Adaptive decision feedback detection with constellation constraints for multi-antenna systems

This paper considers the joint design of bit loading, precoding and receive filters for a multiple-input multiple-output (MIMO) digital communication system employing decision feedback (DF) detection at the receiver. Both the transmitter as well as the receiver are assumed to know the channel matrix perfectly. It is well known that, for linear MIMO transceivers, a diagonal transmission (i.e., orthogonalization of the matrix channel) is optimal for some criteria. Surprisingly, it was shown five years ago that for the family of Schur-convex functions an additional rotation of the symbols is necessary. However, if the bit loading is optimized jointly with the linear transceiver, then the rotation is unnecessary. Similarly, for DF MIMO transceivers, a rotation of the symbols is sometimes needed. The main result of this paper shows that for a DF MIMO transceiver where the bit loading is jointly optimized with the transceiver filters, the rotation of the symbols becomes unnecessary and, consequently, also the DF part of the receiver is not required.

A systematic approach to decision feedback multiuser detection is introduced for the joint detection of symbols of K simultaneously transmitting users of a synchronous correlated waveform multiple-access (CWMA) channel with Gaussian noise. A new performance criterion called symmetric energy is defined which is a low-noise indicator of the joint error rate that at least one user is detected erroneously. Even the best linear detectors can perform poorly in terms of symmetric energy compared to the maximum-likelihood detector. A general class of decision feedback detectors (DFDs) is defined with O(K) implementational complexity per user. The symmetric energy of arbitrary DFD and bounds on their asymptotic effective energy (AEE) performance are obtained along with an exact bit-error rate and AEE analysis for the decorrelating DFD. The optimum DFD that maximizes symmetric energy is obtained. Each one of the K! optimum, decorrelating, and conventional DFDs, that correspond to the K! orders in which the users can be detected, are shown to outperform the linear optimum, decorrelating, and conventional detectors, respectively, in terms of symmetric energy. Moreover, algorithms are obtained for determining the choice of order of detection for the three DFDs which guarantee that they uniformly (user-wise) outperform their linear counterparts. In addition to optimality in symmetric energy, it is also shown that under certain conditions, the optimum DFD achieves the AEE performance of the exponentially complex maximum-likelihood detector for all users simultaneously. None of the results of this paper make the perfect feedback assumption. The implications of our work on power control for multiuser detection are also discussed.

This paper describes a new approximate maximum-likelihood (ML) MIMO detection approach by studying a Lagrangian dual relaxation (LDR) of ML. Unlike many existing relaxed ML methods, the proposed LDR employs a discrete domain for the problem formulation. We find that the proposed LDR exhibits an intriguing relationship to the lattice decoders (LDs) and the lattice reduction aided (LRA) detectors, both of which have caught much attention recently. Specifically, regularization in LDs, which was proposed to mitigate out-of-bounds symbol effects, can alternatively be interpreted as a way to constrain the symbol decision within bounds in a Lagrangian sense. We handle the LDR problem by using a projected subgradient method. The resultant method may physically be viewed as an adaptive regularization control in which a sequence of LDs are involved. Based on this newly developed insight, we propose two additional iterative LDR-based detectors using LRA decision-feedback (DF) and "lazy" DF. By simulation results, we show that the LDR LRA-DF and lazy-DF detectors yield better symbol error rate performance than the MMSE-regularized LRA-DF and DF detectors, respectively, where the SNR gaps can be more than 3dB.

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.

The large-system performance of iterative multiuser decision-feedback detectors (DFDs) is studied for synchronous coded direct-sequence code-division multiple access. Both successive and parallel demodulation of users are considered. The filters are optimized according to the minimum mean-squared error criteria, assuming perfect feedback. We first consider Viterbi decoding with hard decision feedback, and compute union bounds on the large-system error rate. We then consider maximum a posteriori (MAP) decoding with soft decision feedback, and evaluate the error rate semianalytically by assuming the log-likelihood ratios computed by the MAP decoder are Gaussian random variables. Performance is studied numerically as a function of noise level, spectral efficiency, and code rate. Results show that soft decision feedback gives substantial gains relative to hard decision feedback. At moderate spectral efficiencies (users divided by bandwidth expansion less than 0.9), the iterative DFDs with soft decision feedback based on a posteriori probabilities can achieve near-single-user performance at an E/sub b//N/sub 0/ close to the large-system capacity bound.

We consider interference rejection for code-division multiple-access (CDMA) channels using decision-feedback detectors. Performance of zero-forcing and the minimum mean square error (MMSE) multiuser decision-feedback detectors is studied, and the full and partial feedback approaches are investigated. We also derive the maximum-likelihood detector based on the white noise CDMA channel model. Comparison among the decision-feedback detectors, the two-stage receivers, the conventional detector, and the linear decorrelating detector is undertaken for a four-user bandwidth-efficient asynchronous CDMA channel. We find that the decision-feedback detectors compare favorably to other suboptimal methods and maintain good performance under diverse channel conditions. This conclusion is further strengthened by performance analysis of the decision-feedback detector for a two-user synchronous CDMA flat Rayleigh fading channel. >

Existing work on decision feedback detection (DFD) of differential space-time modulation (DTSM) were largely confined to diagonal constellations. In other works considering nondiagonal constellations, the temporal variation of fading in the DTSM supersymbol duration was ignored. In this paper, we take a close look at the DFD receiver structure for nondiagonal DSTM in temporally correlated fading. We identify the constellations of which the error performance is not influenced by ignorance of fading variation. In addition, by analyzing the error performance, we demonstrate that existing DFD, is however, fundamentally mismatched to other constellations in fast fading. A major conclusion is that diagonal design still plays an important role for the efficacy of DFD for nondiagonal constellation in fast fading.

In the underwater passive positioning systems (UPPS), it involves a key technology of multi-user communication that the beacons synchronously send positioning messages to the targets. Interferences from other users, referred to multi-access interferences (MAIs), can induce significant bit errors for the desired user. In this paper, we designed an underwater acoustic Code Division Multiple Access (CDMA) system using the coded cyclic shift key (CCSK) modulation, and proposed a hybrid MAI cancellation scheme based on cyclic shift inverse matrix transform (CSIMT) and recursive least square (RLS) in the CDMA system. The hybrid scheme can suppress MAI better than RLS or CSIMT, and meets the requirements of strong stability to support reliable transmission for UPPS. The CSIMT interference cancellation performs well under the far-near effects, which doesn’t depend on the accuracy of the estimation of transmitted data, and the strong MAI can be reduced by transformation of the zero-forcing correlation values using m sequence cyclic shift inverse matrix. The RLS interference cancellation is used to mitigate MAI form the detected users with comparable power, by using the estimated the channel impulse response between the receiver and the detected users, and the regenerated signal of detected users form decoder output, which allows of strong error-correcting codes, and it’s robust in an asynchronous environment. The theoretical analysis and experimental result show that the hybrid MAI cancellation scheme can effectively suppress MAI better. The shallow water sea trial was carried out near Dalian Tiger Beach Ocean Park in China, at a distance of about 5 km, the data rates of 100bps, where three users could communicate asynchronously with low failure ratio and can match the UPPS application.

An analytical framework for noncoherent decision feedback detection is introduced while considering nonorthogonal binary modulation (NBM) over the synchronous Gaussian K-user channel. Following the key idea of noncoherent decorrelating decision feedback detection (NC-DDFD) proposed previously, a K-parameter class of NC-DDFDs is defined. The symmetric energy measure is defined as the worst-case (over users) asymptotic effective energy for noncoherent detection. Without making any simplifying assumption about error propagation, the NC-DDFD that optimizes symmetric energy among the K parameter class of detectors is derived. Since the NC-DDFD based on the generalized likelihood ratio test (GLRT) belongs to the K-parameter class of NC-DDFDs, the optimum NC-DDFD outperforms the GLRT based NC-DDFD in symmetric energy. Like the latter detector, the optimum NC-DDFD does not require the knowledge of the energies or phases of any of the users' transmissions. Exact expressions for symmetric energy and upper and lower bounds for symbol error rate (SER) and asymptotic effective energies are obtained for the optimum NC-DDFD. Rules for ordering users are obtained that guarantee that the optimum NC-DDFD can user-wise outperform a parallel bank of post-decorrelative GLRT detectors.

Recently proposed orthogonal time frequency space (OTFS) modulation has been considered as a promising candidate for accommodating various emerging communication and sensing applications in high-mobility environments. In this paper, we propose a novel cross domain iterative detection algorithm to enhance the error performance of OTFS modulation. Different from conventional OTFS detection methods, the proposed algorithm applies basic estimation/detection approaches to both the time domain and delay-Doppler (DD) domain and iteratively updates the extrinsic information from two domains with the unitary transformation. In doing so, the proposed algorithm exploits the time domain channel sparsity and the DD domain symbol constellation constraints. We evaluate the estimation/detection error variance in each domain for each iteration and derive the state evolution to investigate the detection error performance. We show that the performance gain due to iterations comes from the non-Gaussian constellation constraint in the DD domain. More importantly, we prove that the proposed algorithm can indeed converge and, in the convergence, the proposed algorithm can achieve almost the same error performance as the maximum-likelihood sequence detection even in the presence of fractional Doppler shifts. Furthermore, the computational complexity associated with the domain transformation is low, thanks to the structure of the discrete Fourier transform (DFT) kernel. Simulation results are consistent with our analysis and demonstrate a significant performance improvement compared to conventional OTFS detection methods.

This paper investigates the design and analysis of minimum mean square error (MMSE) turbo decision feedback equalization (DFE), with expectation propagation (EP), for single carrier modulations. Classical non iterative DFE structures have substantial advantages at high data rates, even compared to turbo linear equalizers - interference cancellers (LE-IC), hence making turbo DFE-IC schemes an attractive solution. In this paper, we derive an iterative DFE-IC, capitalizing on the use of soft feedback based on expectation propagation, along with the use of prior information for improved filtering and interference cancellation. This DFE-IC significantly outperforms exact turbo LE-IC, especially at high spectral efficiency, and also exhibits various advantages and performance improvements over existing variants of DFE-IC. The proposed scheme can also be self-iterated, as done in the recent trend on EP-based equalizers, and it is shown to be an attractive alternative to linear self-iterated receivers. For time-varying (TV) filter equalizers, an efficient matrix inversion scheme is also proposed, considerably reducing the computational complexity relative to existing methods. Using finite-length and asymptotic analysis on a severely selective channel, the proposed DFE-IC is shown to achieve higher rates than known alternatives, with better waterfall thresholds and faster convergence, while keeping a similar computational complexity.

This paper presents a novel adaptive reduced-rank multiple-input-multiple-output (MIMO) equalization scheme and algorithms based on alternating optimization design techniques for MIMO spatial multiplexing systems. The proposed reduced-rank equalization structure consists of a joint iterative optimization of the following two equalization stages: 1) a transformation matrix that performs dimensionality reduction and 2) a reduced-rank estimator that retrieves the desired transmitted symbol. The proposed reduced-rank architecture is incorporated into an equalization structure that allows both decision feedback and linear schemes to mitigate the interantenna (IAI) and intersymbol interference (ISI). We develop alternating least squares (LS) expressions for the design of the transformation matrix and the reduced-rank estimator along with computationally efficient alternating recursive least squares (RLS) adaptive estimation algorithms. We then present an algorithm that automatically adjusts the model order of the proposed scheme. An analysis of the LS algorithms is carried out along with sufficient conditions for convergence and a proof of convergence of the proposed algorithms to the reduced-rank Wiener filter. Simulations show that the proposed equalization algorithms outperform the existing reduced- and full- algorithms while requiring a comparable computational cost.

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 the single-carrier M-ary differential phase-shift keying (MDPSK), the multiple-symbol differential detector, or the noncoherent maximum-likelihood sequence detector (NSD), and its three special cases, namely, the noncoherent one-shot detector, the linearly predictive decision-feedback (DF) detector, and the linearly predictive Viterbi receiver are reviewed based on a hierarchical interpretation. For the multicarrier transmission, the differential orthogonal frequency division multiplexing (OFDM) systems with diversity reception are discussed. It is well known that there are two types of differential OFDM systems, namely, the time domain differential OFDM (TD-OFDM) and the frequency domain differential OFDM (FD-OFDM). In this paper, the NSD and its special cases are incorporated to the differential OFDM systems. Furthermore, we provide a simple closed-form bit-error-rate (BER) expression for the differential OFDM systems utilizing the noncoherent one-shot detector with diversity reception in the time-varying multipath Rayleigh fading channels. Numerical results have revealed that, with multi-antenna diversity reception, the performance of the noncoherent one-shot detector is improved significantly. However, when only one or two receive antennas are available, the implementation of the linearly predictive DF detector or the linearly predictive Viterbi receiver is necessary for achieving better and satisfactory performance.

For the two-branch space-time (ST) block-coded direct-sequence code-division multiple-access (DS-CDMA) systems, the impacts of a time-varying multipath channel on the downlink transmission are analyzed. By considering the systems using the random binary spreading code (RBSC) and deterministic binary spreading code (DBSC), the effects of the multipath interference and multiuser interference are included in the analyses of the bit-error rate and bit-error outage. Also, for the performance analysis of the system employing the decision-feedback (DF) detector, the effect of error propagation is taken into account. It is known that enlarging the spreading factor can enhance the interference-rejection ability of a DS-CDMA system and, hence, can improve the performance. However, it also lengthens the symbol duration and, thus, stiffens the diversity penalty resulting from the channel variation within an ST-code-word duration. Thus, a moderate spreading factor should be chosen. In this paper, for the RBSC system using the simple-maximum-likelihood (SML) detector, we derive an optimum spreading factor that is optimum in the minimum-error-probability sense. Numerical results have revealed that the derived optimum spreading factor is a good estimate of the ones for the DBSC systems using the SML, zero-forcing, and DF detectors. Therefore, it is very useful for system designers in determining the system parameters