Least bit error rate adaptive nonlinear equalisers for binary signalling

Adaptive beamforming for binary phase shift keying communication systems

The problem of constructing adaptive minimum bit error rate (MBER) linear multiuser detectors is considered for direct-sequence code division multiple access (DS-CDMA) signals transmitted through multipath channels.Based on the approach of kernel density estimation for approximating the bit error rate (BER) from training data, a least mean squares (LMS) style stochastic gradient adaptive algorithm is developed for training linear multiuser detectors.Computer simulation is used to study the convergence speed and steady-state BER misadjustment of this adaptive MBER linear multiuser detector, and the results show that it outperforms an existing LMS-style adaptive MBER algorithm first presented at Globecom'98 by Yeh et al.

Block data transmission is an efficient scheme to mitigate the inter-symbol interference (ISI) caused by dispersive channels. Recent research work attempt to obtain optimal designs of precoders given various linear and non-linear receivers. In this paper we focus on the systems with optimal precoder designs based on the minimization of bit error rate (BER) which is the more meaningful criterion in data communications. The linear receivers employed in these systems include zero-forcing (ZF) and minimum mean square error (MMSE) equalizers. Recently, block decision feedback equalization (DFE) has also been suggested to be used in the design of such block data transmission systems. We also revisit the jointly optimum designs of the precoder coupled with the DFE receivers. First we derive the block-data error rate for all of these different systems with their corresponding optimal precoders. Then we rank their performance accordingly. Simulation results are also obtained to verify our analysis. Later, we evaluate the computational complexity on the various systems and draw some conclusions on their relative merits. Finally, we derive the lower and upper bounds of bit error rate (BER) considering error propagation for systems employing nonlinear equalizers.

This research aims to use the Adaptive Minimum Bit Error Rate (AMBER) for Wideband Code Division Multiple Access (WCDMA). AMBER and Normalized AMBER (NAMBER) algorithms for WCDMA systems are derived and implemented. Its Bit Error Rate (BER) performance is measured using a WCDMA Frequency Division Duplex (FDD) Downlink Physical Layer model. The new methods are compared to the original WCDMA system and the NLMS Adaptive Combiner. Results show around 5 dB performance gain over the single antenna system, and around 2 dB performance gain over the Dual Antenna Normalized Least Mean Squares (NLMS) Adaptive Combiner system in an Additive White Gaussian Noise channel at a BER of 10-2.5. However, complex computation requirements render the algorithms impractical for widespread use. Simplifications and alternative implementations have to be investigated.

In a companion paper, we have studied the zero-forcing (ZF) transceiver with decision feedback equalizer (DFE) over slowly time-varying narrowband multiinput multioutput (MIMO) channels. The space-time generalized triangular decomposition (ST-GTD) was used for the design of ZF-DFE transceivers. The space-time geometric mean decomposition (ST-GMD) ZF transceiver minimizes both the arithmetic mean square error (MSE) at the feedback detector and the average uncoded bit error rate (BER) in moderate high signal-to-noise ratio (SNR). This paper addresses the design problem of DFE transceiver without zero-forcing constraint. In the first part, a channel independent temporal precoder is superimposed on the conventional block-wise GMD-based minimum mean square error (MMSE) DFE transceiver to take advantage of the temporal diversity. In the second part, ST-GTD is applied for the design of MMSE DFE transceivers. With accurate channel prediction and space-time powerloading, the proposed ST-GMD MMSE transceiver minimizes the arithmetic MSE at the feedack detector, and maximizes Gaussian mutual information. For practical applications, the ST-GTD MMSE transceiver which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD MMSE system is also developed. In the convex region, our analysis shows that the proposed MMSE transceivers has better BER performance than the conventional GMD-based MMSE transceiver; the average BERs of the proposed systems are nonincreasing functions of the ST-block size. The superior performance of ST-GMD MMSE transceiver over the ST-GMD ZF transceiver is also verified analytically.

An asymptotically minimum bit error rate (BER) linear block precoder is determined for block-by-block communication systems employing linear minimum mean square error (MMSE) equalisation and disjoint detection. The problem is solved by a two-stage optimisation procedure in which a lower bound on the BER is first minimised, and then it is shown how this minimised lower bound can be achieved. Simulation results show that the BER performance of the proposed scheme is superior to the standard MMSE precoder and several other conventional systems such as orthogonal frequency division multiplexing. At reasonable BERs, the signal-to-noise ratio (SNR) gain can be of the order of several decibels.

Differential Evolution (DE) is a novel but powerful optimizer. It has been proved that the DE is superior to Genetic Algorithm (GA) in many real life applications. This paper proposed a memetic Differential Evolution assisted Minimum Bit Error Rate (MBER) linear detector for Multiple-input and multiple-output (MIMO) multi-user system. Compared with GA based MBER and other linear MIMO detectors such as minimum mean square error (MMSE) and zero forcing(ZF)detectors, the proposed scheme shows a better performance in terms of the bit error rate.

The paper derives a minimum bit error rate (BER) solution for the decision feedback equaliser (DFE) that employs a linear combination of the channel observations and the past decisions. We show that by using a geometric translation the DFE is reduced to a simpler linear equaliser. A BER expression for the linear equaliser is obtained under the assumption of linearly separable decision regions, and a method is proposed to optimally set the linear-combiner coefficients of the DFE. This minimum BER solution is superior to the usual minimum mean square error (MSE) solution.

A novel genetic algorithm (GA) assisted minimum bit error rate (MBER) beamforming technique is introduced. The performance of the proposed GAs is characterised by the probability density function (PDF) and the mean value of the achievable bit error rate (BER) at the beamformer's output. The results are also compared to the theoretical bounds. It is shown that GAs are suitable for MBER beamforming and that a trade-off between the complexity of the GA and its robustness against system parameter variations can be found.

We investigate adaptive minimum bit error rate (MBER) multiuser receivers for single (SC) and multicarrier (MC) CDMA systems in frequency selective channels. The approximate minimum BER (AMBER) receiver is examined and a Newton adaptive implementation is presented. Simulations results show how the proposed algorithm outperforms minimum mean squared error based algorithms.

In this paper, we propose a joint channel estimation and symbol detection (JCESD) algorithm relying on message-passing algorithms (MPA) for orthogonal frequency division multiple access (OFDMA) systems. The channel estimation and symbol detection leverage the framework of expectation propagation (EP) and belief propagation (BP) with the aid of Gaussian approximation, respectively. Furthermore, to reduce the computation complexity involved in channel estimation, the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula. Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%, compared with the traditional linear minimum mean square error (LMMSE) algorithm, and can approach to the bit error rate (BER) performance bound of perfectly known channel state information within 0.1 dB.

This paper presents some experimental results on both the channel estimation based minimum mean square error Turbo equalizer (CE MMSE-TEQ) and the direct-adaptation turbo equalizer (DA-TEQ) in single-input single-output (SISO) underwater acoustic (UWA) channels. For CE MMSE-TEQ, we compare the soft-decision feedback Turbo equalizer (SDFE), the bidirectional soft-decision feedback Turbo equalizer (Bi-SDFE) and the classic linear Minimum Mean Square Error (MMSE) Turbo equalizer in terms of bit error rate (BER) performance. For DA-TEQ, the recently proposed soft-decision direct-adaptation TEQ (Soft DA-TEQ) is evaluated with the same set of experimental data. Both QPSK and multilevel modulations (8PSK and 16QAM) have been tested with the symbol rate of 9.77 ksymbols/s. Experimental results show that the CE-TEQs are more robust in SISO underwater acoustic transmission under harsh channel conditions. Especially, with low pilot overheads, the recently proposed Bi-SDFE achieved low BER performance in all cases.

The conventional decision feedback equaliser (DFE) that employs a linear combination of channel observations and past decisions is considered. The design of this class of DFE is to construct a hyperplane that separates the different signal classes. It is well known that the popular minimum mean square error (MMSE) design is generally not the optimal minimum bit error rate (MBER) solution. A strategy is proposed for designing the DFE based on support vector machines (SVMs). The SVM design achieves asymptotically the MBER solution and is superior in performance to the usual MMSE solution. Unlike the exact MBER solution, this SVM solution can be computed very efficiently.

In this paper, linear precoding (LP) algorithm has been studied to improve the bit error rate (BER) performance of large scale multiple input multiple output (MIMO) system. A new technique of enhancing the BER performance of linear precoding algorithm without complexity in hardware and mathematical calculations is proposed and it is used on a traditional LP algorithms like a Maximum Ratio Transmission (MRT), a Zero-Forcing (ZF), a Regularized Zero-Forcing (RZF), and a Minimum Mean Square Error (MMSE) for Millimeter wave MU-MIMO communication system. A new technique is also used to mitigate the BER gab problem between (ZF, MMSE) and (RZF, MMSE) linear precoding algorithms. The result shows that with using the new technique, the BER performance of modified LP significantly outperform their traditional LP by 10−5 when using 4 element of BS antenna, 10−6 when using 16 element of BS antenna and mitigate the BER gab problem at different signal to noise ratio (SNR).

Iterative multiuser receivers constitute an effective solution for transmission over Multiple Access Interference (MAI) infested channels, when invoking a combined multiuser detector and channel decoder. Most reduced-complexity methods in this area use the Complex-valued Minimum Mean Squared Error (CMMSE) Multiuser Detector (MUD). Since the desired output of BPSK systems is real-valued, minimizing the Mean Square Error (MSE) between the beamformer's desired output and the real part of the beamformer output has the potential of significantly improving the attainable Bit Error Rate (BER) performance. We refer to this MMSE design as the Real-valued MMSE (RMMSE) receiver. In this paper, we explore a new Soft-Input Soft-Output (SISO) interference cancellation multiuser detection algorithm based on the novel Minimum BER (MBER) criterion. We demonstrate that the MBER turbo receiver outperforms both the CMMSE and the RMMSE algorithms, particularly in so-called `overloaded' beamforming systems, where the number of receiver antennas is lower than the number of users supported.