251 research outputs found
Hardware Impairments Aware Transceiver Design for Bidirectional Full-Duplex MIMO OFDM Systems
In this paper we address the linear precoding and decoding design problem for
a bidirectional orthogonal frequencydivision multiplexing (OFDM) communication
system, between two multiple-input multiple-output (MIMO) full-duplex (FD)
nodes. The effects of hardware distortion as well as the channel state
information error are taken into account. In the first step, we transform the
available time-domain characterization of the hardware distortions for FD MIMO
transceivers to the frequency domain, via a linear Fourier transformation. As a
result, the explicit impact of hardware inaccuracies on the residual
selfinterference (RSI) and inter-carrier leakage (ICL) is formulated in
relation to the intended transmit/received signals. Afterwards, linear
precoding and decoding designs are proposed to enhance the system performance
following the minimum-mean-squarederror (MMSE) and sum rate maximization
strategies, assuming the availability of perfect or erroneous CSI. The proposed
designs are based on the application of alternating optimization over the
system parameters, leading to a necessary convergence. Numerical results
indicate that the application of a distortionaware design is essential for a
system with a high hardware distortion, or for a system with a low thermal
noise variance.Comment: Submitted to IEEE for publicatio
Joint source and relay optimization for interference MIMO relay networks
This paper considers multiple-input multiple-output (MIMO) relay communication in multi-cellular (interference)
systems in which MIMO source-destination pairs communicate simultaneously. It is assumed that due to severe
attenuation and/or shadowing effects, communication links can be established only with the aid of a relay node. The
aim is to minimize the maximal mean-square-error (MSE) among all the receiving nodes under constrained source
and relay transmit powers. Both one- and two-way amplify-and-forward (AF) relaying mechanisms are considered.
Since the exactly optimal solution for this practically appealing problem is intractable, we first propose optimizing the
source, relay, and receiver matrices in an alternating fashion. Then we contrive a simplified semidefinite programming
(SDP) solution based on the error covariance matrix decomposition technique, avoiding the high complexity of the
iterative process. Numerical results reveal the effectiveness of the proposed schemes
Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach
This paper considers the Sum-Rate (SR) maximization problem in downlink
MU-MISO systems under imperfect Channel State Information at the Transmitter
(CSIT). Contrary to existing works, we consider a rather unorthodox
transmission scheme. In particular, the message intended to one of the users is
split into two parts: a common part which can be recovered by all users, and a
private part recovered by the corresponding user. On the other hand, the rest
of users receive their information through private messages. This
Rate-Splitting (RS) approach was shown to boost the achievable Degrees of
Freedom (DoF) when CSIT errors decay with increased SNR. In this work, the RS
strategy is married with linear precoder design and optimization techniques to
achieve a maximized Ergodic SR (ESR) performance over the entire range of SNRs.
Precoders are designed based on partial CSIT knowledge by solving a stochastic
rate optimization problem using means of Sample Average Approximation (SAA)
coupled with the Weighted Minimum Mean Square Error (WMMSE) approach. Numerical
results show that in addition to the ESR gains, the benefits of RS also include
relaxed CSIT quality requirements and enhanced achievable rate regions compared
to conventional transmission with NoRS.Comment: accepted to IEEE Transactions on Communication
Robust Joint Precoder and Equalizer Design in MIMO Communication Systems
We address joint design of robust precoder and equalizer in a MIMO
communication system using the minimization of weighted sum of mean square
errors. In addition to imperfect knowledge of channel state information, we
also account for inaccurate awareness of interference plus noise covariance
matrix and power shaping matrix. We follow the worst-case model for imperfect
knowledge of these matrices. First, we derive the worst-case values of these
matrices. Then, we transform the joint precoder and equalizer optimization
problem into a convex scalar optimization problem. Further, the solution to
this problem will be simplified to a depressed quartic equation, the
closed-form expressions for roots of which are known. Finally, we propose an
iterative algorithm to obtain the worst-case robust transceivers.Comment: 2 figures, 5 pages, conferenc
A worst-case robust MMSE transceiver design for nonregenerative MIMO relaying
Transceiver designs have been a key issue in guaranteeing the performance of multiple-input multiple-output (MIMO) relay systems, which are, however, often subject to imperfect channel state information (CSI). In this paper, we aim to design a robust MIMO transceiver for nonregenerative MIMO relay systems against imperfect CSI from a worst-case robust perspective. Specifically, we formulate the robust transceiver design, under the minimum mean-squared error (MMSE) criterion, as a minimax problem. Then, by decomposing the minimax problem into two subproblems with respect to the relay precoder and destination equalizer, respectively, we show that the optimal solution to each subproblem has a favorable channel-diagonalizing structure under some mild conditions. Based on this finding, we transform the two complex-matrix subproblems into their equivalent scalar forms, both of which are proven to be convex and can be efficiently solved by our proposed methods. We further propose an alternating algorithm to jointly optimize the precoder and equalizer that only requires scalar operations. Finally, the effectiveness of the proposed robust design is verified by simulation results
Robust Linear Hybrid Beamforming Designs Relying on Imperfect CSI in mmWave MIMO IoT Networks
Linear hybrid beamformer designs are conceived for the decentralized
estimation of a vector parameter in a millimeter wave (mmWave) multiple-input
multiple-output (MIMO) Internet of Things network (IoTNe). The proposed designs
incorporate both total IoTNe and individual IoTNo power constraints, while also
eliminating the need for a baseband receiver combiner at the fusion center
(FC). To circumvent the non-convexity of the hybrid beamformer design problem,
the proposed approach initially determines the minimum mean square error (MMSE)
digital transmit precoder (TPC) weights followed by a simultaneous orthogonal
matching pursuit (SOMP)-based framework for obtaining the analog RF and digital
baseband TPCs. Robust hybrid beamformers are also derived for the realistic
imperfect channel state information (CSI) scenario, utilizing both the
stochastic and norm-ball CSI uncertainty frameworks. The centralized MMSE bound
derived in this work serves as a lower bound for the estimation performance of
the proposed hybrid TPC designs. Finally, our simulation results quantify the
benefits of the various designs developed.Comment: 15 pages, 7 figure
Transceiver Optimization for Interference MIMO Relay Communication Systems
This thesis focuses on transceivers design for interference MIMO relay systems. Based on the MMSE criterion, several iterative algorithms are proposed to jointly optimize the source, relay, and receiver matrices subjecting to the individual power constraints at the source and the relay nodes. These algorithms have better performance than some existing algorithms and provide a better performance-complexity trade-off which is interesting in practical interference MIMO relay communication systems
Joint Transceiver Design Algorithms for Multiuser MISO Relay Systems with Energy Harvesting
In this paper, we investigate a multiuser relay system with simultaneous
wireless information and power transfer. Assuming that both base station (BS)
and relay station (RS) are equipped with multiple antennas, this work studies
the joint transceiver design problem for the BS beamforming vectors, the RS
amplify-and-forward transformation matrix and the power splitting (PS) ratios
at the single-antenna receivers. Firstly, an iterative algorithm based on
alternating optimization (AO) and with guaranteed convergence is proposed to
successively optimize the transceiver coefficients. Secondly, a novel design
scheme based on switched relaying (SR) is proposed that can significantly
reduce the computational complexity and overhead of the AO based designs while
maintaining a similar performance. In the proposed SR scheme, the RS is
equipped with a codebook of permutation matrices. For each permutation matrix,
a latent transceiver is designed which consists of BS beamforming vectors,
optimally scaled RS permutation matrix and receiver PS ratios. For the given
CSI, the optimal transceiver with the lowest total power consumption is
selected for transmission. We propose a concave-convex procedure based and
subgradient-type iterative algorithms for the non-robust and robust latent
transceiver designs. Simulation results are presented to validate the
effectiveness of all the proposed algorithms
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