97 research outputs found
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
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
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
Interference alignment for one-hop and two-hops MIMO systems with uncoordinated interference
Providing higher data rate is a momentous goal for wireless communications systems, while interference is an important obstacle to reach this purpose. To cope with this problem, interference alignment (IA) has been proposed. In this paper, we propose two rank minimization methods to enhance the performance of IA in the presence of uncoordinated interference, i.e., interference that cannot be properly aligned with the rest of the network and thus is a crucial issue. In this scenario, perfect and imperfect channel state information (CSI) cases are considered. Our proposed approaches employ the l2 and the Schatten-p norms to approximate the rank function, due to its non-convexity. Also, we propose a new convex relaxation to expand the feasible set of our optimization problem, providing lower rank solutions compared to other IA methods from the literature. In addition, we propose a modified weighted-sum method to deal with interference in the relay-aided MIMO interference channel, which employs a set of weighting parameters in order to find more solutions
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