Sum power iterative water-filling for multi-antenna Gaussian broadcast channels

By Nihar Jindal, Syed Ali Jafar, Sriram Vishwanath, Andrea J. Goldsmith. Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002., 2002

540 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8d9f7cb8906e7f9774eb738be303f903eccdfdbf

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

On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming (2006, methodology): “, linearly with the number of users [27].”
Capacity limits of MIMO channels (2003, methodology): “An algorithm based on the iterative waterfilling algorithm [86] that finds the sum rate optimal covariances is given in [43].”
An introduction to convex optimization for communications and signal processing (2006, background): “This fact has been exploited in [18] and [19] for efficient computation of the sum capacity.”
On the duality of Gaussian multiple-access and broadcast channels (2002, methodology): “In [8], duality is extended to multiple-antenna Gaussian channels and in [8], [9] this duality has been used to find the sum capacity of the multiple-antenna BC. Duality also greatly simplifies numerical computation of the multiple-antenna BC sum rate capacity and achievable region [10], [11].”
Massive MIMO Performance Evaluation Based on Measured Propagation Data (2014, methodology): “This can be done using the sumpower iterative water-filling algorithm presented in [28].”
Learning to Cooperate in Decentralized Wireless Networks (2018, result): “While the literature on power control is abundant including for decentralized cases [3] [4], and moreover deep learning approaches [5] [6], this research departs in significant ways from past work in that we consider that each decision making agent (i.”
Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design (2008, methodology): “DPC sum-capacity reference bounds are produced using A LGORITHM 2 from [19].”