Matrix analysis
Elements of information theory
Elements of information theory
Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Matrix computations (3rd ed.)
Convex Optimization
Achieving log-utility fairness in cdma systems via majorization theory
IEEE Communications Letters
IEEE Transactions on Communications
Fair-rate allocation in multiuser OFDM-SDMA networks
IEEE Transactions on Signal Processing
Robust transceiver optimization in downlink multiuser MIMO systems
IEEE Transactions on Signal Processing
Linear processing and sum throughput in the multiuser MIMO downlink?
IEEE Transactions on Wireless Communications
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
Linear transmit processing in MIMO communications systems
IEEE Transactions on Signal Processing - Part I
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
Downlink MMSE Transceiver Optimization for Multiuser MIMO Systems: MMSE Balancing
IEEE Transactions on Signal Processing - Part I
A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach
IEEE Transactions on Wireless Communications
Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design
IEEE Transactions on Wireless Communications - Part 1
Opportunistic beamforming using dumb antennas
IEEE Transactions on Information Theory
On the achievable throughput of a multiantenna Gaussian broadcast channel
IEEE Transactions on Information Theory
Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality
IEEE Transactions on Information Theory
Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels
IEEE Transactions on Information Theory
On the duality of Gaussian multiple-access and broadcast channels
IEEE Transactions on Information Theory
On the capacity of MIMO broadcast channels with partial side information
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
IEEE Journal on Selected Areas in Communications
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In this paper, we study the linear transmission (or beamforming) techniques in MIMO broadcast channels (BC) and propose beamforming algorithms for rate optimization. Our method for algorithm design draws on ideas from the classic Arimoto-Blahut algorithm. Like Arimoto-Blahut algorithm, our algorithms operate iteratively in a two-stage manner, i.e., in one iteration, the first stage is for updating test conditional probabilities, the second for updating beamforming matrices, and both stages are composed of simple convex subproblems. Optimal transmit beamforming for weighted sum rate maximization, weighted rate balancing, and proportional fair rate allocation in MIMO BC are considered. We rediscover the weighted sum-rate beamforming weighted minimum mean square error (WSRBF-WMMSE) algorithm in [1] for MIMO BC. And we apply our method together with uplink-downlink duality to optimal beamforming for weighted rate balancing and proportional fair rate allocation in MIMO BC. We show experimentally that our algorithm for rate balancing requires less computation time to converge than existing algorithms without performance loss, and the algorithm for proportional fair rate allocation can achieve the balance between sum rate maximization and minimum rate maximization.