Convex Optimization
Recent advances in amplify-and-forward two-hop relaying
IEEE Communications Magazine
IEEE Transactions on Signal Processing
MIMO Relaying With Linear Processing for Multiuser Transmission in Fixed Relay Networks
IEEE Transactions on Signal Processing
Linear Transceiver Design in Nonregenerative Relays With Channel State Information
IEEE Transactions on Signal Processing
Optimal Design of Non-Regenerative MIMO Wireless Relays
IEEE Transactions on Wireless Communications
MIMO Configurations for Relay Channels: Theory and Practice
IEEE Transactions on Wireless Communications
Optimality of diagonalization of multi-hop MIMO relays
IEEE Transactions on Wireless Communications
Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Practical Vector Dirty Paper Coding for MIMO Gaussian Broadcast Channels
IEEE Journal on Selected Areas in Communications
Joint precoding and power allocation for multiuser transmission in MIMO relay networks
International Journal of Communication Systems
Weighted Sum Rate Maximization for Downlink Multiuser Relay Network with Direct Link
Wireless Personal Communications: An International Journal
Wireless Personal Communications: An International Journal
Hi-index | 35.68 |
A power allocation or scheduling problem is studied for a multiuser multiple-input multiple-output (MIMO) wireless relay system where there is a non-regenerative relay between one access point and multiple users. Each node in the system is equipped with multiple antennas. The purpose of this study is to develop fast algorithms to compute the source covariance matrix (or matrices) and the relay transformation matrix to optimize a system performance. We consider the minimization of power consumption subject to rate constraint and also the maximization of system throughput subject to power constraint. These problems are nonconvex and apparently have no simple solutions. In this paper, a number of computational strategies are presented and their performances are investigated. Both uplink and downlink cases are considered. The use of multiple carriers is also discussed. Moreover, a generalized water-filling (GWF) algorithm is developed to solve a special class of convex optimization problems. The GWF algorithm is used for two of the strategies shown in this paper.