In this paper, we consider decouple-and-forward (DCF) relaying, where the relay encodes and amplifies decoupled data using orthogonal space-time block codes (OSTBCs), to achieve the maximum diversity gain of multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying. Since the channel status of all antennas is generally unknown and time-varying for cooperation in multi-antenna multiple-relay systems, we investigate an opportunistic relaying scheme for DCF relaying to harness distributed antennas and minimize the cooperation overheads by not using the global channel state information (CSI). In addition, for realistic wireless channels which have spatial fading correlation due to closely-spaced antenna configurations and poor scattering environments, we analyze the exact and lower bound on the symbol error probability (SEP) of the opportunistic DCF relaying over spatially correlated MIMO Rayleigh fading channels. Numerical results show that, even in the presence of spatial fading correlation, the proposed opportunistic relaying scheme is efficient and achieves additional performance gain with low overhead.

This paper presents an improved min-sum iterative decoding scheme for regular and irregular LDPC codes. The proposed decoding scheme scales the extrinsic soft information from variable nodes to check. Different scaling factors are applied for iterations and the scaling factors are obtained by a simplified vector optimization method.

This paper presents an interference cancellation and multipath mitigation algorithm for use in Global Positioning System (GPS) with an array antenna. It is shown that interference signals and multipath signals are effectively suppressed using a serial subspace projection method without any knowledge of the incoming directional information. After the subspace projections, a beamformer is used to maximize the SNR of the received signal. The enhancement in the performance is presented in terms of the cross correlation value and beam patterns.

In this paper, the performance of Tree-LDPC code [1] is presented based on the min-sum algorithm with scaling and the asymptotic performance in the water fall region is shown by density evolution. We presents that the Tree-LDPC code show a significant performance gain by scaling with the optimal scaling factor [3] which is obtained by density evolution methods. We also show that the performance of min-sum with scaling is as good as the performance of sum-product while the decoding complexity of min-sum algorithm is much lower than that of sum-product algorithm.

Density evolution has recently been used to analyze the iterative decoding of Low Density Parity Check (LDPC) codes, Turbo codes, and Serially Concatenated Convolutional Codes (SCCC). The density evolution technique makes it possible to explain many characteristics of iterative decoding including convergence of performance and preferred structures for the constituent codes. While the analytic density evolution methods were applied to LDPC codes, the simulation based density evolution methods were used for Turbo codes and SCCC due to analytic difficulties. In this paper, several density evolution ideas in the literature are used to analyze common code structures and it is shown that those ideas yield consistent results. In order to do that, we derive expressions for density evolution of SCCC with a simple 2-state constituent code. The analytic expressions are based on the sum-product and min-sum algorithms, and the thresholds are evaluated for both message passing algorithms. Particularly, for the min-sum algorithm, the density evolution with Gaussian approximation is derived and used to analyze the effect of scaling soft information. The scaling of extrinsic information slows down the convergence of soft information or avoids an overestimation effect of it and results in better performance, and its gain is maximized in particular constituent codes. Similar approaches are made for LDPC code. We show that the scaling gain is noticeable in the LDPC code as well. This scaling gain is analyzed with both density evolution and simulation performance. The expected scaling gain by density evolution matches well with the achievable scaling gain from simulation results. These results can be extended to the irregular LDPC codes based on the degree distribution for the min-sum algorithm. All density evolution algorithms used in this paper are based on the Gaussian approximation for the exchanged messages.

In this letter, we propose an efficient on-the-fly algorithm for maximum-likelihood decoding of Raptor codes used over the binary erasure channel. It is shown that our proposed decoding algorithm can reduce the actual elapsed decoding time by more than two-thirds with respect to an optimized conventional maximum-likelihood decoding.

This paper presents a performance and thresholds for Irregular Tree-LDPC codes. We obtain optimal irregular degree distributions and threshold by the density evolution technique. It is presented that Irregular Tree-LDPC code has performance gain at low SNR.