32 research outputs found
Exploiting statistical and outdated CSI in multiuser downlink transmission
In this paper, we propose a multiuser downlink transmission scheme, which exploits both the statistical and outdated channel state information (CSI) at the transmitter. The proposed scheme extends the outdated CSI-aided scheme, first introduced by Maddah-Ali and Tse in [1] (denoted as MAT), by sending symbols demanded by a user along its statistical eigenmodes, instead of directly sending the symbols through separate antennas, and we refer to it as statistical eigenmode-MAT (SE-MAT). Considering zero-forcing receiver, we explicitly prove that the proposed SE-MAT scheme can achieve a higher ergodic sum-rate compared to the original MAT scheme, under different correlation conditions. Moreover, a user selection method which selects statistically orthogonal users for the SE-MAT transmission is proposed to further improve the system performance
Transmit Precoding for MIMO Systems with Partial CSI and Discrete-Constellation Inputs
In this paper, we consider the transmit linear precoding problem for MIMO systems with discrete-constellation inputs. We assume that the receiver has perfect channel state information (CSI) and the transmitter only has partial CSI, namely, the channel covariance information. We first consider MIMO systems over frequency-flat fading channels. We design the optimal linear precoder based on direct maximization of mutual information over the MIMO channels with discrete-constellation inputs. It turns out that the optimal linear precoder is a non-diagonal non-unitary matrix. Then, we consider MIMO systems over frequency selective fading channels via extending our method to MIMO-OFDM systems. To keep reasonable computational complexity of solving the linear precoding matrix, we propose a sub-optimal approach to restrict the precoding matrix as a block-diagonal matrix. This approach has near-optimal performance when we integrate it with a properly chosen interleaver. Numerical examples show that for MIMO systems over frequency flat fading channels, our proposed optimal linear precoder enjoys 6-9 dB gain compared to the same system without linear precoder. For MIMO-OFDM systems, our reduced-complexity sub-optimal linear precoder captures 3-6 dB gain compared to the same system with no precoding. Moreover, for those MIMO systems employing a linear precoder designed based on Gaussian inputs with gap approximation technique for discrete-constellation inputs, significant loss may occur when the signal-to-noise ratio is larger than 0 dB
Power Allocation Games in Wireless Networks of Multi-antenna Terminals
We consider wireless networks that can be modeled by multiple access channels
in which all the terminals are equipped with multiple antennas. The propagation
model used to account for the effects of transmit and receive antenna
correlations is the unitary-invariant-unitary model, which is one of the most
general models available in the literature. In this context, we introduce and
analyze two resource allocation games. In both games, the mobile stations
selfishly choose their power allocation policies in order to maximize their
individual uplink transmission rates; in particular they can ignore some
specified centralized policies. In the first game considered, the base station
implements successive interference cancellation (SIC) and each mobile station
chooses his best space-time power allocation scheme; here, a coordination
mechanism is used to indicate to the users the order in which the receiver
applies SIC. In the second framework, the base station is assumed to implement
single-user decoding. For these two games a thorough analysis of the Nash
equilibrium is provided: the existence and uniqueness issues are addressed; the
corresponding power allocation policies are determined by exploiting random
matrix theory; the sum-rate efficiency of the equilibrium is studied
analytically in the low and high signal-to-noise ratio regimes and by
simulations in more typical scenarios. Simulations show that, in particular,
the sum-rate efficiency is high for the type of systems investigated and the
performance loss due to the use of the proposed suboptimum coordination
mechanism is very small
Adaptive Transmission with Partial Channel Information in Spatially Correlated MIMO Channels
We propose a new adaptive multiple-input multipleoutput
(MIMO) transmission scheme that can work with partial
channel information. Utilizing the information on dominant eigendimensions
of the channel correlation matrix, the proposed
scheme reduces the amount of channel information required for
adaptive transmission without noticeable performance
degradation. It is analytically shown that the proposed scheme can
minimize the performance loss by properly choosing the number
of eigen-dimensions of the channel correlation matrix. Simulation
results show that the proposed scheme is quite applicable to
practical systems where quantized channel information is utilized
On the precoder design of flat fading MIMO systems equipped with MMSE receivers: a large system approach
This paper is devoted to the design of precoders maximizing the ergodic
mutual information (EMI) of bi-correlated flat fading MIMO systems equiped with
MMSE receivers. The channel state information and the second order statistics
of the channel are assumed available at the receiver side and at the
transmitter side respectively. As the direct maximization of the EMI needs the
use of non attractive algorithms, it is proposed to optimize an approximation
of the EMI, introduced recently, obtained when the number of transmit and
receive antennas and converge to at the same rate. It is
established that the relative error between the actual EMI and its
approximation is a term. It is shown that the left
singular eigenvectors of the optimum precoder coincide with the eigenvectors of
the transmit covariance matrix, and its singular values are solution of a
certain maximization problem. Numerical experiments show that the mutual
information provided by this precoder is close from what is obtained by
maximizing the true EMI, but that the algorithm maximizing the approximation is
much less computationally intensive.Comment: Submitted to IEEE Transactions on Information Theor