375 research outputs found
Wireless MIMO Switching: Weighted Sum Mean Square Error and Sum Rate Optimization
This paper addresses joint transceiver and relay design for a wireless
multiple-input-multiple-output (MIMO) switching scheme that enables data
exchange among multiple users. Here, a multi-antenna relay linearly precodes
the received (uplink) signals from multiple users before forwarding the signal
in the downlink, where the purpose of precoding is to let each user receive its
desired signal with interference from other users suppressed. The problem of
optimizing the precoder based on various design criteria is typically
non-convex and difficult to solve. The main contribution of this paper is a
unified approach to solve the weighted sum mean square error (MSE) minimization
and weighted sum rate maximization problems in MIMO switching. Specifically, an
iterative algorithm is proposed for jointly optimizing the relay's precoder and
the users' receive filters to minimize the weighted sum MSE. It is also shown
that the weighted sum rate maximization problem can be reformulated as an
iterated weighted sum MSE minimization problem and can therefore be solved
similarly to the case of weighted sum MSE minimization. With properly chosen
initial values, the proposed iterative algorithms are asymptotically optimal in
both high and low signal-to-noise ratio (SNR) regimes for MIMO switching,
either with or without self-interference cancellation (a.k.a., physical-layer
network coding). Numerical results show that the optimized MIMO switching
scheme based on the proposed algorithms significantly outperforms existing
approaches in the literature.Comment: This manuscript is under 2nd review of IEEE Transactions on
Information Theor
Linear Precoding Designs for Amplify-and-Forward Multiuser Two-Way Relay Systems
Two-way relaying can improve spectral efficiency in two-user cooperative
communications. It also has great potential in multiuser systems. A major
problem of designing a multiuser two-way relay system (MU-TWRS) is transceiver
or precoding design to suppress co-channel interference. This paper aims to
study linear precoding designs for a cellular MU-TWRS where a multi-antenna
base station (BS) conducts bi-directional communications with multiple mobile
stations (MSs) via a multi-antenna relay station (RS) with amplify-and-forward
relay strategy. The design goal is to optimize uplink performance, including
total mean-square error (Total-MSE) and sum rate, while maintaining individual
signal-to-interference-plus-noise ratio (SINR) requirement for downlink
signals. We show that the BS precoding design with the RS precoder fixed can be
converted to a standard second order cone programming (SOCP) and the optimal
solution is obtained efficiently. The RS precoding design with the BS precoder
fixed, on the other hand, is non-convex and we present an iterative algorithm
to find a local optimal solution. Then, the joint BS-RS precoding is obtained
by solving the BS precoding and the RS precoding alternately. Comprehensive
simulation is conducted to demonstrate the effectiveness of the proposed
precoding designs.Comment: 13 pages, 12 figures, Accepted by IEEE TW
How to Understand LMMSE Transceiver Design for MIMO Systems From Quadratic Matrix Programming
In this paper, a unified linear minimum mean-square-error (LMMSE) transceiver
design framework is investigated, which is suitable for a wide range of
wireless systems. The unified design is based on an elegant and powerful
mathematical programming technology termed as quadratic matrix programming
(QMP). Based on QMP it can be observed that for different wireless systems,
there are certain common characteristics which can be exploited to design LMMSE
transceivers e.g., the quadratic forms. It is also discovered that evolving
from a point-to-point MIMO system to various advanced wireless systems such as
multi-cell coordinated systems, multi-user MIMO systems, MIMO cognitive radio
systems, amplify-and-forward MIMO relaying systems and so on, the quadratic
nature is always kept and the LMMSE transceiver designs can always be carried
out via iteratively solving a number of QMP problems. A comprehensive framework
on how to solve QMP problems is also given. The work presented in this paper is
likely to be the first shoot for the transceiver design for the future
ever-changing wireless systems.Comment: 31 pages, 4 figures, Accepted by IET Communication
Robust MMSE beamforming for multiantenna relay networks
In this paper, we propose a robust minimum mean square error (MMSE) based beamforming
technique for multiantenna relay broadcast channels, where a multi-antenna base station transmits signal to single antenna users with the help of a multiantenna relay. The signal transmission from the base station to the single antenna users is completed in two time slots, where the relay receives the signal from the base station in the first time slot and it then forwards the received signal to different users based on amplify and forward protocol. We propose a robust beamforming technique for sum-power
minimization problem with imperfect channel state information (CSI) between the relay and the users. This robust scheme is developed based on the worst-case optimization framework and Nemirovski
Lemma by incorporating uncertainties in the CSI. The original optimization problem is divided into three subproblems due to joint non-convexity in terms of beamforming vectors at the base station, the relay amplification matrix, and receiver coefficients. These subproblems are formulated into a convex optimization framework by exploiting Nemirovski Lemma, and an iterative algorithm is developed by
alternatively optimizing each of them with channel uncertainties. In addition, we provide an optimization framework to evaluate the achievable worst-case mean square error (MSE) of each user for a given set of design parameters. Simulation results have been provided to validate the convergence of the proposed algorithm
Linear Precoders for Non-Regenerative Asymmetric Two-way Relaying in Cellular Systems
Two-way relaying (TWR) reduces the spectral-efficiency loss caused in
conventional half-duplex relaying. TWR is possible when two nodes exchange data
simultaneously through a relay. In cellular systems, data exchange between base
station (BS) and users is usually not simultaneous e.g., a user (TUE) has
uplink data to transmit during multiple access (MAC) phase, but does not have
downlink data to receive during broadcast (BC) phase. This non-simultaneous
data exchange will reduce TWR to spectrally-inefficient conventional
half-duplex relaying. With infrastructure relays, where multiple users
communicate through a relay, a new transmission protocol is proposed to recover
the spectral loss. The BC phase following the MAC phase of TUE is now used by
the relay to transmit downlink data to another user (RUE). RUE will not be able
to cancel the back-propagating interference. A structured precoder is designed
at the multi-antenna relay to cancel this interference. With multiple-input
multiple-output (MIMO) nodes, the proposed precoder also triangulates the
compound MAC and BC phase MIMO channels. The channel triangulation reduces the
weighted sum-rate optimization to power allocation problem, which is then cast
as a geometric program. Simulation results illustrate the effectiveness of the
proposed protocol over conventional solutions.Comment: 30 pages, 7 figures, submitted to IEEE Transactions on Wireless
Communication
Mathematical optimization and signal processing techniques for cooperative wireless networks
The rapid growth of mobile users and emergence of high data rate multimedia and interactive services have resulted in a shortage of the radio spectrum. Novel solutions are therefore required for future generations of wireless networks to enhance capacity and coverage. This thesis aims at addressing this issue through the design and analysis of signal processing algorithms. In particular various resource allocation and spatial diversity techniques have
been proposed within the context of wireless peer-to-peer relays and coordinated base station (BS) processing.
In order to enhance coverage while providing improvement in capacity, peer-to-peer relays that share the same frequency band have been considered and various techniques for designing relay coefficients and allocating powers optimally are proposed. Both one-way and two-way amplify and forward (AF) relays have been investigated. In order to maintain fairness, a signal-to-interference plus noise ratio (SINR) balancing criterion has been adopted. In order to improve the spectrum utilization further, the relays within the context of cognitive radio network are also considered. In this case, a cognitive peer-to-peer relay network is required to achieve SINR balancing while maintaining the interference leakage to primary receiver below a certain threshold.
As the spatial diversity techniques in the form of multiple-input-multipleoutput (MIMO) systems have the potential to enhance capacity significantly, the above work has been extended to peer-to-peer MIMO relay networks. Transceiver and relay beamforming design based on minimum mean-square error (MSE) criterion has been proposed. Establishing uplink downlink MSE duality, an alternating algorithm has been developed. A scenario where multiple users are served by both the BS and a MIMO relay is considered and a joint beamforming technique for the BS and the MIMO relay is proposed. With the motivation of optimising the transmission power at both the BS and the relay, an interference precoding design is presented that takes into account the knowledge of the interference caused by the relay to the users served by the BS.
Recognizing joint beamformer design for multiple BSs has the ability to reduce interference in the network significantly, cooperative multi-cell beamforming design is proposed. The aim is to design multi-cell beamformers to maximize the minimum SINR of users subject to individual BS power constraints. In contrast to all works available in the literature that aimed at balancing SINR of all users in all cells to the same level, the SINRs of users in each cell is balanced and maximized at different values. This new technique takes advantage of the fact that BSs may have different available transmission powers and/or channel conditions for their users
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