Iterative Detection And Decoding Receiver Research Articles

Low-Routing-Complexity Convolutional/Turbo Decoder Design for Iterative Detection and Decoding Receivers

A highly hardware-shared convolutional/turbo decoder for iterative detection and decoding (IDD) receivers is presented here. Furthermore, parallel dual-mode decoding kernels are proposed to alternatively decode the long-term evolution (LTE)-compatible convolutional codes (CCs) and turbo codes (TCs) using a parity-enhanced soft-input soft-output maximum a-posteriori algorithm. However, decoding the high-constraint-length CC results in complicated interconnections among the parallel decoding kernels and unroutable back-end chip implementation. Therefore, a minimized global route (MGR) design is proposed for the dual-mode decoder to further simplify the global data transfers and reduce the routing complexity. Using a 40-nm CMOS process, the proposed dual-mode decoder achieves a 48% area reduction compared with the individual single-mode TC and single-mode CC decoders. The global routing length of the proposed decoding kernels is reduced by 32% using the MGR design. Because of the feasible placements and routing, the proposed dual-mode decoder is implemented in an application-specific integrated circuit of 2.88-mm2 core area at the maximum operating frequency of 364 MHz. For the LTE-based IDD receiver, the proposed dual-mode decoder achieves high area efficiencies of 0.21 and 0.35 bits/mm2 for the TC and CC decoding, respectively.

Knowledge‐aided iterative detection and decoding for multiuser multiple‐antenna systems

In this work, the authors assess the performance and latency of a receiver design for multiuser multiple-antenna systems using low-density parity-check (LDPC) codes with iterative detection and decoding (IDD). The proposed knowledge-aided IDD (KA-IDD) receiver employs a parallel interference cancellation detector with refined iterative processing and a reweighted belief propagation (BP) decoder. Additionally, two BP-based decoding algorithms are proposed for improved performance of the decoder. The first cycle knowledge-aided reweighted-BP decoder takes advantage of the information about the distribution of cycles in the Tanner graph and the second expansion knowledge-aided reweighted-BP decoder expands the original graph into a set of subgraphs, then locally optimises the reweighting parameters of each subgraph. Novel reweighting parameter optimisation strategies are developed for decoding regular or irregular LDPC codes. The developed schemes optimise the parameters off-line and neither of these proposed algorithms imposes extra computational complexity to the on-line decoding procedure. Furthermore, the proposed schemes reduce the decoding latency. Simulation results show that the proposed KA-IDD scheme and algorithms outperform prior art and require a reduced number of decoding iterations.

EM‐based poor slot update method for MIMO IDD receiver in fast time‐varying channels

In this study, the authors propose an expectation-maximisation (EM)-based poor slot update method for multiple-input multiple-output (MIMO) iterative detection and decoding (IDD) receivers to increase their channel tracking capability in fast time-varying channels. The poor slots that trigger error propagation in a frame are selected, the channel state information is updated, and the updated recursive least squares channel tracking algorithm is executed. The accurate channel tracking capability of this new channel updating technique contributes to a 3 dB improvement in the bit error rate performance of an IDD receiver in a fast mobile environment ( > 180 km / h ). The authors also demonstrate that an ∼ 20 − 25 % complexity reduction can be achieved under various conditions.

Tight Upper Bound Performance of Full-Duplex MIMO-BICM-IDD Systems in the Presence of Residual Self-Interference

In this paper, we derive a tight upper bound on the performance of a coded full-duplex multiple-input multiple-output (MIMO)-based bidirectional transceiver. Iterative detection and decoding (IDD) are proposed to suppress the residual self-interference (SI) remaining after applying different stages of SI cancellation. IDD comprises an adaptive minimum mean-squared error filter with log-likelihood ratio demapping, while the soft decoder by using soft-in soft-out decoding utilizes the maximum a posteriori algorithm. Furthermore, bit-interleaved coded modulation is considered in the presence of additive white Gaussian noise over MIMO frequency non-selective Rayleigh fading channels. Simulation results are presented to demonstrate the bit-error rate (BER) performance as a function of the signal-to-noise ratio showing a close match to the SI-free case for the proposed system. Furthermore, we validate our results by deriving a tight upper bound on the performance of the proposed system using rate-1/2 convolutional codes together with $M$ -ary quadrature amplitude modulation, which asymptotically exhibits a close agreement with the simulated BER performance. Moreover, extrinsic information transfer chart analysis is used to investigate the convergence behavior of the proposed IDD receiver and to determine the number of iterations required for this convergence.

Iterative Detection and Decoding Algorithms for MIMO Systems in Block-Fading Channels Using LDPC Codes

We propose iterative detection and decoding (IDD) algorithms with low-density parity-check (LDPC) codes for multiple-input multiple-output (MIMO) systems operating in block-fading and fast Rayleigh fading channels. Soft-input-soft-output minimum-mean-square-error (MMSE) receivers with successive interference cancellation are considered. In particular, we devise a novel strategy to improve the bit error rate (BER) performance of IDD schemes, which takes into account the soft a posteriori output of the decoder in a block-fading channel when root-check LDPC codes are used. A MIMO IDD receiver with soft information processing that exploits the code structure and the behavior of the log-likelihood ratios is also developed. Moreover, we present a scheduling algorithm for decoding LDPC codes in block-fading channels. Simulations show that the proposed techniques result in significant gains in terms of BER for both block-fading and fast-fading channels.

A low‐complexity iterative MIMO detection and decoding scheme using dimension reduction

AbstractSpatial multiplexing multiple‐input multiple‐output is considered as a core advanced communication technology to increase data rate. Although it guarantees higher capacity, it gives huge burden on the receiver side especially when iterative detection and decoding (IDD) is employed. Therefore, the IDD receiver needs to be efficiently implemented considering the complexity as well as performance in practice. In this paper, we propose an IDD scheme employing dimension reduction soft demodulation (DRSD) principle based on maximum a posteriori criterion necessary for IDD operation. With separation into hard and soft streams in the DRSD, the proposed scheme employs all ordering successive interference cancellation with a simple modified slicing for hard detection to consider the effect of a priori information conveyed from past iteration, enabling complexity reduction. It can provide better trade‐off between complexity and performance. Copyright © 2014 John Wiley & Sons, Ltd.

From Nominal to True A Posteriori Probabilities: An Exact Bayesian Theorem Based Probabilistic Data Association Approach for Iterative MIMO Detection and Decoding

It was conventionally regarded that the approximate Bayesian theorem based existing probabilistic data association (PDA) algorithms output the estimated symbol-wise a posteriori probabilities (APPs) as soft information. In our recent work, however, we demonstrated that these probabilities are not the true APPs in the rigorous mathematical sense, but a type of nominal APPs, which are unsuitable for the classic architecture of iterative detection and decoding (IDD) aided receivers. To circumvent this predicament, in this paper we propose an exact Bayesian theorem based logarithmic domain PDA (EB-Log-PDA) method, whose output has similar characteristics to the true APPs, and hence it is readily applicable to the classic IDD architecture of multiple-input-multiple-output (MIMO) systems using the general M-ary modulation. Furthermore, we investigate the impact of the EB-Log-PDA algorithm's inner iteration on the design of EB-Log-PDA aided IDD receiver. We demonstrate that introducing inner iterations into EB-Log-PDA, which is common practice in conventional-PDA aided uncoded MIMO systems, would actually degrade the IDD receiver's performance, despite significantly increasing the overall computational complexity of the IDD receiver. Finally, we investigate the relationship between the extrinsic log-likelihood ratios (LLRs) of the proposed EB-Log-PDA and of the approximate Bayesian theorem based logarithmic domain PDA (AB-Log-PDA) reported in our previous work. Despite their difference in extrinsic LLRs, we also show that the IDD schemes employing the EB-Log-PDA and the AB-Log-PDA without incorporating any inner PDA iterations have a similar achievable performance close to that of the optimal maximum a posteriori (MAP) detector based IDD receiver, while imposing a significantly lower computational complexity in the scenarios considered.

Lattice Reduction-Based MIMO Iterative Receiver Using Randomized Sampling

For iterative detection and decoding (IDD) in multiple-input multiple-output (MIMO) systems, although the maximum a posteriori probability (MAP) detector is desirable in terms of performance, it is difficult to be employed due to its prohibitively high complexity as an exhaustive search is used. In this paper, a lattice reduction (LR)-based MIMO detection method is studied to achieve near MAP performance with reasonably low complexity for IDD. The a priori information (API), which is available from a soft-input soft-output (SISO) decoder, is taken into account to generate a list with a randomized successive interference cancellation (SIC) method. More specifically, a joint Gaussian distribution is used to convert the API into the LR domain and a modified sampling distribution, which was originally adopted for near optimal LR-based detection in non-IDD MIMO systems, is derived for random sampling to build a list of candidate vectors of high a posteriori probability (APP) with low complexity. It is shown that the IDD receiver with the proposed method outperforms those with the conventional LR-based methods, where no API is taken into account to build a list. Furthermore, the trade-off between performance and complexity is exploited with varying list length.

Approximate Bayesian Probabilistic-Data-Association-Aided Iterative Detection for MIMO Systems Using Arbitrary $M$-ary Modulation

In this paper, the issue of designing an iterative-detection-and-decoding (IDD)-aided receiver, relying on the low-complexity probabilistic data association (PDA) method, is addressed for turbo-coded multiple-input-multiple-output (MIMO) systems using general <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -ary modulations. We demonstrate that the classic candidate-search-aided bit-based extrinsic log-likelihood ratio (LLR) calculation method is not applicable to the family of PDA-based detectors. Additionally, we reveal that, in contrast to the interpretation in the existing literature, the output symbol probabilities of existing PDA algorithms are not the true a posteriori probabilities (APPs) but, rather, the normalized symbol likelihoods. Therefore, the classic relationship, where the extrinsic LLRs are given by subtracting the a priori LLRs from the a posteriori LLRs, does not hold for the existing PDA-based detectors. Motivated by these revelations, we conceive a new approximate Bayesian-theorem-based logarithmic-domain PDA (AB-Log-PDA) method and unveil the technique of calculating bit-based extrinsic LLRs for the AB-Log-PDA, which facilitates the employment of the AB-Log-PDA in a simplified IDD receiver structure. Additionally, we demonstrate that we may dispense with inner iterations within the AB-Log-PDA in the context of IDD receivers. Our complexity analysis and numerical results recorded for Nakagami- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading channels demonstrate that the proposed AB-Log-PDA-based IDD scheme is capable of achieving a performance comparable with that of the optimal maximum a posteriori (MAP)-detector-based IDD receiver, while imposing significantly lower computational complexity in the scenarios considered.