9 research outputs found
Linear Precoding for MIMO Channels with QAM Constellations and Reduced Complexity
In this paper, the problem of designing a linear precoder for Multiple-Input
Multiple-Output (MIMO) systems in conjunction with Quadrature Amplitude
Modulation (QAM) is addressed. First, a novel and efficient methodology to
evaluate the input-output mutual information for a general Multiple-Input
Multiple-Output (MIMO) system as well as its corresponding gradients is
presented, based on the Gauss-Hermite quadrature rule. Then, the method is
exploited in a block coordinate gradient ascent optimization process to
determine the globally optimal linear precoder with respect to the MIMO
input-output mutual information for QAM systems with relatively moderate MIMO
channel sizes. The proposed methodology is next applied in conjunction with the
complexity-reducing per-group processing (PGP) technique, which is
semi-optimal, to both perfect channel state information at the transmitter
(CSIT) as well as statistical channel state information (SCSI) scenarios, with
high transmitting and receiving antenna size, and for constellation size up to
. We show by numerical results that the precoders developed offer
significantly better performance than the configuration with no precoder, and
the maximum diversity precoder for QAM with constellation sizes , and
and for MIMO channel size
Downlink Precoding for Massive MIMO Systems Exploiting Virtual Channel Model Sparsity
In this paper, the problem of designing a forward link linear precoder for
Massive Multiple-Input Multiple-Output (MIMO) systems in conjunction with
Quadrature Amplitude Modulation (QAM) is addressed. First, we employ a novel
and efficient methodology that allows for a sparse representation of multiple
users and groups in a fashion similar to Joint Spatial Division and
Multiplexing. Then, the method is generalized to include Orthogonal Frequency
Division Multiplexing (OFDM) for frequency selective channels, resulting in
Combined Frequency and Spatial Division and Multiplexing, a configuration that
offers high flexibility in Massive MIMO systems. A challenge in such system
design is to consider finite alphabet inputs, especially with larger
constellation sizes such as . The proposed methodology is next
applied jointly with the complexity-reducing Per-Group Processing (PGP)
technique, on a per user group basis, in conjunction with QAM modulation and in
simulations, for constellation size up to . We show by numerical results
that the precoders developed offer significantly better performance than the
configuration with no precoder or the plain beamformer and with
Joint Precoder and Artificial Noise Design for MIMO Wiretap Channels with Finite-Alphabet Inputs Based on the Cut-Off Rate
We consider precoder and artificial noise (AN) design for multi-antenna wiretap channels under the finite-alphabet input assumption. We assume that the transmitter has access to the channel coefficients of the legitimate receiver and knows the statistics of the eavesdropper's channel. Accordingly, we propose a secrecy rate maximization algorithm using a gradient descent-based optimization of the precoder matrix and an exhaustive search over the power levels allocated to the AN. We also propose algorithms to reduce the complexities of direct ergodic secrecy rate maximization by: 1) maximizing a cut-off rate-based approximation for the ergodic secrecy rate, simplifying the mutual information expression, which lacks a closed-form and 2) diagonalizing the channels toward the legitimate receiver and the eavesdropper, which allows for employing a per-group precoding-based technique. Our numerical results reveal that jointly optimizing the precoder and the AN outperforms the existing solutions in the literature, which rely on the precoder optimization only. We also demonstrate that the proposed low complexity alternatives result in a small loss in performance while offering a significant reduction in computational complexity. © 2002-2012 IEEE
Analysis of SVD-Based Hybrid Schemes for Massive MIMO with Phase Noise and Imperfect Channel Estimation
In hybrid analog-digital schemes, proposed to reduce the number of RF chains especially at millimeter waves, the precoding at the transmitter and the combining at the receiver are split into digital and analog parts. We analyze the sensitivity of hybrid schemes to phase noise and channel estimation errors and we compare them to a full-digital approach. The scheme adopted for the analog part employs fixed phase shifters, then the digital part is optimized by a singular-value decomposition. We derive analytical expressions for the interference and the SNR degradation arising from the imperfect decomposition due to phase noise and the channel estimation error, for typical millimter-wave massive MIMO channels. In particular we show that when the channel estimation is made in the beam-space, this hybrid scheme is more robust to the phase noise and to the channel estimation errors than a full-digital approach
Low-complexity MIMO precoding with discrete signals and statistical CSI
In this paper, we investigate the design of multiple-input multiple-output single-user precoders for finite-alphabet signals under the premise of statistical channel-state information at the transmitter. Based on an asymptotic expression for the mutual information of channels exhibiting antenna correlations, we propose a low-complexity iterative algorithm that radically reduces the computational load of existing approaches by orders of magnitude with only minimal losses in performance. The complexity savings increase with the number of transmit antennas and with the cardinality of the signal alphabet, making it possible to support values thereof that were unwieldy in existing solutions.The work of Y. Wu and R. Schober was supported by the Alexander von/nHumboldt Foundation. The work of C.-K. Wen was supported in part by the/nthe Ministry of Science and Technology, Taiwan, under Grant MOST103-/n2221-E-110-029-MY3
Low-complexity MIMO precoding with discrete signals and statistical CSI
In this paper, we investigate the design of multiple-input multiple-output single-user precoders for finite-alphabet signals under the premise of statistical channel-state information at the transmitter. Based on an asymptotic expression for the mutual information of channels exhibiting antenna correlations, we propose a low-complexity iterative algorithm that radically reduces the computational load of existing approaches by orders of magnitude with only minimal losses in performance. The complexity savings increase with the number of transmit antennas and with the cardinality of the signal alphabet, making it possible to support values thereof that were unwieldy in existing solutions.The work of Y. Wu and R. Schober was supported by the Alexander von/nHumboldt Foundation. The work of C.-K. Wen was supported in part by the/nthe Ministry of Science and Technology, Taiwan, under Grant MOST103-/n2221-E-110-029-MY3