Space-Time transmit precoding with imperfect feedback

By E. Visotsky, Upamanyu Madhow. IEEE Transactions on Information Theory, 2001

674 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8f093bed5c809511e7cb793833b4ddc5e69de7aa

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Citations in the corpus

What is the value of limited feedback for MIMO channels? (2004, background): “For example, these assumptions include perfect channel knowledge [1, 3, references therein], incomplete or estimated knowledge of subspaces associated with the channel [4] [5], and statistical channel knowledge (e.g., [6] [7] [8]).”
MIMO Transceiver Design via Majorization Theory (2007, unknown): “, [10, 101, 123, 159, 165].”
On beamforming with finite rate feedback in multiple-antenna systems (2003, methodology): “1The conditions for the optimality of beamforming with parti l channel information at the transmitter is investigated in [3, 7, 8] with mutual information as the performance metri c.”
Channel capacity and beamforming for multiple transmit and receive antennas with covariance feedback (2001, methodology): “when is just a row vector distributed as , the optimal solution was shown in [ 3 ] to consist of independent Gaussian inputs along the eigenvectors of . We show that the same is true for our case even with multiple receive antennas.”
Secure Transmission in Cognitive Satellite Terrestrial Networks (2016, background): “• Statistical CSI: In this case, the BS does not know the CSI of hp , but it has statistical information about the BS-PU link, namely hp ∼ N ( 0,Rp ) [32], where the channel correlation matrix (CCM) Rp is a non-negative definite Hermitian matrix with Rp ∈ CN×N and Rp 0.”
An overview of limited feedback in wireless communication systems (2008, background): “One of the first looks at trying to design the covariance matrix using imperfect channel information was the covariance design for multiple-intput single-output (MISO) systems using statistical information published in [262].”
Great expectations: the value of spatial diversity in wireless networks (2004, background): “There has also been work in understanding the impact of imperfect transmitter channel state information on performance [38], [270].”
Optimal transmitter eigen-beamforming and space-time block coding based on channel mean feedback (2002, methodology): “Alamouti’s code suffers up to 50% rate loss when extended to more than two transmit antennas with spectrally efficient complex constellations.”
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].”
MIMO over Satellite: A Review (2011, methodology): “Prediction models for this particular attenuation factor have been developed within the framework of ITU-R Recommendation P.840 [63].”
Capacity limits of MIMO channels (2003, methodology): “Note that [40], [57], [58], and [76] assume a single receive antenna.”
Impact of antenna correlation on the capacity of multiantenna channels (2005, unknown): “(See also [53], [54] for multiple-transmit single-receive channels.”
Spectral efficiency in the wideband regime (2002, methodology): “In the special case of a single receive antenna, beamforming was shown to be asymptotically optimal for vanishing in [22] (see also [23]) using the traditional (first-order) optimality criterion.”