Linear transmit processing in MIMO communications systems
By M. Joham, Wolfgang Utschick, J. Nossek. IEEE Transactions on Signal Processing, 2005
860 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/ee13c7113905fcc396cb83af8e6bbde0d422d112
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In Computer Networks and Communications
- Emil Björnson
- Eduard Axel Jorswieck
- Robert W. Heath
- Björn E. Ottersten
- Luca Sanguinetti
- David Gesbert
- Gan Zheng
- Mats Bengtsson
In Electrical and Electronic Engineering
- Emil Björnson
- Luca Sanguinetti
- Robert W. Heath
- Eduard Axel Jorswieck
- Björn E. Ottersten
- David Gesbert
- Rui Zhang
- Gan Zheng
Citations in the corpus
- Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure [Lecture Notes] (2014, methodology): “(17) The heuristic beamforming in (17) is known as regularized zero-forcing beamforming [10] since the identity matrix acts as a regularization of the ZFBF in (14).”
- Beamspace MIMO for high-dimensional multiuser communication at millimeter-wave frequencies (2013, neutral): “4(a)) [20].”
- Quantized Precoding for Massive MU-MIMO (2016, methodology): “1) WF precoding: For the case when the BS is equipped with infinite-resolution DACs, the solution to (5) is the Wiener filter (WF) precoder [39]:”
- Zero-Forcing Precoding and Generalized Inverses (2008, background): “The ZF precoding design problem is closely related to the concept of generalized inverses in linear algebra [23], [30].”
- A Deep Learning Framework for Optimization of MISO Downlink Beamforming (2019, methodology): “To evaluate the performance of the proposed BNNs, we carry out numerical simulations to compare the BNNs with several benchmark solutions (when available), including the optimal beamforming, the ZF beamforming [58], the RZF beamforming [59], and the WMMSE algorithm.”
- Shifting the MIMO Paradigm (2007, background): “One of the simplest approaches for finding the precoder is to premultiply the transmitted signal by a suitably normalized ZF or MMSE inverse of the multiuser matrix channel [14], [15].”
- Optimal Resource Allocation in Coordinated Multi-Cell Systems (2013, methodology): “The counterparts to the three classic receive combining techniques are maximum ratio transmission (MRT), zero-forcing beamforming (ZFBF), and signal-to-leakage-and-noise ratio maximizing (SLNR-MAX) beamforming (also known as transmit Wiener filter [115]).”
- An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems (2015, neutral): “22”