Multimode Transmission for Multiuser MIMO Systems With Block Diagonalization
IEEE Transactions on Signal Processing - Part II
On downlink beamforming with greedy user selection: performance analysis and a simple new algorithm
IEEE Transactions on Signal Processing - Part I
Rate Optimization for Multiuser MIMO Systems With Linear Processing
IEEE Transactions on Signal Processing - Part II
Joint Design of Tx-Rx Beamformers in MIMO Downlink Channel
IEEE Transactions on Signal Processing
Coordinated Beamforming for the Multiuser MIMO Broadcast Channel With Limited Feedforward
IEEE Transactions on Signal Processing
Downlink MMSE Transceiver Optimization for Multiuser MIMO Systems: Duality and Sum-MSE Minimization
IEEE Transactions on Signal Processing
Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels
IEEE Transactions on Signal Processing
Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization
IEEE Transactions on Signal Processing
User Selection With Zero-Forcing Beamforming Achieves the Asymptotically Optimal Sum Rate
IEEE Transactions on Signal Processing - Part I
Zero-Forcing Precoding and Generalized Inverses
IEEE Transactions on Signal Processing
On the achievable throughput of a multiantenna Gaussian broadcast channel
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
Downlink capacity evaluation of cellular networks with known-interference cancellation
IEEE Journal on Selected Areas in Communications
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
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
Weighted sum rate maximization in the MIMO MAC with linear transceivers: algorithmic solutions
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
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Achieving the boundary of the capacity region in the multiple-input multiple-output (MIMO) broadcast channel requires the use of dirty paper coding (DPC). As practical nearly optimum implementations of DPC are computationally complex, purely linear approaches are often used instead. However, in this case, the problem of maximizing a weighted sum rate constitutes a nonconvex and, in most cases, also a combinatorial optimization problem. In this paper, we present two heuristic nearly optimum algorithms with reduced computational complexity. For this purpose, a lower bound for the weighted sum rate under linear zero-forcing constraints is used. Based on this bound, both greedy algorithms successively allocate data streams to users. In each step, the user is determined that is given an additional data stream such that the increase in weighted sum rate becomes maximum. Thereby, the data stream allocations and filters obtained in the previous steps are kept fixed and only the filter corresponding to the additional data stream is optimized. The first algorithm determines the receive and transmit filters directly in the downlink. The other algorithm operates in the dual uplink, from which the downlink transmit and receive filters can be obtained via the general rate duality leading to nonzero-forcing in the downlink. Simulation results reveal marginal performance losses compared to more complex algorithms.