Base station transmitting antenna arrays for multipath environments
Signal Processing
Matrix analysis and applied linear algebra
Matrix analysis and applied linear algebra
Handbook of Antennas in Wireless Communications
Handbook of Antennas in Wireless Communications
Radio Resource Management for Wireless Networks
Radio Resource Management for Wireless Networks
Joint transmitter receiver diversity for efficient space division multiaccess
IEEE Transactions on Wireless Communications
Nearest neighbor decoding for additive non-Gaussian noise channels
IEEE Transactions on Information Theory
Transmit beamforming and power control for cellular wireless systems
IEEE Journal on Selected Areas in Communications
QoS-based resource allocation and transceiver optimization
Communications and Information Theory
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
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We study the problem of non-orthogonal spatial multiplexing under hard fairness constraints, assuming that the transmitter is equipped with multiple antennas and each of the independent receivers has a single antenna. Channel state information is available at the transmitter. All users are coupled by co-channel interference, thus maintaining individual QoS requirements requires the joint optimization of beamforming and power control. In this paper we study the problem in the absence of noise. The achievable signal-to-interference-ratios (SIR) of all user are limited by the amount of mutual cross-talk. The design question: at which level can the relative SIR levels be balanced under the given channel condition, and what are the optimal beamforming weights? Our approach is analytic. By exploiting the duality between uplink and downlink beamforming, we derive an iterative optimization scheme that is globally convergent and always finds the optimally balanced level. This provides a necessary and sufficient condition for the feasibility of the given scenario. Hence, the results will prove useful for the design of new beamforming algorithms as well as for new spectrally efficient resource allocation strategies.