A practical low cost architecture for a MB-OFDM equalizer (ECMA-368)

The relative fast processing speed requirements in Wireless Personal Area Network (WPAN) consumer based products are often in conflict with their low power and cost requirements. In order to solve this conflict the efficiency and cost effectiveness of these products and the underlying functional modules become paramount. This paper presents a low-cost, simple, yet high performance solution for the receiver Channel Estimator and Equalizer for the Mutiband OFDM (MB-OFDM) system, particularly directed to the WiMedia Consortium Physical Later (ECMA-368) consumer implementation for Wireless-USB and Fast Bluetooth. In this paper, the receiver fixed point performance is measured and the results indicate excellent performance compared to the current literature(1).

RBF equalizer design using directional evolutionary multi-objective optimization

Whilst radial basis function (RBF) equalizers have been employed to combat the linear and nonlinear distortions in modern communication systems, most of them do not take into account the equalizer's generalization capability. In this paper, it is firstly proposed that the. model's generalization capability can be improved by treating the modelling problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets. Then, as a modelling application, a new RBF equalizer learning scheme is introduced based on the directional evolutionary MOO (EMOO). Directional EMOO improves the computational efficiency of conventional EMOO, which has been widely applied in solving MOO problems, by explicitly making use of the directional information. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good performance not only on explaining the training samples but on predicting the unseen samples.

Performance and conformance results of the deterministic DVB-T equalizer

One of the enablers for new consumer electronics based products to be accepted in to the market is the availability of inexpensive, flexible and multi-standard chipsets and services. DVB-T, the principal standard for terrestrial broadcast of digital video in Europe, has been extremely successful in leading to governments reconsidering their targets for analogue television broadcast switch-off. To enable one further small step in creating increasingly cost effective chipsets, the ODFM deterministic equalizer has been presented before with its application to DVB-T. This paper discusses the test set-up of a DVB-T compliant baseband simulation that includes the deterministic equalizer and DVB-T standard propagation channels. This is then followed by a presentation of the found inner and outer Bit Error Rate (BER) results using various modulation levels, coding rates and propagation channels in order to ascertain the actual performance of the deterministic equalizer(1).

Deterministic equalization and results of a DVB-T multipath equalizer for both 16-QAM and 64-QAM operation

Recent developments in the UK concerning the reception of Digital Terrestrial Television (DTT) have indicated that, as it currently stands, DVB-T receivers may not be sufficient to maintain adequate quality of digital picture information to the consumer. There are many possible reasons why such large errors are being introduced into the system preventing reception failure. It has been suggested that one possibility is that the assumptions concerning the immunity to multipath that Coded Orthogonal Frequency Division Multiplex (COFDM) is expected to have, may not be entirely accurate. Previous research has shown that multipath can indeed have an impact on a DVB-T receiver performance. In the UK, proposals have been made to change the modulation from 64-QAM to 16-QAM to improve the immunity to multipath, but this paper demonstrates that the 16-QAM performance may again not be sufficient. To this end, this paper presents a deterministic approach to equalization such that a 64-QAM receiver with the simple equalizer presented in this paper has the same order of MPEG-2 BER performance as that to a 16-QAM receiver without equalization. Thus, alleviating the requirement in the broadcasters to migrate from 64-QAM to 16-QAM Of course, by adding the equalizer to a 16-QAM receiver then the BER is also further improved and thus creating one more step to satisfying the consumers(1).

Nonlinear channel equalizer design using directional evolutionary multi-objective optimization

In this paper, a new equalizer learning scheme is introduced based on the algorithm of the directional evolutionary multi-objective optimization (EMOO). Whilst nonlinear channel equalizers such as the radial basis function (RBF) equalizers have been widely studied to combat the linear and nonlinear distortions in the modern communication systems, most of them do not take into account the equalizers' generalization capabilities. In this paper, equalizers are designed aiming at improving their generalization capabilities. It is proposed that this objective can be achieved by treating the equalizer design problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets, followed by deriving equalizers with good capabilities of recovering the signals for all the training sets. Conventional EMOO which is widely applied in the MOO problems suffers from disadvantages such as slow convergence speed. Directional EMOO improves the computational efficiency of the conventional EMOO by explicitly making use of the directional information. The new equalizer learning scheme based on the directional EMOO is applied to the RBF equalizer design. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good generalization capabilities, i.e., good performance on predicting the unseen samples.

A self-structured adaptive decision feedback equalizer

In a decision feedback equalizer (DFE), the structural parameters, including the decision delay, the feedforward filter (FFF), and feedback filter (FBF) lengths, must be carefully chosen, as they greatly influence the performance. Although the FBF length can be set as the channel memory, there is no closed-form expression for the FFF length and decision delay. In this letter, first we analytically show that the two-dimensional search for the optimum FFF length and decision delay can be simplified to a one-dimensional search and then describe a new adaptive DFE where the optimum structural parameters can be self-adapted.

An adaptive linear equalizer with optimum filter length and decision delay

The power of an adaptive equalizer is maximized when the structural parameters including the tap-length and decision delay can be optimally chosen. Although the method for adjusting either the tap-length or decision delay has been proposed, adjusting both simultaneously becomes much more involved as they interact with each other. In this paper, this problem is solved by putting a linear prewhitener before the equalizer, with which the equivalent channel becomes maximum-phase. This implies that the optimum decision delay can be simply ¯xed at the tap-length minus one, while the tap-length can then be chosen using a similar approach as that proposed in our previous work.

Adaptive nonlinear equalizer using a mixture of gaussians based on-line density estimator

This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) model, which is designed based on the minimum bit error rate (MBER) criterion, in the system setting of the intersymbol interference channel plus a co-channel interference. Our proposed algorithm is referred to as the on-line mixture of Gaussians estimator aided MBER (OMG-MBER) equalizer. Specifically, a mixture of Gaussians based probability density function (PDF) estimator is used to model the PDF of the decision variable, for which a novel on-line PDF update algorithm is derived to track the incoming data. With the aid of this novel on-line mixture of Gaussians based sample-by-sample updated PDF estimator, our adaptive nonlinear equalizer is capable of updating its equalizer’s parameters sample by sample to aim directly at minimizing the RBF nonlinear equalizer’s achievable bit error rate (BER). The proposed OMG-MBER equalizer significantly outperforms the existing on-line nonlinear MBER equalizer, known as the least bit error rate equalizer, in terms of both the convergence speed and the achievable BER, as is confirmed in our simulation study

Performance of GPRS coding scheme detection under severe multipath and co-channel interference as a function of soft-bit width

The General Packet Radio Service (GPRS) has been developed for the mobile radio environment to allow the migration from the traditional circuit switched connection to a more efficient packet based communication link particularly for data transfer. GPRS requires the addition of not only the GPRS software protocol stack, but also more baseband functionality for the mobile as new coding schemes have be en defined, uplink status flag detection, multislot operation and dynamic coding scheme detect. This paper concentrates on evaluating the performance of the GPRS coding scheme detection methods in the presence of a multipath fading channel with a single co-channel interferer as a function of various soft-bit data widths. It has been found that compressing the soft-bit data widths from the output of the equalizer to save memory can influence the likelihood decision of the coding scheme detect function and hence contribute to the overall performance loss of the system. Coding scheme detection errors can therefore force the channel decoder to either select the incorrect decoding scheme or have no clear decision which coding scheme to use resulting in the decoded radio block failing the block check sequence and contribute to the block error rate. For correct performance simulation, the performance of the full coding scheme detection must be taken into account.

Optimum decision delay of the finite-length DFE

This work investigates the optimum decision delay and tap-length of the finite-length decision feedback equalizer. First we show that, if the feedback filter (FBF) length Nb is equal to or larger than the channel memory v and the decision delay Δ is smaller than the feedforward filter (FFF) length Nf, then only the first Δ+1 elements of the FFF can be nonzero. Based on this result we prove that the maximum effective FBF length is equal to the channel memory v, and if Nb ≥ v and Nf is long enough, the optimum decision delay that minimizes the MMSE is Nf-1.

Flexible MMSE DFE using length and LAG adaptation

This paper investigates how to choose the optimum tap-length and decision delay for the decision feedback equalizer (DFE). Although the feedback filter length can be set as the channel memory, there is no closed-form expression for the feedforward filter length and decision delay. In this paper, first we analytically show that the two dimensional search for the optimum feedforward filter length and decision delay can be simplified to a one dimensional search, and then describe a new adaptive DFE where the optimum structural parameters can be self-adapted.

Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.