Reduced-complexity equalization techniques for ISI and MIMO wireless channels in iterative decoding

Two reduced-complexity soft-input soft-output trellis decoding techniques are presented in this paper for equalizing single-input single-output intersymbol interference (ISI) channels and multiple-input multiple-output (MIMO) frequency selective fading channels. Given a trellis representing an ISI channel, the soft-output M-algorithm (SOMA) reduces the complexity of equalization by retaining only the best M survivors at each trellis interval. The remaining survivors are discarded. The novelty of the SOMA is the use of discarded paths to obtain soft-information. Through a simple update-and-discard procedure, the SOMA extracts reliable soft-information from discarded paths which enables a large trellis to be successfully decoded with a relatively small value of M. To decode a trellis representing a MIMO frequency selective fading channel, two challenges are faced. Not only that the trellis has a large number of states, the number of branches per trellis interval is also enormous. The soft-output trellis/tree M-algorithm (SOTTMA) expands each trellis interval into a tree-like structure and performs the M-algorithm twice: once at each trellis interval to reduce the number of states and the other at each tree sub-level to remove unwanted branches. With the proposed technique, high-order trellises with million of branches per interval can be decoded with modest complexity.     

Blind equalization for broadband access

This article discusses the general principles of blind equalization and its use in emerging broadband access applications such as FTTC and xDSL. New results obtained for these applications are also presented     

Frequency domain equalization for single-carrier broadband wirelesssystems

Broadband wireless access systems deployed in residential and business environments are likely to face hostile radio propagation environments, with multipath delay spread extending over tens or hundreds of bit intervals. Orthogonal frequency-division multiplex (OFDM) is a recognized multicarrier solution to combat the effects of such multipath conditions. This article surveys frequency domain equalization (FDE) applied to single-carrier (SC) modulation solutions. SC radio modems with frequency domain equalization have similar performance, efficiency, and low signal processing complexity advantages as OFDM, and in addition are less sensitive than OFDM to RF impairments such as power amplifier nonlinearities. We discuss similarities and differences of SC and OFDM systems and coexistence possibilities, and present examples of SC-FDE performance capabilities     

Reduced-complexity UWB time-reversal techniques and experimental results

This paper presents a reduced-complexity time reversal technique for ultra-wideband (UWB) communications. Time reversal takes advantage of rich scattering environments to achieve signal focusing via transmitter-side processing, which enables the use of simple receivers. The goal of this paper is to demonstrate a UWB time reversal system architecture based on experimental results and practical pulse waveform, taking into account some practical constraints, and to show feasibility of UWB time reversal. Pre-decorrelating in addition to time reversal processing is considered for a downlink multiuser configuration. Multiple transmit antennas are employed to improve the performance.     

Turbo space-time equalization of TCM for broadband wireless channels

This paper presents a space-time turbo (iterative) equalization method for trellis-coded modulation (TCM) signals over broadband wireless channels. For fixed wireless systems operating at high data rates, the multipath delay spread becomes large, making it impossible to apply trellis-based equalization methods. The equalizer proposed here consists of a broadband beamformer which processes antenna array measurements to shorten the observed channel impulse response, followed by a conventional scalar turbo equalizer. Since the applicability of trellis-based equalizers is limited to additive white noise channels, the beamformer is required to preserve the whiteness of the noise at its output. This constraint is equivalent to requiring that the finite-impulse response (FIR) beamforming filters must have a power complementarity property. The power complementarity property imposes nonnegative definite quadratic constraints on the beamforming filters, so the beamformer design is expressed as a constrained quadratic optimization problem. The composite channel impulse response at the beamformer output is shortened significantly, making it possible to use a turbo equalizer for the joint equalization and decoding of trellis modulated signals. The proposed receiver structure is simulated for two-dimensional TCM signals such as 8-PSK and 16-QAM and the results indicate that the use of antenna arrays with only two or three elements allows a large decrease in the channel signal-to-noise ratio needed to achieve a 10/sup -4/ bit-error rate.     

A blind equalization with the sign algorithm for broadband access

This paper presents an optimal reduced constellation point of sign reduced constellation algorithm (SRCA) for square and nonsquare carrierless amplitude and phase (CAP)/QAM signal constellations. Convergence characteristics of the SRCA algorithm are analyzed and compared to those of the RCA algorithm     

On frequency-domain equalization and diversity combining for broadband wireless communications

This paper is concerned with the use of frequency-domain equalization (FDE) and space diversity within block transmission schemes for broadband wireless communications. The expected performance with both multicarrier (MC) and single-carrier (SC) modulations is emphasized, when a cyclic prefix, long enough to cope with the maximum relative channel delay, is appended to each transmitted block. A set of numerical results is presented and discussed, with the help of appropriate, analytical performance bounds which are conditional on a given channel realization. These bounds are used to explain the performance advantage of the SC/FDE option, the benefits of space diversity, and the impact of the criterion for computing the FDE parameters.     

Fast recovery equalization techniques for DTV signals

Blind equalizers do not require any training sequence for the initial startup period but rather perform equalization blindly on the data directly. In this paper, a general approach for designing such equalizers for 8-VSB transmission systems is presented. The candidate algorithms considered here include Godard's algorithm (Godard 1980), Sato's algorithm (Sato 1975), the G-pseudo error algorithm using Sato's function and the G-pseudo error algorithm using Godard's function. This paper analyzes these algorithms for the 8-VSB transmission format and recommends the most suitable algorithm. The performance comparison parameters include MSE, convergence characteristics, computational load and accuracy of estimating the channel     

Support vector machine techniques for nonlinear equalization

The emerging machine learning technique called support vector machines is proposed as a method for performing nonlinear equalization in communication systems. The support vector machine has the advantage that a smaller number of parameters for the model can be identified in a manner that does not require the extent of prior information or heuristic assumptions that some previous techniques require. Furthermore, the optimization method of a support vector machine is quadratic programming, which is a well-studied and understood mathematical programming technique. Support vector machine simulations are carried out on nonlinear problems previously studied by other researchers using neural networks. This allows initial comparison against other techniques to determine the feasibility of using the proposed method for nonlinear detection. Results show that support vector machines perform as well as neural networks on the nonlinear problems investigated. A method is then proposed to introduce decision feedback processing to support vector machines to address the fact that intersymbol interference (ISI) data generates input vectors having temporal correlation, whereas a standard support vector machine assumes independent input vectors. Presenting the problem from the viewpoint of the pattern space illustrates the utility of a bank of support vector machines. This approach yields a nonlinear processing method that is somewhat different than the nonlinear decision feedback method whereby the linear feedback filter of the decision feedback equalizer is replaced by a Volterra filter. A simulation using a linear system shows that the proposed method performs equally to a conventional decision feedback equalizer for this problem     

Spatial and temporal equalization for broadband wireless indoornetworks at millimeter waves

The combined use of adaptive antennas and decision feedback equalization (DFE) is analyzed in a realistic propagation scenario at millimeter waves, taking the direction of arrivals (DOA's) of the received paths into account. The joint antennas and DFE scheme, with one forward filter for each antenna and a single feedback filter (FBF), can be viewed as a spatial and temporal DFE (ST-DFE). The performance of this solution is compared with the cascade of adaptive antenna used for beamforming and DFE. It is found that ST-DFE achieves better performance since it combines the beamforming capability of the antenna array with the equalization properties of the DFE, with great advantages especially when rays arrive from similar angles. The mean square error (MSE) is analytically derived for infinitely long filters in a quasi-static environment with multiple rays having different DOAs, and compared (for the two-path model) with simulation results assuming filters with a small number of taps. Finally, service availability through coverage evaluation is developed and compared with that of a coded-orthogonal frequency division multiplexing (C-OFDM) system     

Trellis-based soft-output adaptive equalization techniques for TDMAcellular systems

The concatenation of an equalizer and a Viterbi (1967) decoder is a powerful means for improving receiver performance in wireless communication systems. A soft-output equalizer increases the impact of this combination by enabling the use of soft-decision Viterbi decoding. It is well known that the maximum a posteriori (MAP) algorithm provides optimal reliability information, but at the cost of substantial complexity. This paper contains the results of an investigation into the design and performance of soft-output adaptive equalization techniques based on suboptimum trellis-based soft-output decoding algorithms. It is shown that the performance improvement relative to hard output equalizers is substantial, while the cost in terms of complexity is modest. A time-division multiple-access (TDMA) cellular system is used as the basis for comparisons. Simulation results and a complexity analysis are presented     

Finite dictionary techniques for MSER equalization in RKHS

Adaptive channel equalization is a signal processing technique to mitigate inter-symbol interference in a time dispersive channel. For adaptive equalization, minimum mean square error (MMSE) criterion-based reproducing kernel Hilbert spaces (RKHS) approaches such as the kernel least mean squares (KLMS) algorithm and its variants have been suggested in the literature for nonlinear channels. Another optimality criterion, based on minimum bit/symbol error rate (MBER/MSER), is a better choice for adapting an equalizer as compared to MMSE criterion. A kernel-based minimum symbol error rate (KMSER) equalization algorithm combines minimum symbol error rate (MSER)-based approaches with RKHS techniques. However, most algorithms in RKHS such as KMSER/KLMS require infinite storage requirement and hence cannot be practically implemented. To curtail the infinite memory requirement, and make adaptive algorithm suitable for implementation with finite memory and processing power, we propose quantized KMSER (QKMSER) and fixed-budget quantized KMSER (FBQKMSER)-based equalizers in this paper. In this paper, we derive the dynamical equation for MSE evolution of the QKMSER and FBQKMSER and find their performance to be asymptotically close to the MSE behavior of the KMSER. Also, it is found via simulations that the tracking performance of FBQKMSER is better than all the compared algorithms in this paper which is particularly useful for non-stationary channels.     

Reduced-complexity equaliser for nonlinear channels

The generalised cerebellar model arithmetic computer (GCMAC) network is applied to the problem of adaptive equalisation of nonlinear channels. The GCMAC-based equaliser is compared with other well-known structures such as the Volterra filter and the multi-layer perceptron. The results obtained show the effectiveness of the proposed structure for compensating strong nonlinearities     

Reduced-complexity circuit for neural networks

The Letter demonstrates that a 10 bit reduced-complexity VLSI circuit can be used in place of a 32 bit floating-point processor to speed up some neural network applications, reducing circuit area and power consumption by 88% with a negligible increase in RMS error. Applications were executed on a radial basis function neurocomputer using the reduced-complexity circuit implemented with FPGA technology. One application produced better results than had been previously obtained for a NASA data set using either neural network or non-neural network approaches     

Layered space-time receivers for frequency-selective wirelesschannels

Results in information theory have demonstrated the enormous potential of wireless communication systems with antenna arrays at both the transmitter and receiver. To exploit this potential, a number of layered space-time architectures have been proposed. These layered space-time systems transmit parallel data streams, simultaneously and on the same frequency, in a multiple-input multiple-output fashion. With rich multipath propagation, these different streams can be separated at the receiver because of their distinct spatial signatures. However, the analysis of these techniques presented thus far had mostly been strictly narrowband. In order to enable high-data-rate applications, it might be necessary to utilize signals whose bandwidth exceeds the coherence bandwidth of the channel, which brings in the issue of frequency selectivity. In this paper, we present a class of layered space-time receivers devised for frequency-selective channels. These new receivers, which offer various performance and complexity tradeoffs, are compared and evaluated in the context of a typical urban channel with excellent results     

Reduced-complexity design for triple-tunable frequency synthesiser

A new design method for a triple-tunable type DDFS-driven PLL frequency synthesiser is presented. Since only a phase accumulator is used in the DDFS (direct digital frequency synthesiser), the other parts of the DDFS such as ROM and a D/A converter can be excluded using the proposed method. Therefore, performance improvements are achieved such as circuit simplicity, reduced power consumption and switching time. In addition, the output of the designed DDFS is processed to provide a jitter-free input reference to the PLL. Simulation results show the validity and performance improvements of the proposed system, compared with the conventional system     

Experimentation on asynchronous switching techniques for broadband ISDN

This paper deals with a proposed implementation exploiting the new asynchronous transfer mode (ATM) multiplexing and switching techniques. In particular, the basic architectural and functional choices are outlined and various aspects are examined regarding the implementation of a switching arrangement using ATM switching techniques, giving some indication about its hardware and software architecture and the foreseeable system performance.     

Reduced-complexity decoding algorithm for low-density parity-checkcodes

A new reduced-complexity decoding algorithm for low-density parity-check codes that operates entirely in the log-likelihood domain is presented. The computationally expensive check-node updates of the sum-product algorithm are simplified by using a difference-metric approach on a two-state trellis and by employing the dual-max approximation. The dual-max approximation is further improved by using a correction factor that allows the performance to approach that of full sum-product decoding     

A least mean squares blind equalization techniques for OFDM systems

Classical multicarrier systems based on the discrete Fourier transform(dft) make use of aguard interval (gi) in order to enable a low complexity equalization scheme. Thisguard interval consists of a redundant prefix cyclically appended to each block of modulated symbols so as to exploit the cyclic convolution property of thedft. Therefore, besides decreasing the useful transmitted symbol rate, this technique is very specific todft-basedofdm systems. In order to implement a digital modulator, an oversampled version of the continuous signal that would be produced by the all-analog ideal modulator is often computed. This amounts to appending null symbols to the block of symbols to be modulated. This work shows that forcing the presence of these null symbols at the appropriate places on the receiver side is sufficient to equalize the channel. Here, a linear equalizer is adapted by minimizing a quadratic criterion based on the energy of the subband signals that should be zero. Since no knowledge about theuseful data is required, this method performs blind equalization. Moreover, it requires neither a guard interval nor any reference symbol. As a result, for a given channel bitrate budget, the data rate is increased