75 research outputs found
Linear transceiver design for amplify-and-forward MIMO relay systems under channel uncertainties
Proceedings of the IEEE Wireless Communications and Networking Conference, 2010, p. 1-6In this paper, robust joint design of linear relay precoders and destination equalizers for amplify-and-forward (AF) MIMO relay systems under Gaussian channel uncertainties is investigated. After incorporating the channel uncertainties into the robust design based on the Bayesian framework, a closed-form solution is derived to minimize the mean-square-error (MSE) of the received signal at the destination. The effectiveness of the proposed robust transceiver is verified by simulations. ©2010 IEEE.published_or_final_versionThe IEEE Wireless Communications and Networking Conference (WCNC), Sydney, Australia, 18-21 April 2010. In Proceedings of WCNC, 2010, p. 1-
Joint robust weighted LMMSE transceiver design for dual-hop AF multiple-antenna relay systems
In this paper, joint transceiver design for dual-hop amplify-and-forward (AF) MIMO relay systems with Gaussian distributed channel estimation errors in both two hops is investigated. Due to the fact that various linear transceiver designs can be transformed to a weighted linear minimum mean-square-error (LMMSE) transceiver design with specific weighting matrices, weighted mean square error (MSE) is chosen as the performance metric. Precoder matrix at source, forwarding matrix at relay and equalizer matrix at destination are jointly designed with channel estimation errors taken care of by Bayesian philosophy. Several existing algorithms are found to be special cases of the proposed solution. The performance advantage of the proposed robust design is demonstrated by the simulation results. © 2011 IEEE.published_or_final_versionThe 2011 IEEE Global Telecommunications Conference (GLOBECOM 2011), Beijing, China, 5-9 December 2011. In Globecom. IEEE Conference and Exhibition, 2011, p. 1-
Rate-Energy Balanced Precoding Design for SWIPT based Two-Way Relay Systems
Simultaneous wireless information and power transfer (SWIPT) technique is a
popular strategy to convey both information and RF energy for harvesting at
receivers. In this regard, we consider a two-way relay system with multiple
users and a multi-antenna relay employing SWIPT strategy, where splitting the
received signal leads to a rate-energy trade-off. In literature, the works on
transceiver design have been studied using computationally intensive and
suboptimal convex relaxation based schemes. In this paper, we study the
balanced precoder design using chordal distance (CD) decomposition, which
incurs much lower complexity, and is flexible to dynamic energy requirements.
It is analyzed that given a non-negative value of CD, the achieved harvested
energy for the proposed balanced precoder is higher than that for the perfect
interference alignment (IA) precoder. The corresponding loss in sum rates is
also analyzed via an upper bound. Simulation results add that the IA schemes
based on mean-squared error are better suited for the SWIPT maximization than
the subspace alignment-based methods.Comment: arXiv admin note: text overlap with arXiv:2101.1216
A General Robust Linear Transceiver Design for Multi-Hop Amplify-and-Forward MIMO Relaying Systems
In this paper, linear transceiver design for multi-hop amplify-and-forward
(AF) multiple-input multiple-out (MIMO) relaying systems with Gaussian
distributed channel estimation errors is investigated. Commonly used
transceiver design criteria including weighted mean-square-error (MSE)
minimization, capacity maximization, worst-MSE/MAX-MSE minimization and
weighted sum-rate maximization, are considered and unified into a single
matrix-variate optimization problem. A general robust design algorithm is
proposed to solve the unified problem. Specifically, by exploiting majorization
theory and properties of matrix-variate functions, the optimal structure of the
robust transceiver is derived when either the covariance matrix of channel
estimation errors seen from the transmitter side or the corresponding
covariance matrix seen from the receiver side is proportional to an identity
matrix. Based on the optimal structure, the original transceiver design
problems are reduced to much simpler problems with only scalar variables whose
solutions are readily obtained by iterative water-filling algorithm. A number
of existing transceiver design algorithms are found to be special cases of the
proposed solution. The differences between our work and the existing related
work are also discussed in detail. The performance advantages of the proposed
robust designs are demonstrated by simulation results.Comment: 30 pages, 7 figures, Accepted by IEEE Transactions on Signal
Processin
Transceiver Design for Dual-Hop Non-regenerative MIMO-OFDM Relay Systems Under Channel Uncertainties
In this paper, linear transceiver design for dual-hop non-regenerative
(amplify-and-forward (AF)) MIMO-OFDM systems under channel estimation errors is
investigated. Second order moments of channel estimation errors in the two hops
are first deduced. Then based on the Bayesian framework, joint design of linear
forwarding matrix at the relay and equalizer at the destination under channel
estimation errors is proposed to minimize the total mean-square-error (MSE) of
the output signal at the destination. The optimal designs for both correlated
and uncorrelated channel estimation errors are considered. The relationship
with existing algorithms is also disclosed. Moreover, this design is extended
to the joint design involving source precoder design. Simulation results show
that the proposed design outperforms the design based on estimated channel
state information only.Comment: 30 pages, 6 figures, IEEE Transactions on Signal Processing, The
Final Versio
Matrix-Monotonic Optimization for MIMO Systems
For MIMO systems, due to the deployment of multiple antennas at both the
transmitter and the receiver, the design variables e.g., precoders, equalizers,
training sequences, etc. are usually matrices. It is well known that matrix
operations are usually more complicated compared to their vector counterparts.
In order to overcome the high complexity resulting from matrix variables, in
this paper we investigate a class of elegant multi-objective optimization
problems, namely matrix-monotonic optimization problems (MMOPs). In our work,
various representative MIMO optimization problems are unified into a framework
of matrix-monotonic optimization, which includes linear transceiver design,
nonlinear transceiver design, training sequence design, radar waveform
optimization, the corresponding robust design and so on as its special cases.
Then exploiting the framework of matrix-monotonic optimization the optimal
structures of the considered matrix variables can be derived first. Based on
the optimal structure, the matrix-variate optimization problems can be greatly
simplified into the ones with only vector variables. In particular, the
dimension of the new vector variable is equal to the minimum number of columns
and rows of the original matrix variable. Finally, we also extend our work to
some more general cases with multiple matrix variables.Comment: 37 Pages, 5 figures, IEEE Transactions on Signal Processing, Final
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