Autoregressive modeling for fading channel simulation
By Kareem E. Baddour, Norman Charles Beaulieu. IEEE Transactions on Wireless Communications, 2005
648 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/a9499141c73aaffef7db7516f92bd94670da04bf
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
- Gary Boudreau
- Kothapalli Venkata Srinivas
- Hussein A. Ammar
- Robert W. Heath
- Shahram ShahbazPanahi
- Kien T. Truong
- Raviraj S. Adve
- D. J. Love
In Electrical and Electronic Engineering
- Gary Boudreau
- Shahram ShahbazPanahi
- Raviraj S. Adve
- Kothapalli Venkata Srinivas
- Hussein A. Ammar
- Robert W. Heath
- Kien T. Truong
- Ahmed Alkhateeb
Citations in the corpus
- Effects of channel aging in massive MIMO systems (2013, methodology): “channel is completely characterized by the second order statistics of the channel, in particular the autocorrelation function of the channel, which is generally a function of propagation geometry, velocity of the user, and antenna characteristics [18].”
- User-Centric Cell-Free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions (2021, methodology): “In this context, exploitation of angle reciprocity in FDD systems may be less effective in millimeter wave communication because the uplink and downlink carrier frequencies could be relatively far from each other due to the availability of large bandwidth.”