm CMOS technology and occupies an active area of 0.254 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . This receiver consumes 24.4 mW at 10 Gb/s, corresponding to the energy efficiency of 2.44 pJ/b, which is the lowest compared to other recently published video interface receivers.

SUMMARYThis paper proposes a novel adaptive decision feedback equalizer (DFE) based on compact self‐constructing recurrent fuzzy neural network (CSRFNN) for quadrature amplitude modulation systems. Without the prior knowledge of channel characteristics, a novel training scheme containing both compact self‐constructing learning (CSL) and real‐time recurrent learning algorithms is derived for the CSRFNN. The proposed CSL algorithm adopts two evaluation criteria to intelligently decide the number of fuzzy rules that are necessary. The real‐time recurrent learning is performed simultaneously with the CSL at each time instant to adjust DFE parameters. The proposed DFE is compared with several neural network‐based DFEs on a nonlinear complex‐valued channel. The results show that the CSRFNN DFE is superior to classical neural network DFEs in terms of symbol‐error rate, convergence speed, and time cost. Copyright © 2011 John Wiley &amp; Sons, Ltd.

We proposed an adaptive two-stage nonlinear feedforward equalizer and decision feedback equalizer to minimize the negative influence of nonlinear distortions. A data rate of 960 Mbit/s is experimentally achieved on the guided visible-light transparent transmission over a 100-m ultra-large effective area pure silica fiber. The experimental results verified the effectiveness and improvement of the proposed method compared with the traditional feedforward post-equalizers.

In this work we present a per-subchannel nonlinear adaptive equalizer for a class of filter bank based multicarrier (FBMC) systems. We consider the class of exponentially modulated FBMCs with offset quadrature amplitude modulated (OQAM) input symbols. We present a fractionally spaced adaptive decision feedback equalizer (DFE) based on the least-mean-square (LMS) algorithm. The input of each equalizer comprises only the output of each subchannel. In the simulation results we show that, despite its increased computational complexity, the performance and higher bandwidth efficiency of OQAM FBMC systems makes them a competitive alternative to conventional multicarrier systems like cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM).

The paper describes an adaptive equalizer suitable for digital wireless systems. These systems are normally defined to work in indoor environments where channels show low delay spread values. For this reason, the possibility of signal equalization is not usually taken into account. Moreover, simplicity and cost are important parameters for these systems, and therefore simple and inexpensive receivers are used whenever it is possible. Because of their high capacity and low cost, it is interesting to study new applications based on these systems, for example, outdoor applications. However, these applications show higher delay spread values are necessary to perform an equalization process to maintain the communication quality. The problem appears when a limiter/discriminator receiver is used in the system due to the fact that this produces different distortions over the received signal which make the equalization process difficult. On the other hand, the modulation used in these systems may sometimes show modulation index variations that must be compensated for. The paper shows an equalization method that can perform the equalization process over the received baseband signal, compensating all distortions mentioned by using a shaped training sequence.

Within the population of voiceband telephone channels, few channel characteristics are as pervasive in their impairment of high-speed data communication as nonlinear distortion, which cannot be removed or equalized in the receiver as easily as can linear distortion. The purpose of this paper is to report on an investigation of a QAM receiver incorporating adaptive equalization of nonlinearities as well as adaptive decision feedback equalization and data-aided carrier recovery for mitigation of linear distortion and phase jitter, respectively. Nonlinearities are equalized by adding to the received in-phase and quadrature signals a weighted sum of nonlinear functionals of the received signal and of modulated previous receiver decisions. The choice of nonlinear terms in the sum is based on a channel model incorporating quadratic and cubic nonlinearities as well as linear dispersive elements. The adjustment of the weighting, or tap, coefficients for the various terms is based on a gradient algorithm, as is the adjustment of the linear tap coefficients and the carrier phase reference. The feasibility of nonlinearity equalization on real voiceband channels was confirmed in a test in which recorded 9600-bps QAM signals, received from a worse-than-average set of 17 voiceband telephone channels, were processed by a computer-simulated version of the proposed receiver (termed the NL receiver). The observed error rates for all channels were lower, in some cases by several orders of magnitude, than those achieved by computer-simulated versions of the linear receiver and of a decision feedback equalization receiver (termed the DFE receiver).

A 10 Gb/s adaptive analog decision feedback equalizer (DFE) with 6 taps is realized in 0.13 μm CMOS. A modified Cherry-Hooper stage is designed as the delay element in the feed-forward path. An analog implementation of the LMS algorithm is used to continuously adapt the feedback filter coefficients. A clock and data recovery (CDR) circuit is used to extract the clock from the DFE output. The adaptive DFE dissipates 452 mW and can equalize PRBS data corrupted by a 300m-long multimode fiber (MMF) achieving BER <; 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-13</sup> .

The adaptive multichannel Decision Feedback Equalizer (DFE) has been shown to be an effective algorithm for enabling reliable high rate acoustic communications in complex and time-varying underwater environments. The choice of the number of channels used in an equalizer presents a performance trade-off. The minimal achievable error that can be realized by the equalizer decreases as the number of channels increases. However, an increase in the number of channels increases the number of filter weights that need to be adapted. Thus, the computational complexity of least squares and Kalman type adaptation algorithms is proportional to the number of channels squared. In addition, the averaging interval required by an adaptation algorithm in order to achieve good performance grows linearly with the number of parameters. Thus, an increase in the number of M-DFE channels can reduce the rate of channel fluctuation that can successfully tracked by the M-DFE. The partitioning of an array into sub-arrays which are each independently equalized before combining their outputs can both improve performance and reduce complexity in processing real-world signals. The choice of the size and sensor locations for the subarrays is analyzed. The resulting adaptive subarray multichannel DFE algorithm is compared to other multichannel equalization algorithms.

In a TDMA mobile communication system, an adaptive decision feedback equalizer (DFE) is the common device to compensate the intersymbol interference caused by the multipath effect. Due to the fast fading characteristic of channels, most conventional DFEs use the recursive least square (RLS) algorithm. However, it is known that the RLS algorithm is computationally intensive and not easy to implement. The LMS is well known for its simple structure, however, due to its poor tracking property, it cannot be used. Recently, a multiple-training and multiple-tracking LMS (MTT-LMS) algorithm was developed. It was shown that the DFE trained by the MTT-LMS algorithm can yield a satisfactory result at moderate mobile speed. The MTT-LMS algorithm retains the simple structure of the LMS algorithm and is suitable for hardware implementation. In this paper, we consider the ASIC design of the MTT-LMS DFE for application to North American IS-54 systems. We have designed an efficient architecture which not only has small chip area but low clock rate. We also develop a new decision device to provide the desired signal for the MTT-LMS algorithm and the implementation of the device is simpler than the conventional one.

For PC DRAM buses, the number of slots per channel has decreased as data rates have increased. This limits the maximum memory capacity per channel. Signal equalization can be used to increase bit-rates for channels with a large number of slots and offer a cost effective method to solve the memory capacity problem. This paper presents a blind adaptive decision feedback equalizer (DFE) that enables high data-rates with a large number of slots per channel. Measurements at 2.6 Gb/s over a four-drop bus are presented.

This paper proposes using direct adaptation (DA)-based turbo equalization in multiple-input-multiple-output (MIMO) filtered multitone (FMT) time reversal (TR) acoustic communications to jointly suppress noise, residual co-channel interference (CCI) and intersymbol interference (ISI) after the TR process. Soft information-based adaptive decision feedback equalization (ADFE) adjusted according to the recursive expected least squares (RELS) algorithm, including interference cancellation and decoding, is used to construct the DA-based turbo equalization. In the proposed method, soft information is exchanged between soft symbols with soft decisions of decoding iteratively, and interference suppression is proceeded successively and iteratively until the performance is stable. The principle of the proposed method is analyzed, and based on the acoustic channel responses measured in a real experiment, the performance is assessed in relation to that of anther two methods. Compared with the MIMO-FMT TR underwater acoustic communication using interference suppression without error control coding (ECC), the proposed method performs better, benefitting from the ECC included in turbo equalization. Additionally, compared with the MIMO-FMT TR underwater acoustic communication using interference suppression based on hard decision equalization and decoding, the proposed method exhibits superior performance by exploiting soft information.