Grassmannian beamforming for multiple-input multiple-output wireless systems

By D. J. Love, Robert W. Heath, Thomas Strohmer. IEEE International Conference on Communications, 2003. ICC '03., 2003

1,657 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8a3020ce8fa71f9c6bb802b07830a24b07ed606b

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Fast transfer of channel state information in wireless systems (2006, methodology): “coded and modulated onto a standard PSK or QAM constellation [ 17 , 18].”
Millimeter Wave Beamforming for Wireless Backhaul and Access in Small Cell Networks (2013, methodology): “In conventional MIMO beamforming systems [21], the beamforming codeword is selected as a function of the estimated channel to maximize some measure of system performance.”
High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning (2019, background): “This relationship has also been extended to the multiple-input multiple-output (MIMO) case [13].”
Achieving the Welch bound with difference sets (2005, methodology): “Also based on results from [19], another bound becomes available [16, Theorem 2] I max 1 4N (cid:0)1=(K(cid:0)1) 1=2 (30) which is always inferior to the new bound in (29).”
MIMO Relaying With Linear Processing for Multiuser Transmission in Fixed Relay Networks (2008, methodology): “A well-known approach for feedback is using vector quantization or limited feedback [42], [43].”
Cooperative Algorithms for MIMO Interference Channels (2010, background): “…SINR design has the best overall performance of all proposed strategies (in most cases, as shown in the simulations), but requires more channel state information than the previous designs and also results in non-orthogonal pre-coders which are difﬁcult to quantize in a practical setting [24].”
Multiple-antenna techniques for wireless communications - a comprehensive literature survey (2009, background): “SA Rx beamforming [5] Rx Rx N/W low ANT Tx beamforming [5] Tx Tx & Rx N/W low ANT Limited feedback schemes [148], [149] Tx (& Rx) Tx (lim.”
What is the value of limited feedback for MIMO channels? (2004, methodology): “This model has been proposed for limited feedback beamforming [12] [13], precoded orthogonal space-time block codes [1] [14], precoded spatial multiplexing [15] [16], and transmit covariance optimization [17] [18].”
MIMO Broadcast Channels With Finite-Rate Feedback (2006, background): “receiver quantizes its channel to the quantization vector that is closest to its channel vector, where closeness is measured in terms of the angle between two vectors or, equivalently, the inner product [4], [5].”
High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning (2020, background): “On the other hand, for a ﬁnite codebook size and a MIMO channel with rich scattering, an important ﬁnding is reported in [16], [17] that the optimal beamforming/precoding codebook design can be translated into the mathematical problem of Grass-mannian line/subspace packing.”
Spatially Sparse Precoding in Millimeter Wave MIMO Systems (2013, background): “FBB is a subspace quantity that can be quantized on the Grassmann manifold [52], [53].”
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming (2006, methodology): “For single-user MIMO channels, various types of imperfect CSIT, including covariance [30], delayed [31], and quantized feedback [32], have been considered in the literature.”
A Comprehensive Survey on Millimeter Wave Communications for Fifth-Generation Wireless Networks: Feasibility and Challenges (2020, background): “Grassmannian manifold codebook [280] is designed to maximize the minimum distance between any pair of lines, spanned by the codebook vectors.”
An overview of limited feedback in wireless communication systems (2008, methodology): “Using codebooks based on the Fourier concept for limited feedback was later generalized in [162], [175], based on a design in [84].”
Limited feedback unitary precoding for spatial multiplexing systems (2005, background): “WhenM = 1, it is also known that the o(Mt) term is always 2 and (24) is an exact expression [20].”
Multi-Antenna Downlink Channels with Limited Feedback and User Selection (2007, background): “Note that for a single user system, CQI is not necessary since there is no need of user selection.”
On beamforming with finite rate feedback in multiple-antenna systems (2003, background): “It is interesting to note that a different approach, viz., SNR maximization, also leads to the same design criterion for beamformer codebooks with single receive antenna [11]–[13].”
Multimode antenna selection for spatial multiplexing systems with linear receivers (2005, methodology): “We could approach this bound as close as desired by increasing the number of vectors in using the quantization-based approach of [25].”