An Efficient Near-ML Algorithm with SQRD for Wireless MIMO Communications in Metro Transportation Systems

2013

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This paper proposes a robust transceiver design against the effect of channel state information (CSI) estimation error to optimize precoded uplink (UL) multi-user multipleinput multiple-output (MU-MIMO) transmission in limited feedback system under the consideration of the least-square technique on CSI estimation. To improve this limited feedback precoding, the constrained minimum variance (MV) approach with quadratic form to realize the computationally-efficient optimization problem, advantageously invoking the characteristics of the CSI estimation error, is proposed to suppress the effect of CSI estimation error, multiple user interference and noise. According to the Lagrange multiplier method on this MV approach, the deterministic function to resist uncertain CSI can be obtained to optimize design of the precoder and adaptive matrices jointly. With these optimum adaptive and precoder matrices, an optimum robust weighting matrix can be obtained to facilitate the user-wise detection in precoded UL MU-MIMO system. Performance analysis shows that the proposed robust weighting matrix is an unbiased design and it also can regularize the diagonal loading factor technique, and the detection performance of the proposed robust transceiver design can be predicted simplistically by applying our derived signal-to-interference-plusnoise ratio formulation. Computer simulations are conducted to confirm the efficacy of the proposed design in both perfect and imperfect CSI estimation.

Section: Simulation Resultsmentioning

confidence: 99%

Design of Robust Transceiver for Precoded Uplink MU-MIMO Transmission in Limited Feedback System

2013

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“…Based on this structure, the tree search technique is adopted to avoid the exhaustive QRDs in (9) and (13) in finding the precoder. The precoders of the M th q codebook converted into a binary search tree exploited by the constellation point, using a separation of real and imaginary, are firstly developed in Table 1.…”

Section: Efficient Precoder Selection Via Tree Search Algorithmmentioning

confidence: 99%

“…Particularly, absolute value and subtraction in (14) to cluster few candidate precoders have less computational complexity than the QRD in (13). Thus, the tree search reduces the complexity of…”

Section: Efficient Precoder Selection Via Tree Search Algorithmmentioning

confidence: 99%

Efficient QR-Based Multi-Mode Precoding for Limited Feedback Multi-User MIMO Systems

Lee

2013

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This paper proposes QR-based criteria for efficient selection of multi-mode precoders in multi-user multiple-input multiple-output (MU-MIMO) precoded systems with a limited feedback. In particular, a MU-MIMO QR based precoding scheme is developed which takes advantage of the overall precoder design among users in conjunction with QR detection. A selection criterion is developed to identify the precoder that yields the maximum free distance. Efficient mode selection and tree search strategies are adopted to reduce the complexity associated with the identification of the optimum precoder. To further improve the detection performance in correlated channels, an efficient QR-based MMSE V-BLAST detector is proposed. Computer simulations confirm that the proposed QR-based precoding scheme attains the performance of existing schemes with a significantly lower complexity level.

“…More specifically, the full MIMO channel matrix multiplication [6] leads to complicated very-large-scale integration (VLSI) [11], field-programmable gate array (FPGA) implementation [12] and real-time design [1][2][3]. To simplify the computational complexity, the QR-decomposition (QRD) scheme [13][14][15] with restraining complexity has been devised to reduce the MIMO channel matrix multiplication due to involving a lot of zeros in a triangular matrix [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…In order to achieve a simply way, the MIMO channel matrix can be uniquely represented a triangular matrix (R) and a unitary matrix after QRD [13][14][15], provided that the number of receiving antennas (M) is larger than or equal to the number of transmitting antennas (N). Thus, computational complexity can be simplified by the following ways.…”

Section: Introductionmentioning

confidence: 99%

Complexity Reduction by Using QR-Based Scheme in Computing Capacity for Optimal Transmission

2009

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Multiple-input-multiple-output (MIMO) technique is often employed to increase capacity in comparing to systems with single antenna. However, the computational complexity in evaluating channel capacity or transmission rate (data rate) grows proportionally to the number of employed antennas at both ends of the wireless link. Recently, the QR decomposition (QRD) based detection schemes have emerged as a low-complexity solution. After conducting QRD on a full channel matrix that results in a triangular matrix, we claim that computational complexity can be simplified by the following ways. First, to simplify channel capacity calculation, we prove that eigenvalues of the full channel matrix multiplication equals eigenvalues of the triangular channel matrix multiplication. Second, to simplify the calculation of the optimal transmission rate constrained constellation, we propose a simplistic multiplication of the resulted simple triangular matrix and a transmitted signal vector. Then, we also propose a modified mutual information calculation (MMIC) to achieve a quite low-complexity via the divided calculation. By using computer simulation and fieldprogrammable gate array (FPGA) implementation, simulation results show that the proposed QRD-based schemes are capable of achieving conventional performance, but at a low-complexity level.