Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Blind Channel Equalization and Identification
Blind Channel Equalization and Identification
Deterministic blind subspace MIMO equalization
EURASIP Journal on Applied Signal Processing
Blind separation of synchronous co-channel digital signals using anantenna array. I. Algorithms
IEEE Transactions on Signal Processing
Closed-form blind symbol estimation in digital communications
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Adaptive blind source separation and equalization for multiple-input/multiple-output systems
IEEE Transactions on Information Theory
Blind channel identification based on second-order statistics: a frequency-domain approach
IEEE Transactions on Information Theory
Transmit beamforming and power control for cellular wireless systems
IEEE Journal on Selected Areas in Communications
A framework for uplink power control in cellular radio systems
IEEE Journal on Selected Areas in Communications
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Traditional joint power control and beamforming achieve the targeted signal-to-interference-noise ratio (SINR) at the receivers by assuming the knowledge of the measurements of channel parameters and SINR. Blind beamforming is an effective technique for beamforming and channel estimation without the need of training sequences, thus not consuming extra bandwidth. In this paper, we propose a novel joint power control and blind beamforming algorithm that reformulates the power control problem in such a way that it does not need any prior knowledge and additional measurements in the physical layer. In contrast to the traditional schemes that optimize SINR and, as a result, minimize bit error rate (BER), our proposed algorithm achieves the desired BER by adjusting a quantity available from blind beamforming. By sending this quantity to the transmitter through a feedback channel, the transmit power is iteratively updated in a distributed manner in the wireless networks with cochannel interferences (CCIS). Our proposed algorithm is more robust to estimation errors. We have shown in both analysis and simulation that our algorithm converges to the desired solution. In addition, a Cramer-Rao lower bound (CRB) is derived to compare with the performance of our proposed joint power control and blind beamforming system.