MMSE space-time multiuser decision-feedback detection in multiple-antenna SDMA systems over dispersive fading channels

We study a design of optimum finite-length space-time decision feedback equalization (STDFE) assisted multiuser detection (MUD) in space division multiple access (SDMA) systems to improve system capacity over fading channels. The MUD-STDFE receiver uses multi-dimensional finite-length anticausal symbol-spaced feedforward filter (FFF) and multi-dimensional feedback filter (FBF), where the optimality criterion is minimum mean-squared error (MMSE). This space-time DFE combined with MUD technology is capable of improving the performance significantly in a SDMA system. The algorithm for computing the tap coefficients of STDFE-MUD is presented and then applied to the fast error probability calculation using the Gauss quadrature rule (GQR), which offers accuracy as well as considerable saving of computer time.

Data transmission over HF channels is subject to phenomena of dispersion, absorption and multiple paths. Performance may be improved by using orthogonal frequency division multiplexing spread spectrum (OFDM-SS) systems. In OFDM-SS systems, transmitting data over slowly varying multi-path channels, both inter-symbol interference (ISI) and multiple-access interference (MAI) arise and should therefore be mitigated. Two adaptive non-linear equalization architectures based on the minimum mean-square error (MMSE) criterion are proposed and examined over such channels. The first receiver architecture is for single-user detection (SUD) consisting of a multiple-layer feed-forward filter (ML-FFF) and a feedback filter (FBF). The ML-FFF acts as a multi-path diversity combiner as well as canceller of precursor ISI and main-cursor MAI while the FBF acts as a canceller of post-cursor ISI. The second receiver architecture is for multi-user detection (MUD) where in addition to the first structure, it employs a centralized FBF (CFBF) for cancelling the MAI of previous symbols. Results indicate that an enhancement in capacity is obtained by the multi-user structure over the single-user structure. Additionally, it is demonstrated that both structures perform multi-path energy combining (Rake-like) when the delay spread is in excess of a symbol interval.

In this paper, we discuss multiuser detection based on wideband code division multiple access (WCDMA) protocols. Multirate transmission and spreading method of WCDMA systems introduce a problem that characteristics of multiple access interference (MAI) change periodically. General adaptive algorithms will not work in that situation. An improved adaptive minimum mean-squared error (MMSE) multiuser detection algorithm is proposed to solve the problem. During our processing procedures, output vector sequence, which is cyclostationary, of matched filter is divided into several stationary vector sequences by down sampling. Then we respectively process those sequences using a bank of adaptive transversal filters using least-mean-square (LMS) algorithm. The improved algorithm is analyzed under FDD mode of WCDMA protocols, in which S(2) short scrambling codes are applied. Simulation result shows that improved multiuser detection algorithm solves multirate problems well and effectively suppresses MAI under AWGN channels and multipath time-varying channels according to IMT-2000 Vehicular Model A. The improved adaptive MMSE algorithm has better performance than conventional detector and improved constant modulus algorithm using the same thinking.

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.

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.

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.

In this contribution, we consider the performance of multiple-input multiple-output (MIMO) code division multiple access (CDMA) system for digital image transmission over correlated Rayleigh fading channel. MIMO system employs multiple antennas both at the transmitter and receiver. In our work, we consider turbo coded system to investigate the performance of MIMO-CDMA system. We realize turbo code using parallel concatenated convolutional encoder and second convolutional encoder is preceded by random interleaver. Further the output of two convolutional encoder are punctured to get rate of ½. At the receiver, we employ iterative decoding algorithm to reduce the effect of multiple access interference (MAI) and Inter-Symbol-Interference (ISI) and median filters to reduce the effect of salt and pepper noise.. In particular, we evaluate the performance of coded MIMO-CDMA system using Zero forcing (ZF) - multi-user detection (MUD) and minimum mean square error (MMSE)-MUD detection technique to mitigate the effects of multi-stream interference (MSI). It is shown through the simulation study that our considered coded MIMO-CDMA system with MMSE algorithm achieves better picture quality with less signal-to-noise ratio (SNR) as compared to ZF MUD.

SummaryThe intelligent reflecting surface (IRS) has recently become the most promising technology to achieve maximum beam‐forming gain with a simultaneous wireless information and power transfer (SWIPT) system. Many existing studies perform a single IRS deployment or utilize space division multiple access (SDMA) and non‐orthogonal multiple access (NOMA) schemes. However, the existing schemes face high time complexity and block signal transmission for larger indoor communications. Hence, this article introduces a dual IRS‐aided multiuser SWIPT system by implementing rate‐splitting multiple access (RSMA) systems. To enhance the minimum achievable rate and ensure the minimum harvesting energy (HE), this study proposes a joint successive convex approximation with an integrated optimization algorithm (SCA‐IOA). The proposed algorithm jointly optimizes the reflecting beam forming and power splitting (PS) coefficient of all the users effectively. The simulation results demonstrate the effectiveness of the proposed techniques and produce an outstanding performance for deploying dual IRS and implementing RSMA compared to traditional SDMA and NOMA systems.

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.

This paper presents an iterative, yet effective minimum mean square error (MMSE) space-time multiuser detector (MUD) with the assistance of soft interference to enhance the performance in the multipath code division multiple access (CDMA) systems. The proposed space-time MUD is of rank one and comprises of a spatial filter and a temporal filter. To offset the performance loss due to such a constraint, the new MUD alternatively updates the spatial filter or the temporal filter with the soft interference cancellation in between so as to refine the received signal. Computer simulations show that the new MUD can drastically enhance the performance compared to previous works with modest computations, especially in highly loaded scenarios.

A promising class of nonlinear multiuser detector is introduced for CDMA systems. These multiuser detectors use optimized multipass algorithms to successively cancel multiple-access interference (MAI) from received data and generate symbol decisions whose reliability increases monotonically with each iteration. They significantly outperform decorrelating detectors and linear minimum mean-square error (MMSE) multiuser detectors, but have the same order of computational complexity. When the ratio of the number of users to the spreading factor is below a certain threshold, iterated-decision multiuser detectors asymptotically achieve the performance of the optimum multiuser detector, ie, maximum-likelihood (ML) decoding.

Smart base station antenna must be established in limited installation spaces in urban cellular environments. To realize this, smart antennas employing a vertical pattern have been studied. In this paper, we first present the characteristics of the angular spread in the vertical plane using an array antenna with elements arranged in the vertical plane in an actual cellular environment. The performance and problems of smart antennas employing the vertical pattern are elucidated by computer simulation considering the measured angular spread. This paper also proposes space division multiple access (SDMA) using smart antennas utilizing vertical pattern and polarization control with terminal polarization assignment, which can discriminate SDMA users while using a limited antenna installation space. Finally, the effectiveness of the proposed SDMA system is confirmed by computer simulation using the measured propagation channel data in an actual cellular environment.

Nowadays, Multicarrier Direct sequence code division multiple access (MC DS-CDMA) systems are used in mobile communication. Performance of these systems are limited by multiple access interference (MAI) created by spread-spectrum users in the channel as well as background channel noise. This paper proposes an incremental gradient descent (IGD) multi-user detection (MUD) for MC DS-CDMA system that can achieve near-optimum performance while the number of users is linear in its implementation complexity. The IGD algorithm make an effort to perform optimum MUD by updating one user's bit decision each iteration in the best way. This algorithm accelerates the gradient algorithm convergence by averaging. When a minimum mean square error (MMSE) MUD is employed to initialize the proposed algorithm, in all cases tested the gradient search converges to a solution with optimum performance. Further, the iterative tests denote that the proposed IGD algorithm provides significant performance for cases where other suboptimum algorithms perform poorly. Simulation compares the proposed IGD algorithm with the conventional detectors.

In code division multiple access (CDMA) systems transmitting over time-varying multipath channels, both intersymbol interference (ISI) and multiple access interference (MAI) arise. The conventional suboptimum receiver consisting of a bank of matched filters is often inefficient because interference is treated as noise. The optimum multi-user detector is too complex to be implemented at present. Four suboptimum detection techniques based on zero forcing (ZF) and minimum mean square error (MMSE) equalization with and without decision feedback (DF) are presented and compared. They combat both ISI and MAI. The computational complexity of all four equalizers is essentially the same and they are independent of the size of the data symbol alphabet. It is shown that all four equalizers considerably outperform the conventional receiver. The MMSE equalizers are superior to the corresponding ZF equalizers. Furthermore, the equalizers with DF perform better than the corresponding equalizers without DF. An algorithm termed channel sorting is introduced to reduce the impairing effect of error propagation on the equalizers with DF. >

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.