9 research outputs found
Robust Transceiver with Tomlinson-Harashima Precoding for Amplify-and-Forward MIMO Relaying Systems
In this paper, robust transceiver design with Tomlinson-Harashima precoding
(THP) for multi-hop amplify-and-forward (AF) multiple-input multiple-output
(MIMO) relaying systems is investigated. At source node, THP is adopted to
mitigate the spatial intersymbol interference. However, due to its nonlinear
nature, THP is very sensitive to channel estimation errors. In order to reduce
the effects of channel estimation errors, a joint Bayesian robust design of THP
at source, linear forwarding matrices at relays and linear equalizer at
destination is proposed. With novel applications of elegant characteristics of
multiplicative convexity and matrix-monotone functions, the optimal structure
of the nonlinear transceiver is first derived. Based on the derived structure,
the transceiver design problem reduces to a much simpler one with only scalar
variables which can be efficiently solved. Finally, the performance advantage
of the proposed robust design over non-robust design is demonstrated by
simulation results.Comment: IEEE Journal on Selected Areas in Communications - Special Issue on
Theories and Methods for Advanced Wireless Relays The final version and
several typos have been correcte
Robust Tomlinson-Harashima precoding for non-regenerative multi-antenna relaying systems
Conference Theme: PHY and FundamentalsIn this paper, we consider the robust transceiver design with Tomlinson-Harashima precoding (THP) for multi-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying systems. THP is adopted at the source to mitigate the spatial inter-symbol interference and then a joint Bayesian robust design of THP at source, linear forwarding matrices at relays and linear equalizer at destination is proposed. Based on the elegant characteristics of multiplicative convexity and matrix-monotone functions, the optimal structure of the nonlinear transceiver is first derived. Based on the derived structure, the optimization problem is greatly simplified and can be efficiently solved. Finally, the performance advantage of the proposed robust design is assessed by simulation results. © 2012 IEEE.published_or_final_versionThe 2012 IEEE Wireless Communications and Networking Conference (WCNC), Paris, France, 1-4 April 2012. In IEEE Wireless Communications and Networking Conference Proceedings, 2012, p. 753-75
Hybrid Transceiver Optimization for Multi-Hop Communications
Multi-hop communication with the aid of large-scale antenna arrays will play
a vital role in future emergence communication systems. In this paper, we
investigate amplify-and-forward based and multiple-input multiple-output
assisted multi-hop communication, in which all nodes employ hybrid
transceivers. Moreover, channel errors are taken into account in our hybrid
transceiver design. Based on the matrix-monotonic optimization framework, the
optimal structures of the robust hybrid transceivers are derived. By utilizing
these optimal structures, the optimizations of analog transceivers and digital
transceivers can be separated without loss of optimality. This fact greatly
simplifies the joint optimization of analog and digital transceivers. Since the
optimization of analog transceivers under unit-modulus constraints is
non-convex, a projection type algorithm is proposed for analog transceiver
optimization to overcome this difficulty. Based on the derived analog
transceivers, the optimal digital transceivers can then be derived using
matrix-monotonic optimization. Numeral results obtained demonstrate the
performance advantages of the proposed hybrid transceiver designs over other
existing solutions.Comment: 32 pages, 6 figures. This manuscript has been submitted to IEEE
Journal on Selected Areas in Communications (special issue on Multiple
Antenna Technologies for Beyond 5G
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
Versio
Robust transceiver designs for MIMO relay communication systems
The thesis investigates robust linear and non-linear transceiver design problems for wireless MIMO relay communication systems with the assumption that the partial information of the channel is available at the relay node. The joint source and relay optimization problems for MIMO relay systems are highly nonconvex, in general. We transform the problems into suitable forms which can be efficiently solved using standard convex optimization techniques. The proposed design schemes outperform the existing techniques