387 research outputs found
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
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
Multiuser Multihop MIMO Relay System Design Based on Mutual Information Maximization
In this paper, we consider multiuser multihop relay communication systems, where the users, relays, and the destination node may have multiple antennas. We address the issue of source and relay precoding matrices design to maximize the system mutual information (MI). By exploiting the linkbetween the maximal MI and the weighted minimal mean-squared error (WMMSE) objective functions, we show that the intractable maximal MI-based source and relay optimization problem can be solved via the WMMSE-based source and relay design through an iterative approach which is guaranteed toconverge to at least a stationary point. For the WMMSE problem, we derive the optimal structure of the relay precoding matrices and show that the WMMSE matrix at the destination node can be decomposed into the sum of WMMSE matrices at all hops. Under a (moderately) high signal-to-noise ratio (SNR) condition, this WMMSE matrix decomposition significantly simplifies the solution to the WMMSE problem. Numerical simulations are performed to demonstrate the effectiveness of the proposed algorithm
Robust MMSE Precoding Strategy for Multiuser MIMO Relay Systems with Switched Relaying and Side Information
In this work, we propose a minimum mean squared error (MMSE) robust base station (BS) precoding strategy based on switched relaying (SR) processing and limited transmission of side information for interference suppression in the downlink of multiuser multiple-input multiple-output (MIMO) relay systems. The BS and the MIMO relay station (RS) are both equipped with a codebook of interleaving matrices. For a given channel state information (CSI) the selection function at the BS chooses the optimum interleaving matrix from the codebook based on two optimization criteria to design the robust precoder. Prior to the payload transmission the BS sends the index corresponding to the selected interleaving matrix to the RS, where the best interleaving matrix is selected to build the optimum relay processing matrix. The entries of the codebook are randomly generated unitary matrices. Simulation results show that the performance of the proposed techniques is significantly better than prior art in the case of imperfect CSI.
Resource allocation and optimization techniques in wireless relay networks
Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the
useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay
network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The
secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource
allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks
Maximizing the Sum Rate in Cellular Networks Using Multi-Convex Optimization
In this paper, we propose a novel algorithm to maximize the sum rate in
interference-limited scenarios where each user decodes its own message with the
presence of unknown interferences and noise considering the
signal-to-interference-plus-noise-ratio. It is known that the problem of
adapting the transmit and receive filters of the users to maximize the sum rate
with a sum transmit power constraint is non-convex. Our novel approach is to
formulate the sum rate maximization problem as an equivalent multi-convex
optimization problem by adding two sets of auxiliary variables. An iterative
algorithm which alternatingly adjusts the system variables and the auxiliary
variables is proposed to solve the multi-convex optimization problem. The
proposed algorithm is applied to a downlink cellular scenario consisting of
several cells each of which contains a base station serving several mobile
stations. We examine the two cases, with or without several half-duplex
amplify-and-forward relays assisting the transmission. A sum power constraint
at the base stations and a sum power constraint at the relays are assumed.
Finally, we show that the proposed multi-convex formulation of the sum rate
maximization problem is applicable to many other wireless systems in which the
estimated data symbols are multi-affine functions of the system variables.Comment: 24 pages, 5 figure
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
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