On the capacity of MIMO broadcast channels with partial side information

By Masoud Sharif, Babak Hassibi. IEEE Transactions on Information Theory, 2005

1,278 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/66e8e7160cbb418b919a4873260fb001db865275

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In Electrical and Electronic Engineering

Citations in the corpus

MIMO broadcast channels with finite rate feedback (2006, background): “DMA. Because regularized ZF outperforms ZF at all SNR’s, we only consider regularized ZF systems. Random beamforming is an extension of opportunistic beamforming [34] to the multiple antenna downlink [7]. The transmitter randomly chooses M orthogonal beamforming vectors and transmits pilot symbols a”
A Survey on Multiple-Antenna Techniques for Physical Layer Security (2017, background): “It is generally known that beamformer and jamming signal designs in multiple-antenna systems depend on the availability of channel state information (CSI) at the transmitter [46], [47].”
Joint Spatial Division and Multiplexing—The Large-Scale Array Regime (2012, background): “5Unlike channel-based opportunistic user selection, [28]–[31], that requires to collect CSIT from many users and then select a subset of users with quasiorthogonal channel vectors.”
An overview of limited feedback in wireless communication systems (2008, background): “The broad second category is a multiuser version of the opportunistic beamforming approach mentioned earlier (as initially discussed in [291]).”
Pilot Contamination and Precoding in Multi-Cell TDD Systems (2009, methodology): “In [3], [5]–[8], [27] such a setting is considered.”
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming (2006, background): “The proof is based on the observation that is lower bounded by the sum rate of the orthogonal random beamforming (RBF) strategy proposed in [ 14 ], which achieves the same asymptotic throughput in (5) as DPC.”
On the Performance of Non-Orthogonal Multiple Access in 5G Systems with Randomly Deployed Users (2014, methodology): “This observation can be used to remove the constants in the integral, and is written as follows: (18) In the above equation, each term of the sum is an exponential function with a non-zero exponent, i.e. .”
Optimal Resource Allocation in Coordinated Multi-Cell Systems (2013, background): “Such scheduling updates can be performed locally (if users report the SINR of their preferable beam, similar to what is done in random beamforming [238]) and the system can iterate between updating scheduling and updating beamforming vectors for the currently active users.”
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].”
Multi-Antenna Downlink Channels with Limited Feedback and User Selection (2007, methodology): “In order to scale the sum rate at the optimal log log K rate, the transmitter must also have channel quality information (CQI), based on SINR, to exploit selection diversity among users as well as control the effect of quantization error in the CDI.”