Guosen Yue

Performance analysis and design optimization of LDPC-coded MIMO OFDM systems

We consider the performance analysis and design optimization of low-density parity check (LDPC) coded multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems for high data rate wireless transmission. The tools of density evolution with mixture Gaussian approximations are used to optimize irregular LDPC codes and to compute minimum operational signal-to-noise ratios (SNRs) for ergodic MIMO OFDM channels. In particular, the optimization is done for various MIMO OFDM system configurations, which include a different number of antennas, different channel models, and different demodulation schemes; the optimized performance is compared with the corresponding channel capacity. It is shown that along with the optimized irregular LDPC codes, a turbo iterative receiver that consists of a soft maximum a posteriori (MAP) demodulator and a belief-propagation LDPC decoder can perform within 1 dB from the ergodic capacity of the MIMO OFDM systems under consideration. It is also shown that compared with the optimal MAP demodulator-based receivers, the receivers employing a low-complexity linear minimum mean-square-error soft-interference-cancellation (LMMSE-SIC) demodulator have a small performance loss (< 1dB) in spatially uncorrelated MIMO channels but suffer extra performance loss in MIMO channels with spatial correlation. Finally, from the LDPC profiles that already are optimized for ergodic channels, we heuristically construct small block-size irregular LDPC codes for outage MIMO OFDM channels; as shown from simulation results, the irregular LDPC codes constructed here are helpful in expediting the convergence of the iterative receivers.

LDPC Code Design for Half-Duplex Cooperative Relay

The authors consider the design of LDPC codes for cooperative relay systems in the half-duplex mode. The capacity of halfduplex relay channels has been studied previously but the design of good channel codes for such channels remains a challenging problem. Employing an efficient relay protocol, we transform the half-duplex relay code design problem into a problem of ratecompatible LDPC code design where different code segments experience different SNRs. The density evolution with conventional Gaussian approximation for single user channels, which assumes invariant SNR within one codeword, is not capable of accurately predicting the code performance for this system. Here we develop a density evolution with a modified Gaussian approximation that takes into account the SNR variation in one received codeword as well as the rate-compatibility constraint. We then optimize the code ensemble using a modified differential evolution procedure. Extensive simulations are carried out to demonstrate that the proposed algorithm offers more accurate prediction of code performance in half-duplex relay channels than the conventional methods, and the optimized codes achieve a significant gain over existing codes.

LDPC-coded cooperative relay systems: performance analysis and code design

We treat the problem of designing low-density parity-check (LDPC) codes to approach the capacity of relay channels. We consider an efficient analysis framework that decouples the factor graph (FG) of a B-block transmission into successive partial FGs, each of which denotes a two-block transmission. We develop design methods to find the optimum code ensemble for the partial FG. In particular, we formulate the relay operations and the destination operations as equivalent virtual MISO and MIMO systems, and employ a binary symmetric channel (BSC) model for the relay node output. For AWGN channels, we further develop a Gaussian approximation for the detector output at the destination node. Jointly treating the relay and the destination, we analyze the performance of the LDPC-coded relay system using the extrinsic mutual information transfer(EXIT) chart technique. Furthermore, differential evolution is employed to search for the optimum code ensemble. Our results show that the optimized codes always outperform the regular LDPC codes with a significant gain; in the AWGN case, when Protocol-II is employed and the relay is close to the source, the optimized code performs within 0.1dB to the capacity bound.

Design of Rate-Compatible Irregular Repeat Accumulate Codes

We consider the design of efficient rate-compatible (RC) irregular repeat accumulate (IRA) codes over a wide code rate range. The goal is to provide a family of RC codes to achieve high throughput in hybrid automatic repeat request (ARQ) scheme for high-speed data packet wireless systems. As a subclass of low-density parity-check codes, IRA codes have an extremely simple encoder and a low-complexity decoder while providing capacity approaching performance. We focus on a hybrid design method which employs both puncturing and extending. We propose a simple puncturing method based on minimizing the maximal recoverable step of the punctured nodes. We also propose a new extending scheme for IRA codes by introducing the degree-1 parity bits for the lower rate codes and obtaining the optimal proportions of extended nodes through density evolution analysis. The throughput performance of the designed RC-IRA codes in hybrid ARQ is evaluated for both AWGN and block fading channels. Simulation results demonstrate that our designed RC codes offer good error correction performance over a wide rate range and provide high throughput, especially in the high and low signal-to-noise ratio regions.

User Grouping for Massive MIMO in FDD Systems: New Design Methods and Analysis

The massive multiple-input multiple-output (MIMO) system has drawn increasing attention recently as it is expected to boost the system throughput and result in lower costs. Previous studies mainly focus on time division duplexing (TDD) systems, which are more amenable to practical implementations due to channel reciprocity. However, there are many frequency division duplexing (FDD) systems deployed worldwide. Consequently, it is of great importance to investigate the design and performance of FDD massive MIMO systems. To reduce the overhead of channel estimation in FDD systems, a two-stage precoding scheme was recently proposed to decompose the precoding procedure into intergroup precoding and intragroup precoding. The problem of user grouping and scheduling thus arises. In this paper, we first propose three novel similarity measures for user grouping based on weighted likelihood, subspace projection, and Fubini-Study, respectively, as well as two novel clustering methods, including hierarchical and K-medoids clustering. We then propose a dynamic user scheduling scheme to further enhance the system throughput once the user groups are formed. The load balancing problem is considered when few users are active and solved with an effective algorithm. The efficacy of the proposed schemes are validated with theoretical analysis and simulations.

Performance analysis and design optimization of LDPC coded MIMO OFDM systems

We consider the performance analysis and design optimization of low-density parity check (LDPC) coded multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems for high data rate wireless transmission. The tools of density evolution with mixture Gaussian approximations are used to optimize irregular LDPC codes and to compute minimum operational signal-to-noise ratios (SNRs) for ergodic MIMO OFDM channels. In particular, the optimization is done for various MIMO OFDM system configurations, which include a different number of antennas, different channel models, and different demodulation schemes; the optimized performance is compared with the corresponding channel capacity. It is shown that along with the optimized irregular LDPC codes, a turbo iterative receiver that consists of a soft maximum a posteriori (MAP) demodulator and a belief-propagation LDPC decoder can perform within 1 dB from the ergodic capacity of the MIMO OFDM systems under consideration. It is also shown that compared with the optimal MAP demodulator-based receivers, the receivers employing a low-complexity linear minimum mean-square-error soft-interference-cancellation (LMMSE-SIC) demodulator have a small performance loss (< 1dB) in spatially uncorrelated MIMO channels but suffer extra performance loss in MIMO channels with spatial correlation. Finally, from the LDPC profiles that already are optimized for ergodic channels, we heuristically construct small block-size irregular LDPC codes for outage MIMO OFDM channels; as shown from simulation results, the irregular LDPC codes constructed here are helpful in expediting the convergence of the iterative receivers.The performance analysis and design optimization of low density parity check (LDPC) coded multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems for high speed wireless transmission is considered. The tool of density evolution with mixture Gaussian approximations is used to optimize irregular LDPC codes and to compute minimum operational signal-to-noise ratios for ergodic MIMO OFDM channels. In particular, the optimization is done for various MIMO OFDM system configurations which include different number of antennas, different channel models and different demodulation schemes; and the optimized performance is compared to the corresponding channel capacity.

Optimization of irregular repeat accumulate codes for MIMO systems with iterative receivers

This paper takes into account the design optimization of the random-like ensemble of irregular repeat accumulate (IRA) codes for multiple-input multiple-output (MIMO) communication systems employing iterative receivers. First, the density evolution-based procedure for optimizing the IRA code ensemble is presented. An approximation method based on linear programming is adopted to design an IRA code with the extrinsic information transfer (EXIT) chart matched to that of the soft MIMO demodulator. The authors then reveal the relationship between the IRA codes and the low-density parity-check (LDPC) codes. With a code ensemble mapping relationship between an IRA code and an LDPC code, a quasi-optimal IRA code can be obtained by transforming an optimal LDPC code designed for MIMO systems. Two types of soft MIMO detectors are treated, namely, the maximum a posteriori (MAP) detector and the soft interference canceller with linear MMSE filtering (SIC-MMSE). The results show that with the MAP receiver the designed IRA codes can perform within 1 dB from the ergodic capacities of the MIMO systems under consideration. The authors also treat the short-length IRA code design for block fading MIMO channels. They adopt design techniques for short-length LDPC codes to improve the performance of the short-length IRA code and to reduce the error floor.

MIMO Transmission with Rank Adaptation for Multi-Gigabit 60GHz Wireless

In this paper, we propose a practical and systematic approach to implement the MIMO transmission with rank adaptation for 60 GHz systems. In the 60 GHz system with multiple antennas, the transmit and receive (Tx-Rx) antenna arrays are grouped into a number of subarrays with a predetermined subarray separation based on the derived geometrical criteria of creating high rank MIMO in LoS environments. We first apply an enhanced blind beamforming technique based on a stochastic gradient algorithm (SGA) for the inner-subarray antennas, which does not require channel state information (CSI) at either the transmitter or the receiver. Secondly, the composite MIMO channel, as a joint effect of Tx-Rx beamforming and the channel impulse response, can be estimated with much reduced complexity. Finally, the MIMO transmission with rank adaptation is performed by adaptively selecting the better scheme out of the high-rank spatial multiplexing and the rank-1 beamforming whichever gives higher system throughput. Simulation results show that high-rank spatial multiplexing and rank-1 beamforming outperform each other at different geometrical placements and transmit power settings. The proposed MIMO transmission with rank adaptation offers significant performance gain especially at high signal-to-noise ratio (SNR) regions.

Pilot Design for Sparse Channel Estimation in OFDM-Based Cognitive Radio Systems

In this correspondence, sparse channel estimation is first introduced in orthogonal frequency-division multiplexing (OFDM)-based cognitive radio systems. Based on the results of spectrum sensing, the pilot design is studied by minimizing the coherence of the dictionary matrix used for sparse recovery. Then, it is formulated as an optimal column selection problem where a table is generated and the indexes of the selected columns of the table form a pilot pattern. A novel scheme using constrained cross-entropy optimization is proposed to obtain an optimized pilot pattern, where it is modeled as an independent Bernoulli random process. The updating rule for the probability of each active subcarrier selected as a pilot subcarrier is derived. A projection method is proposed so that the number of pilots during the optimization is fixed. Simulation results verify the effectiveness of the proposed scheme and show that it can achieve 11.5% improvement in spectrum efficiency with the same channel estimation performance compared with the least squares (LS) channel estimation.

Generalized Low-Density Parity-Check Codes Based on Hadamard Constraints

In this paper, we consider the design and analysis of generalized low-density parity-check (GLDPC) codes in AWGN channels. The GLDPC codes are specified by a bipartite Tanner graph, as with standard LDPC codes, but with the single parity-check constraints replaced by general coding constraints. In particular, we consider imposing Hadamard code constraints at the check nodes for a low-rate approach, termed LDPC-Hadamard codes. We introduce a low-complexity message-passing based iterative soft-input soft-output (SISO) decoding algorithm, which employs the a posteriori probability (APP) fast Hadamard transform (FHT) for decoding the Hadamard check codes at each decoding iteration. The achievable capacity with the GLDPC codes is then discussed. A modified LDPC-Hadamard code graph is also proposed. We then optimize the LDPC-Hadamard code ensemble using a low-complexity optimization method based on approximating the density evolution by a one-dimensional dynamic system represented by an extrinsic mutual information transfer (EXIT) chart. Simulation results show that the optimized LDPC-Hadamard codes offer better performance in the low-rate region than low-rate turbo-Hadamard codes, but also enjoy a fast convergence rate. A rate-0.003 LDPC-Hadamard code with large block length can achieve a bit-error-rate (BER) performance of 10-5 at -1.44 dB, which is only 0.15 dB away from the ultimate Shannon limit (-1.592 dB) and 0.24 dB better than the best performing low-rate turbo-Hadamard codes