A vector-perturbation technique for near-capacity multiantenna multiuser communication-part II: perturbation

By Bertrand M. Hochwald, Christian B. Peel, A. L. Swindlehurst. IEEE Transactions on Communications, 2005

886 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ae48497325496831afbcc8f2b9a26db0e5cd109d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

A vector-perturbation technique for near-capacity multiantenna multiuser communication-part I: channel inversion and regularization (2005, methodology): “The second part of this paper [13] describes a vector perturbation technique that is used in conjunction with regularization to obtain good performance at all SNR’s.”
Performance of Conjugate and Zero-Forcing Beamforming in Large-Scale Antenna Systems (2013, background): “…with respect to net spectral-efficiency and radiated energy-efficiency in a simplified single-cell scenario where propagation is governed by independent Rayleigh fading, and where channel-state information (CSI) acquisition and data transmission are both performed during a short coherence interval.”
Shifting the MIMO Paradigm (2007, methodology): “Vector perturbation uses a modulo operation at the transmitter to perturb the transmitted signal vector to avoid the transmit power enhancement incurred by ZF methods [21].”
Millimeter-Wave Massive MIMO Communication for Future Wireless Systems: A Survey (2018, background): “implementation feasibility than non-linear precoders (such as dirty-paper-coding (DPC) [46], vector perturbation (VP) [191]”
Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization (2015, background): “inversion [7]- [11] offer the least complexity, but their performance is far from achieving the optimum maximum likelihood bound. Their nonlinear adaptation, namely vector perturbation (VP) precoding [12]- [15] provides a performance improvement at the expense of an increased complexity since the se”
OTFS: A New Generation of Modulation Addressing the Challenges of 5G (2018, methodology): “However, finding the optimal perturbation vector has exponential complexity, therefore in practice Tomlinson-Harashima Precoding (THP) is used to find a “good” perturbation vector [11], [12], [13].”
Quantized Precoding for Massive MU-MIMO (2016, methodology): “Several precoding algorithms to approach the DPC performance have been proposed (see, e.g., [9]–[12]).”