Iterative Soft Interference Cancellation Aided Minimum Bit Error Rate Uplink Receiver Beamforming

The paper considers the problem of constructing adaptive minimum bit error rate (MBER) neural network equalisers for binary signalling. Motivated from a kernel density estimation of the bit error rate (BER) as a smooth function of training data, a stochastic gradient algorithm called the least bit error rate (LBER) is developed for adaptive nonlinear equalisers. This LBER algorithm is applied to adaptive training of a radial basis function (RBF) equaliser in a channel intersymbol interference (ISI) plus co-channel interference setting. A simulation study shows that the proposed algorithm has good convergence speed, and a small-size RBF equaliser trained by the LBER can closely approximate the performance of the optimal Bayesian equaliser. The results also demonstrate that the standard adaptive algorithm, the least mean square (LMS), performs poorly for neural network equalisers because the minimum mean square error (MMSE) is clearly suboptimal in the equalisation setting.

Adaptive beamforming for binary phase shift keying communication systems

The multiuser detection is a signal processing tech- nique which enhances the performance and capacity in DS- CDMA technology. Since its complexity issue was too expensive to handle, there was focus on the suboptimal detectors. In this paper we propose a hybrid method called adaptive differential interference cancellation method (ADIC) which is a hybrid of the differential interference cancellation method and which is then combined in a adaptive way to determine a weight matrix which will map the outcome of the differential interference cancellation method to come out with a better performance. This paper also looks into the computational cost of different methods using the floating point operation (flops) which is a good estimation of the comparative computational cost if not the exact one. I. INTRODUCTION The conventional DS-CDMA match filter detector fails to combat these issues due three prominent drawbacks: unrealis- tic ucorrelated code, near-far problem (even with strict power control (1)), and tough multiple access interference (MAI). Many advanced signal processing approaches have been made to improve the performances of these kinds of detectors. In this paper we will study the different approaches that were made in this field and implement these methods to reach a conclusion about the detection methods. As the name of the topic suggests the focus of our work will be study and propose cost effective better performing multiuser detection method. We will explore Multiuser Detection Techniques in Synchronous CDMA environment. Multi-user detection deals with the development and ap- plication of joint demodulation and interference cancellation cancellation techniques for improved detection of a desired set of digital signals in the presence of multiple access interfer- ence, intersymbol interference and noise. Since veterbi forward dynamic algorithm (2) is used in case of Optimum multiuser detection (3) the complexity grows in with the increase in the number of users. Hence the complexity is immense which increases exponentially with the increase in the number of users. Looking ahead for lower complexity hence lesser cost of implementation, the paper proposes the use of sub-optimal linear detectors (4). The sub-optimal detector the paper next focuses on is Decorrelator type of Detector (5) which is optimal in least squares. This detector out performs the optimal detector in many respects. Then the Minimum Mean Square Error (MMSE) linear detector is proposed which tries to minimize the squared error from the required transformation. It is one of the most popular detectors in use due to its easiness to implement and its lower complexity. But then in the above detection methods the decisions made were based on certain linear transformation criterion and there are missing efforts to check the performance in between the detection process to improvise the transformation method better detection. So then the paper proposes Adaptive multiuser detection. Then the paper focuses on Interference cancellation methods which utilize the feedback to reduce Multiple Access Interference (MAI) in the detected bits. Under the Interference Cancellation umbrella the Successive Interference Cancellation (SIC) (6), (7) method is explored and simulated to observe the results. Then the next method which performs better than SIC and more commonly used in real life, called Parallel Interference Cancellation (PIC) (6), (8) is also implemented. Before going ahead to implement the final proposed detection method, this paper implements Differential Interference Cancellation (DIC) (9) method. And then this paper finally proposes an Inter- ference Cancellation method called the Adaptive Differential Interference Cancellation Multiuser Detection method which is cost effective in comparison to other Interference Cancellation methods as we will require lesser hardware (multipliers as in the SIC or Parallel Interference Cancellation (PIC)) for that matter. More ever since we are using adaptive method the desired BER can be further reduced. This proposed method will be discussed in detail in the following section.

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.

This paper concentrates on investigating an enhanced independent component analysis (ICA) method for blind separation of signals corrupted by noise in wireless communications. Because of the traditional classical ICA methods that always have an inadequate capacity of anti-noise or insufficient separable ability in noise circumstance without satisfying practical application requirements. For this reason, two mechanisms are conducted to establish the modified cost function and fulfill the optimization assignment in the process of constituting an enhanced ICA algorithm. This proposed algorithm can benefit tremendously from the derived minimum bit error rate (BER) criterion and the novel adaptive moment estimation (Adam) optimization approach. In this work, firstly, the novel cost function is obtained according to minimum BER fused into maximum likelihood (ML) principle-based ICA cost function. Furthermore, by utilizing Adam processing, the task of blind separation of mixed signals is implemented via optimizing this modified cost function. Lastly, theoretical analysis and experiment results corroborate the better effectiveness and robustness of the proposed enhanced ICA algorithm compared with a series of popular representative ICA methods.

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.

In this paper we present a relationship between supervised (MMSE) and unsupervised criteria for minimum bit error rate (BER) filtering. A criterion based on the probability density function (pdf) estimation which has an information theoretical approach is used to link the MMSE criterion and the maximum a posteriori one in order to obtain a linear filter that minimizes the BER. An analytical relationship among those three criteria is presented and analyzed showing the limits imposed to achieve minimum BER without training sequences when the pdf estimation-based criterion is considered.KeywordsMinimum Mean Square ErrorTraining SequenceBlind Source SeparationTransmitted SymbolEqualizer OutputThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This paper investigates the effect of other-cell multiple-access interference (MAI) on some suboptimal multiuser detectors such as decorrelating multiuser detector, parallel interference canceller and adaptive minimum mean-squared error (MMSE) multiuser detector. Based on the Gaussian approximation for other-cell MAI, the bit-error rate (BER) of each detector is derived. Both analytical results and simulations indicate that the performance degradation due to other-cell MAI is significant. It is also observed that the other-cell MAI introduces more errors to multiuser detectors that require prior information on users' signature waveforms.

Beamforming (BF) with multiple receiving antennas significantly improves the bit error rate (BER) performance for a DS-CDMA system in a flat Rayleigh fading environment. However, BF fails to suppress multiple access interference (MAI) completely, which results in an irreducible BER floor. Furthermore, soft-decision Viterbi decoding (VD) with BF further lowers the BER floor. The BER performance difference between the minimum mean square error (MMSE) linear multiuser detector (MUD) and zero forcing (ZF) MUD increases with the eigenvalue spread of the code correlation matrix. BF with MUD performs better than MUD alone, and BF+VD is much more effective at combating MAI than MUD+VD for low to moderate SNRs. In this regime, the performance of BF+VD approaches that of BF+MUD+VD, which clearly offers the best performance for all SNRs.

Space-Division Multiple Access-OFDM based wireless communication has the potential to significantly increase the spectral efficiency, system performance and number of users. Research in the development of efficient multiuser signal detection algorithms for such systems has generated much interest in recent years. This research proposes MUD schemes utilizing three neural network (NN) models like Feed Forward NN (FNN) without any hidden layer, FNN with a single hidden layer and Recurrent Neural Network (RNN) as possible alternatives to existing Genetic Algorithm (GA) based Minimum Bit Error Rate (MBER) MUD. Further, these techniques offer low complexity. Extensive simulation based performance study is carried out to prove the efficiency of the proposed techniques. Better performance of FNN with hidden layer and RNN compared to FNN without hidden layer is clearly observed in rank deficient MIMO scenario, where number of users exceeds the number of receiving antennas. The Bit Error Rate (BER) and complexity analysis of the proposed neural MUD schemes are close to optimal ML and show improvement over the previous implemented technique.

We considers the beamforming assisted multiple-antenna receiver for space-division multiple-access based multiuser systems that employ high-throughput quadrature amplitude modulation (QAM) signalling. The bit error ratio (BER) expression as the function of the beamformer's weight vector is derived, and the minimum BER (MBER) beamforming receiver is then obtained as the solution of the resulting optimisation problem that minimises the MBER criterion. A simplified conjugate gradient algorithm, which has previously demonstrated its effectiveness in solving the minimum symbol error ratio (MSER) optimisation problem, is employed to solve this MBER optimisation. For high-order QAM, although the bit decision is an inherently more complicated procedure than making a symbol decision, it turns out that the computational complexity of computing the MBER solution is similar to that of computing the MSER solution. As expected, our simulation results show that both the MBER and MSER systems achieve the same BER performance, and they significantly outperform the standard minimum mean squares error based solution.

Direct-sequence code-division multiple-access (DS-CDMA) is a popular multiple-access technology for wireless communications. However, its performance is limited by multiple-access interference and multipath distortion. Multiuser detection and space-time processing are two signal processing techniques employed to improve the performance of DS-CDMA. Two minimum probability of error-based space-time multiuser detection algorithms are proposed in this paper. The first algorithm, minimum joint probability of error (MJPOE), aims to minimize the joint probability of error for all users. The second algorithm, minimum conditional probability of error (MCPOE), minimizes the probability of error of each user conditioned on the transmitted bit vector, for each user individually. In both the algorithms, the optimal filter weights are computed adaptively using a gradient descent approach. The MJPOE algorithm is blind and offers a bit-error-rate (BER) performance better than the nonadaptive minimum mean squared error (MMSE) algorithm, at the cost of higher computational complexity. An approach for reducing the computational overheads of MJPOE using Gram-Schmidt orthogonalization is suggested. The BER performance of the MCPOE algorithm is slightly inferior to MMSE, however, it has a computational complexity linear in the number of users. Both blind and training-based implementations for MCPOE are proposed. Both MJPOE and MCPOE have a convergence rate much faster than earlier known adaptive implementations of the MMSE detector, viz. least mean square and recursive least squares. Simulation results are presented for synchronous single path channels as well as asynchronous multipath channels, with multiple antennas employed at the receiver.

A minimum bit error rate (MBER) multiuser detector designed for space division multiple access (SDMA) aided orthogonal frequency division multiplexing (OFDM) systems is proposed. It is shown that the MBER detector outperforms the minimum mean squared error (MMSE) detector, since the MBER detector directly minimises the BER, while the MMSE detector minimises the mean-squared error (MSE), which does not guarantee achieving the minimum BER. When supporting two users, the proposed MBER scheme substantially outperforms the classic MMSE arrangement in the investigated propagation scenario.

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.

Visible light communication (VLC) has emerged as a green, low-cost, and secure supplement for existing radio frequency (RF) based systems. Although promising, the performance of VLC based systems is limited by several impairments, which degrade the achievable bit error-rate (BER) performance, viz. variations in channel-gain due to user-mobility, and channel-estimation error. Hence, in this letter, the bit error rate (BER) of maximal ratio combining is quantified over a multiple-input multiple-output (MIMO) VLC system, while considering the aforementioned impairments. Next, using the derived expressions, exact and asymptotic combiners based on the minimum bit error-rate (MBER) criterion are formulated for MIMO VLC systems impaired by user-mobility, and channel-estimation error. The accuracy of the contributed expressions for BER, and the performance of the proposed MBER combiner (MBERC) are corroborated by simulations performed over realistic MIMO VLC channels. Additionally, it is found that the proposed MBERC delivers improved BER performance in presence of channel-estimation error and user-mobility, which makes the proposed methodology viable.