Channel capacity and beamforming for multiple transmit and receive antennas with covariance feedback

By Syed Ali Jafar, Sriram Vishwanath, Andrea J. Goldsmith. ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240), 2001

296 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0ed5a281951581ad474a8d4f705a824ba478489d

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Citations in the corpus

From theory to practice: an overview of MIMO space-time coded wireless systems (2003, background): “Solutions to reduce the feedback cost include using instantaneous yet partial (few bits) CSIT [109] or stastistics of CSIT, such as long term channel correlation information [110], [111], to name a few of the recent papers here.”
Optimal transmitter eigen-beamforming and space-time block coding based on channel mean feedback (2002, background): “Case 2 (Quantized Feedback) [10], [12]:In this case, we assume that the channel is acquired at the receiver and is quantized to code words .”
Capacity limits of MIMO channels (2003, background): “[42], [40], [38], Jorsweick and Boche [45], [46], and Simon and Moustakas [56], [66].”
MIMO capacity through correlated channels in the presence of correlated interferers and noise: a (not so) large N analysis (2003, background): “This result has been shown in [26] to hold in general in the absence of interference for arbitrary antenna numbers (but can be generalized to hold in the presence of interference).”
Transmit signal design for optimal estimation of correlated MIMO channels (2004, background): “The above observations are consistent with those in [ 6 ] and [13], where the capacity analysis of a MIMO system assuming covariance feedback shows that capacity depends on a dominant subset of channel eigenvalues determined by the SNR.”
Random Matrix Theory and Wireless Communications (2004, unknown): “With statistical CSI at the transmitter, achieving capacity requires that the eigenvectors of the input covariance, Φ, coincide with those of ΘT [279, 123].”