Abstract
In this paper, a QR-decomposition-based scheduled belief propagation (BP) detector with interference cancellation (IC) and candidate constraints is proposed for multiple-input multiple-output (MIMO) systems. Based on a bipartite graph generated from an upper triangular channel matrix following linear transformation using QR decomposition, the proposed detector performs a sequential message updating procedure between bit nodes. During this updating procedure, candidate constraints are imposed to restrict the number of possible candidate vectors for the calculation of observation-to-bit messages. In addition, after obtaining the soft message corresponding to the bit sequence in each transmit symbol, a hard-decision IC operation is performed to reduce the size of the bipartite graph and indirectly update the messages for the remaining symbols. Therefore, the proposed scheme provides a huge complexity reduction compared to conventional BP detectors that perform message updating by using all related messages directly. Simulation results confirm that the proposed detector can achieve suboptimum error performance with significantly improved convergence speed and reduced computational complexity compared to conventional BP detectors in MIMO systems.
Highlights
In multiple-input multiple-output (MIMO) systems, signals are simultaneously sent from multiple transmit antennas, and a receiver must estimate and detect the transmitted signals [1,2]
To obtain reasonable average bit-error ratio (BER) and frame-error ratio (FER), numerical simulations were performed until 1000 frame errors were counted for each signal-to-noise ratio (SNR) point, where each frame consists of 576 bits
As an optimal bound for error performance, the maximum likelihood (ML) detector and matched-filter bound (MFB) are considered for uncoded and coded systems, respectively, where the MFB is identical to the performance of the linear MF detector with K = 1 and the same number of receive antennas M [1]
Summary
In multiple-input multiple-output (MIMO) systems, signals are simultaneously sent from multiple transmit antennas, and a receiver must estimate and detect the transmitted signals [1,2]. Among MP approaches, belief propagation (BP) algorithms perform inference on graphical models (e.g., bipartite graphs) [6], and they have been widely applied for channel decoding problems [7,8] and detection problems [9,10,11,12,13,14,15] These BP algorithms can achieve suboptimum performance, and thereby a number of BP detectors have been developed for MIMO systems. Based on large numbers of nodes and edges, a BP detector based on a fully connected bipartite graph for MIMO systems (referred to as the standard BP detector hereafter) incurs huge computational complexity that can even exceed that of ML detection [10]. To obtain additional reductions in computational complexity while accelerating convergence speed and minimizing performance loss, this paper proposes a scheduled QR-BP detector with interference cancellation (IC) and candidate constraints (referred to as the QR-SBP detector hereafter) for MIMO systems.
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