Performance of Conjugate and Zero-Forcing Beamforming in Large-Scale Antenna Systems

By Hong Yang, T. Marzetta. IEEE Journal on Selected Areas in Communications, 2013

718 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/00791cebda5472cff0618527f018524f85f98ae5

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Massive MIMO: An Introduction (2015, positive): “Under high SNR conditions, zeroforcing may perform significantly better than matched filtering and conjugate beamforming [18].”
Uplink Performance of Wideband Massive MIMO With One-Bit ADCs (2016, methodology): “Using results from random matrix theory, they were computed for MRC and ZFC in [34] and [35] for an IID Rayleigh fading channel hmk[ ] ∼ CN (0, p[ ]):”
Spatial Modulation for Generalized MIMO: Challenges, Opportunities, and Implementation (2014, background): “A viable solution to reduce the training overhead is the adoption of a cellular network architecture based on TDD, as discussed in [283], [284], and [286]–[288].”
Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems (2011, methodology): “An analysis related to the one presented here but for the downlink was given in [16].”
Massive MIMO for next generation wireless systems (2013, methodology): “We use a capacity lower bound from [8] that is extended to accommodate slow fading, near/far effects and power control and which accounts for receiver noise, channel estimation errors, the overhead of pilot transmission, and the imperfections of MRT beamforming.”
Limited Feedback Hybrid Precoding for Multi-User Millimeter Wave Systems (2014, methodology): “Thanks to the narrow beamforming and the sparse mmWave channels, the effective MIMO channel is expected to be well-conditioned [31], [32], which makes adopting a simple multi-user digital beamforming strategy like zero-forcing capable of achieving near-optimal performance [33], as will be shown in S”
An Overview of Massive MIMO: Benefits and Challenges (2014, background): “The performance of (R)ZF precoding for a single-cell massive MIMO system is analyzed in [33] when the number of antennas at the BS, , is much larger than the number of users, , and grows to infinity, i.e., and .”
Multipair Full-Duplex Relaying With Massive Arrays and Linear Processing (2014, neutral): “From (10), the received signal used for detecting x k [ i ] at the relay station can be written as | {z } | {z } where ˜ n R ,k [ i ] is considered as the effective noise, given by We can see that the “desired signal” and the “effective noise” in (25) are uncorrelated.”
Quantized Precoding for Massive MU-MIMO (2016, background): “Linear precoding, on the other hand, is an attractive low-complexity approach to massive MU-MIMO downlink precoding, which offers competitive performance to DPC for large antenna arrays [13], [14].”
A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead (2016, background): “Contributions to address these challenges have mainly focused on traditional performance measures (see for example [79] and [80]), and results on the energy efﬁciency of massive MIMO systems have started appearing only very recently.”