On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming

By Taesang Yoo, Andrea J. Goldsmith. IEEE Journal on Selected Areas in Communications, 2006

2,125 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/a2a32bfd16d5982e8b86d569ae78df34dc368b08

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Millimeter-Wave Massive MIMO Communication for Future Wireless Systems: A Survey (2018, methodology): “Beyond the basic schedulers such as the maximum rate, round robin (RR) and proportionally fair (PF) schedulers, more efficient scheduling algorithms such as the DPC and the greedy user selection method based on ZF beamforming and DPC (gZF-DP) [132] have been proposed and developed, and more recently”
MIMO Broadcast Channels With Finite-Rate Feedback (2006, background): “channels with a very large number of mobiles [7] [ 8 ] [9], we consider systems in which the number of”
Outage Constrained Robust Transmit Optimization for Multiuser MISO Downlinks: Tractable Approximations by Conic Optimization (2011, background): “INTRODUCTION In multiuser multi-antenna downlink channels, linear prec oding has been recognized as a practically powerful technique that is capable of leveraging quality of service (QoS) and improving system throughput [3], [4].”
Capacity Enhancement Using an Interference Limited Area for Device-to-Device Uplink Underlaying Cellular Networks (2011, methodology): “However, the dotted line supports fairness using SUS with round robin scheduling (RRS) [14].”
A Minorization-Maximization Method for Optimizing Sum Rate in the Downlink of Non-Orthogonal Multiple Access Systems (2015, background): “[28] is lost and we see a downward trend in achievable data rat es.”
Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming (2018, background): “, MMSE and zero-forcing (ZF) based beamforming [23], [27].”
Optimal Resource Allocation in Coordinated Multi-Cell Systems (2013, background): “An important special case is so-called zero-forcing beamforming9 [23, 46, 85, 115, 252, 297, 305], where the beamforming vectors are selected to cause zero interference to nonintended users.”
Caching in the Sky: Proactive Deployment of Cache-Enabled Unmanned Aerial Vehicles for Optimized Quality-of-Experience (2016, methodology): “Then, the RRHs in each cluster use ZFBF to improve the users’ rates.”
Joint Spatial Division and Multiplexing: Opportunistic Beamforming, User Grouping and Simplified Downlink Scheduling (2014, background): “In the regime of large number of users and fixed number of antennas, the scaling law of the sum capacity with opportunistic user selection has been widely investigated for uncorrelated channels under random beamforming [18] and zero-forcing beamforming [19].”
A Deep Learning Framework for Optimization of MISO Downlink Beamforming (2019, methodology): “…ratio (SINR) balancing problem (also known as interference balancing problem) under a total power constraint [2–4], as a power minimization problem under quality of service (QoS) constraints [5–8], or as a sum rate maximization problem under a total power constraint [2, 9–11].”
Rate-splitting multiple access for downlink communication systems: bridging, generalizing, and outperforming SDMA and NOMA (2017, methodology): “, either in closed form or optimized using optimization methods, though suboptimal, is often very useful when users experience relatively similar channel strengths or long-term signal-to-noise ratio (SNR) and have semi-orthogonal to orthogonal channels [11].”
The Multicell Multiuser MIMO Uplink with Very Large Antenna Arrays and a Finite-Dimensional Channel (2013, background): “Such systems can offer a spatial multiplexing gain even if the users have only a single antenna each [2]–[4].”
Satellite Communications in the New Space Era: A Survey and Future Challenges (2020, background): “In particular, [209], [210] they randomly chose a user as a reference and then deﬁne the remaining group members associated with that user, while [130] selects the ﬁrst user per group according to the semi-orthogonality criteria originally proposed in [200].”
Energy-Efficient Design of MIMO Heterogeneous Networks With Wireless Backhaul (2015, background): “In fact, under lin ear precoding, the number of scheduled UEs should not exceed the number of an tennas, in order for the achievable rate not to be significantly degrade d [55]–[57].”
Shifting the MIMO Paradigm (2007, methodology): “In [25], the users are equipped with only one receive antenna, and ZFBF is performed at the transmitter.”