Channel Models for Fixed Wireless Applications
By Vinko Erceg, K. Hari, Mike J. Smith, Daniel S. Baum, K. Sheikh, C. Tappenden, J. Costa, C. Bushue, A. Sarajedini, R. Schwartz and 1 more. 2001
918 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/0020fa7ad9633e07cc99ce75aed4870eb5e5c02b
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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Robert W. Heath
- David Gesbert
- Andreas F. Molisch
- Arogyaswami Paulraj
- Emil Björnson
- Merouane Debbah
- Mohamed-Slim Alouini
- Paul de Kerret
Citations in the corpus
- Survey of Channel and Radio Propagation Models for Wireless MIMO Systems (2007, methodology): “16a standard include a pathloss model, a model for the narrowband Ricean Kfactor, as well as an antenna gain reduction factor model (see [32] for more details).”
- Peak-To-Average Power Ratio Reduction in OFDM Systems: A Survey And Taxonomy (2013, methodology): “The Stanford university interim (SUI)-1 fading channel model [74] is used and additive white Gaussian noise (AWGN) is added.”
- An interim channel model for beyond-3G systems: extending the 3GPP spatial channel model (SCM) (2005, unknown): “16 standard for fixed wireless access [19].”
- A Survey of Wireless Path Loss Prediction and Coverage Mapping Methods (2013, background): “The authors highlight the best of the three, which turns out to be the ECC-33 model proposed in [29].”
- A fourth-generation MIMO-OFDM broadband wireless system: design, performance, and field trial results (2002, background): “The XPD values were found to decrease with increasing distance [6].”
- Comparison of empirical propagation path loss models for fixed wireless access systems (2005, methodology): “The correction factors for the operating frequency and for the CPE antenna height for the model are [2],”
- Machine Learning in the Air (2019, background): “16a,e [47], or the more advanced geometry-based COST 2100 stochastic channel model [48].”
- A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges (2022, methodology): “COST-231 Walfish-Ikegami model referred to COSTWI [57], is a hybrid of the Walfish and Ikegami models that enhance path loss prediction by taking into considera-”
- Adaptive modulation and MIMO coding for broadband wireless data networks (2002, background): “3 shows the time-varying frequency response of a channel model taken from [8] over 2 MHz bandwidth.”