Convex Optimization
Iterative multiuser uplink and downlink beamforming under SINR constraints
IEEE Transactions on Signal Processing
Adaptive resource allocation in multiuser OFDM systems with proportional rate constraints
IEEE Transactions on Wireless Communications
Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels
IEEE Transactions on Information Theory
Sum power iterative water-filling for multi-antenna Gaussian broadcast channels
IEEE Transactions on Information Theory
Sum-capacity computation for the Gaussian vector broadcast channel via dual decomposition
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
Subchannel Allocation in Multiuser Multiple-Input–Multiple-Output Systems
IEEE Transactions on Information Theory
IEEE Communications Magazine
A perspective on the evolution of mobile communications
IEEE Communications Magazine
Capacity limits of MIMO channels
IEEE Journal on Selected Areas in Communications
Downlink capacity evaluation of cellular networks with known-interference cancellation
IEEE Journal on Selected Areas in Communications
An iterative water-filling algorithm for maximum weighted sum-rate of Gaussian MIMO-BC
IEEE Journal on Selected Areas in Communications
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Recently, the capacity region of the Gaussian broadcast channel has been characterized. For a given transmit power constraint, those points on the boundary of the capacity region can be regarded as the set of optimal operational points. The present work addresses the problem of selecting the point within this set that satisfies given constraints on the ratios between rates achieved by the different users in the network. This problem is usually known as rate balancing. To this end, the optimum iterative approach for general MIMO channels is revisited and adapted to an OFDM transmission scheme. Specifically, an algorithm is proposed that exploits the structure of the OFDM channel and whose convergence speed is essentially insensitive to the number of subcarriers. This is in contrast to a straightforward extension of the general MIMO algorithm to an OFDM scheme. Still, relatively high complexity and the need of a time-sharing policy to reach certain rates are at least two obstacles for a practical implementation of the optimum solution. Based on a novel decomposition technique for broadcast channels a suboptimum non-iterative algorithm is introduced that does not require time-sharing and very closely approaches the optimum solution.