Iterative Decoding and Soft Interference Cancellation for the Gaussian Multiple Access Channel

The presence of home LAN constitutes a major impairment to reliable transmission in the VDSL environment. A low complex iterative soft interference cancellation and decoding technique to mitigate the effect of home-LAN on VDSL is presented. To perform soft interference cancellation, VDSL and home-LAN signals are jointly detected using a soft in soft out multiuser receiver which consists of a soft interference canceler and demodulator combined with a set of turbo decoders. The soft interference canceller uses the a priori probabilities to perform interference cancellation. The turbo decoder produces the a posteriori probabilities which are fed back to the soft interference canceller and demodulator as a priori probabilities.

An iterative QR-based soft feedback segment interference cancellation (QRSFSIC) detection and decoder algorithm for a Reed–Muller (RM) space-time turbo system is proposed in this paper. It forms the sufficient statistic for the minimum-mean-square error (MMSE) estimate according to QR decomposition-based soft feedback successive interference cancellation, stemmed from the a priori log-likelihood ratio (LLR) of encoded bits. Then, the signal originating from the symbols of the reliable segment, the symbol reliability metric, in terms of an a posteriori LLR of encoded bits which is larger than a certain threshold, is iteratively cancelled with the QRSFSIC in order to further obtain the residual signal for evaluating the symbols in the unreliable segment. This is done until the unreliable segment is empty, resulting in the extrinsic information for a RM turbo-coded bit with the greatest likelihood. Bridged by de-multiplexing and multiplexing, an iterative QRSFSIC detection is concatenated with an iterative trellis-based maximum a posteriori probability RM turbo decoder as if a principal Turbo detection and decoder is embedded with an iterative subordinate QRSFSIC detection and a RM turbo decoder, exchanging each other’s detection and decoding soft-decision information iteratively. These three stages let the proposed algorithm approach the upper bound of the diversity. The simulation results also show that the proposed scheme outperforms the other suboptimum detectors considered in this paper.

This paper deals with a novel design approach for a converging iterative receiver for coded CDMA that estimates both the channel coefficients and the transmitted symbols. The receiver design is based on the variational Bayesian space-alternating generalized expectation-maximization (VB-SAGE) method. Conceptually, the probability distribution of each user's code sequence and the probability distribution of all channel coefficients are updated in an iterative fashion. The obtained receiver, which we refer to as VB-SAGE receiver, performs iterative channel estimation, interference cancellation and single-user decoding. Even though the design is based on code sequence probabilities, only the soft decisions (mean values) and the variances of the code symbols are required for channel estimation and interference cancellation; moreover, the variances are functions of the soft decisions. These soft decisions are computed by the single-user decoders based on the outputs of the interference cancellation device. The iterative process of the VB-SAGE receiver is guaranteed to converge in the free energy. The VB-SAGE method proposed in this paper may also be used for other applications.

Iterative or Turbo decoding of parallel concatenated binary error control codes in Binary Phase Shift Keyed (BPSK) Communication System corrupted by both Additive White Gaussian Noise (AWGN) and oscillator phase noise is discussed. As an example of application of the discussed theory, iterative decoding technique of Parallel Concatenated block Codes (PCBC) is applied to a coherent Optical Code Division Multiple Access (OCDMA) network in the presence of Multiple Access Interference (MAI), detector shot noise and laser phase noise. Remarkable improvement in performance resulting from the use of turbo decoding in the OCDMA network is also discussed.

Based on the minimum mean square error (MMSE) detection with iterative soft interference cancellation (SoIC), we propose an adaptive MMSE (A-MMSE) algorithm which acts as an MMSE operator at the beginning of iteration and a maximum ratio combination (MRC) when the interference is nearly cancelled. In our algorithm, a modified metric matrix based on the reliability of soft information from the decoder output is multiplied by the interference part of channel correlation matrix to update the detection operator. The simulation results have shown that this A-MMSE iterative SoIC algorithm can achieve significant performance advantage over the traditional MMSE iterative SoIC algorithm.

For interference alignment (IA) with no channel extension, determining the existence of IA solution for general system parameters is still an open problem. This same problem also exists in interference alignment and cancellation (IAC), which combines IA with interference cancellation in the receivers, involving a new receiver architecture associated with signaling over backhaul links among them. As IAC is expected to achieve more degrees of freedom (DoF) than IA, the existence of IAC solution would be another interesting, yet challenging issue to investigate. In this paper, we have proposed a specific alignment scheme, which allows for the derivation of closed-form IAC solution. Furthermore, we establish and prove the general necessary and sufficient condition to determine the existence of closed-form IAC solution for a Gaussian interference multiple access channel (MAC) with K receivers and J users, each with M antennas.

In this paper, a second stage for algorithms applying iterative soft decision interference cancellation (ISDIC) for channel equalization is proposed, which performs error search and correction. Analysis by simulations shows that matched filter (MF)-based ISDIC (MF ISDIC) with subsequent second stage can outperform more complex minimum-mean-square-error (MMSE) based ISDIC. Furthermore, the latter can be improved by the proposed second stage by up to 2 dB. It is shown that the ISDIC schemes with subsequent second stage can reach the MF bound up to a fraction of a decibel for all analyzed channels and 4-ary quadrature amplitude modulation (QAM) transmission, and up to 1 dB for 16-ary QAM transmission. In the work of Gerstacker , it has been reported that MF ISDIC performs very well for highly dispersive channels, e.g., with 60 symbol-spaced taps, but for channels of moderate dispersion, an error floor occurs. By utilizing performance bounds for delayed decision-feedback sequence estimation (DDFSE), we show that now for channels of moderate length, e.g., 20 symbol-spaced taps, even low-complexity MF ISDIC with the proposed subsequent second stage outperforms a DDFSE approach with states.

In this paper, we propose a low-complexity pseudo-de-quantization based (PDQ-based) iterative receiver in massive multi-user multi-input multi-output (MU-MIMO) systems with low resolution analog-to-digital converters (ADCs). First, a unified framework of massive MU-MIMO system with low resolution ADCs is presented. Then, a low-complexity iterative algorithm applying iterative soft decision interference cancellation (ISDIC) is introduced, where a soft information updating scheme is proposed for the PQD-based optimal detection and an iterative architecture of PDQ-based receiver is given. After that, the effect of quantization step size on the performance of PDQ-based iterative receiver is discussed and a new method is proposed to optimize the quantization step with given resolution ADCs. Finally, simulation results show that the PDQ-based iterative receiver can achieve significant improvement with iterative processing and provide a noticeable performance gain over the MMSE-ISDIC receiver with low resolution ADCs.

In this paper, we introduce the optimization of bit error rate (BER) in parallel cancellation of multiple access interference (PIC) using the bias compensation with a direct sequence unipolar optical code division multiple access (DS-OCDMA) system. This receiver is dedicated to mitigate Multi access Interference (MAI). The principle of our proposed receiver consists in reducing the output error by amplification of the interfering signals. We develop the PIC compensated theoretical error probability expression. The performance of such a technique is analyzed in a synchronous network using orthogonal optical codes (OOCs) and the results are compared with those for different receivers.

This paper studies the performance of iterative multiuser decoding, interference cancellation, and channel estimation techniques applicable to third generation WCDMA systems. The concept uses a posteriori probabilities of code symbols to enhance detection, decoding and channel estimation in an iterative fashion. The performance is analyzed in a multipath channel with simulations. It is seen that the proposed concept combats multiuser interference effectively and performs almost as well as single user systems.

Carrier frequency offset (CFO) is a major factor that degrades performance of the orthogonal frequency division multiplexing (OFDM) system. For orthogonal frequency division multiple access (OFDMA) uplink systems, there are multiple CFOs need to be estimated simultaneously, which is a very challenging task. Particle swarm optimization (PSO) algorithm has been recognized a potential approach for CFOs estimation. However, its performance deteriorates as the number of users increases due to insufficient particles diversity. To overcome this difficulty, an enhanced PSO called MRPSO is proposed to increase particles diversity by employing mutation and repulsive operations. Furthermore, a least square (LS) scheme is adopted to improve the estimated CFOs. Simulation results indicate that the proposed MRPSO attains best BER and MSE performances in CFOs estimation as compared to other PSO-based schemes.

In this paper, new schemes have been proposed for the estimation of the additive white Gaussian noise (AWGN) channel with intersymbol interference (ISI) in an iterative equalization and decoding system using low-density parity check (LDPC) codes. This article explores the use of the least squares algorithm in various scenarios. For example, the impulse response of the AWGN channel h was initially estimated using a training sequence. Subsequently, the impulse response was calculated based on the training sequence and then re-estimated once using the sequence estimated from the output of the LDPC decoder. Lastly, the impulse response was calculated based on the training sequence and re-estimated twice using the sequence estimated from the output of the LDPC decoder. Comparisons were made between the performances of the three mentioned situations, with the situation in which a perfect estimate of the impulse response of the channel is assumed. The performance analysis focused on how the bit error rate changes in relation to the signal-to-noise ratio. The BER performance comes close to the scenario of having a perfect estimate of the impulse response when the estimation is performed based on the training sequence and then re-estimated twice from the sequence obtained from the output of the LDPC decoder.

We propose a layered space time (LST) transceiver in a multiuser code division multiple access (CDMA) mobile communication system. In particular, we examine a multiuser iterative receiver with joint detection, channel estimation and decoding in a frequency selective fading channel. The iterative parallel interference canceller (PIC) with statistics combining is used as the multiuser detection scheme and a least mean square (LMS) adaptive algorithm is applied to estimate the multiple input and multiple output (MIMO) frequency selective fading channel. Simulation results are presented to demonstrate the performance of this receiver. It is shown that the performance of the receiver with iterative channel estimation is close to that of the receiver with perfect channel state information (CSI).

Orthogonal frequency-division multiplexing (OFDM) is robust against frequency selective fading because of the increase of the symbol duration. However, the time-varying nature of the channel causes inter-carrier interference (ICI) which destroys the orthogonal of sub-carriers and degrades the system performance severely. To alleviate the detrimental effect of ICI, there is a need for ICI mitigation within one OFDM symbol. We propose an iterative Inter-Carrier Interference (ICI) estimation and cancellation technique for OFDM systems based on regularized constrained total least squares. In the proposed scheme, ICI aren’t treated as additional additive white Gaussian noise (AWGN). The effect of Inter-Carrier Interference (ICI) and inter-symbol interference (ISI) on channel estimation is regarded as perturbation of channel. We propose a novel algorithm for channel estimation o based on regularized constrained total least squares. Computer simulations show that significant improvement can be obtained by the proposed scheme in fast fading channels.

This paper presents a low-complexity linear minimum mean-squared-error-based iterative soft interference cancellation (LMMSE-ISIC) scheme for multiple-input multiple-output (MIMO) systems. To avoid direct matrix inversion in the conventional LMMSE-ISIC scheme, expressions are derived to obtain the filtering vector and estimate of the conventional scheme; the direct inverse operation is then replaced by the vector-based operations in the proposed scheme. Thus, for the worst-case scenario in the proposed scheme, the complexity of estimating each transmit symbol is approximately proportional to the square of the number of receive antennas; in the conventional scheme, it is approximately proportional to the cube of the number of receive antennas. In addition, because there are no approximations for deriving the filtering vector and estimate, the proposed LMMSE-ISIC scheme achieves near-optimum performance identical to that of the conventional scheme, which is close to the matched filter bound of the channel. Further, the extension of the proposed scheme for iterative detection and decoding is developed for coded systems. The simulated results confirm that the conventional and proposed schemes outperform the approximated matrix inversion based schemes and achieve the identical error performance in both uncoded and coded systems, while the complexity order of the proposed scheme is similar to or even lower than those of the approximation schemes. Therefore, the proposed scheme can be considered an effective near-optimum LMMSE-based iterative detection approach for MIMO systems, especially for massive MIMO systems with a high load factor.