Iterative decoding for MIMO channels via modified sphere decoding

In recent years, soft iterative decoding techniques have been shown to greatly improve the bit error rate performance of various communication systems. For multiantenna systems employing space-time codes, however, it is not clear what is the best way to obtain the soft information required of the iterative scheme with low complexity. In this paper, we propose a modification of the Fincke-Pohst (sphere decoding) algorithm to estimate the maximum a posteriori probability of the received symbol sequence. The new algorithm solves a nonlinear integer least squares problem and, over a wide range of rates and signal-to-noise ratios, has polynomial-time complexity. Performance of the algorithm, combined with convolutional, turbo, and low-density parity check codes, is demonstrated on several multiantenna channels. The results for systems that employ space-time modulation schemes seem to indicate that the best performing schemes are those that support the highest mutual information between the transmitted and received signals, rather than the best diversity gain

Design and Performance Analysis for LDPC Coded Modulation in Multiuser MIMO Systems

The channel capacity can be greatly increased by using multiple transmit and receive antennas, which is usually called multi-input multi-output (MIMO) systems. Iterative processing has achieved near-capacity on a single-antenna Gaussian or Rayleigh fading channel. How to use the iterative technique to exploit the capacity potential in single-user and/or multiuser MIMO systems is of great interest. We propose a low-density parity-check (LDPC) coded modulation scheme in multiuser MIMO systems. The receiver can be regarded as a serially concatenated iterative detection and decoding scheme, where the LDPC decoder performs the role of outer decoder and the multiuser demapper does that of the inner decoder. For the proposed scheme, appropriate selection of a bit-to-symbol mapping is crucial to achieve a good performance, so we investigate and find the best mapping under various cases.Analytical bound serves as a useful tool to assess system performance. The search for powerful codes has motivated the introduction of efficient bounding techniques tailored to some ensembles of codes. We then investigate combinatorial union bounding techniques for fast fading multiuser MIMO systems. The union upper bound on maximum likelihood (ML) decoding error probability provides a prediction for the system performance, with which the simulated system performance can be compared. Closed-form expression for the union bound is obtained, which can be evaluated efficiently by using a polynomial expansion. In addition, the constrained channel capacity and the threshold obtained from extrinsic information transfer (EXIT) chart can also serve as performance measures. Based on the analysis for fast fading case, we generalize the union upper bound to the block fading case