MIMO-OFDM Wireless Communications with MATLAB
By Y. Cho, Jaekwon Kim, W. Yang, C. Kang. 2010
1,929 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/66dd2f77d4934c8f503ed9b7864ac4891608e086
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In Electrical and Electronic Engineering
Citations in the corpus
- Pilot Reuse for Massive MIMO Transmission over Spatially Correlated Rayleigh Fading Channels (2015, background): “We consider the typical outdoor wireless propagation environments where the channel PAS can be modeled as the truncated Laplacian distribution [18], [31] given by (48), shown at the top of the next page, where σ k and θ k represent the AS and the mean AoA of the k th UT’s channel, respectively.”
- Key Generation From Wireless Channels: A Review (2016, background): “Channel estimation in orthogonal frequency-division multiplexing (OFDM) systems can get a noisy observation of CFR [60]–[63], which can be written as”
- Size Reduction of Self-Isolated MIMO Antenna System for 5G Mobile Phone Applications (2019, background): “THE fifth-generation (5G) communication technology can provide many advantages such as higher transmission rate and shorter latency over the current 4G system [1], [2].”
- A Tutorial on Near-Field XL-MIMO Communications Toward 6G (2023, neutral): “However, OFDM also faces many well-known challenges, e.g., high out-of-band (OOB) emission [220], sensitivity to carrier frequency offset (CFO) [178], [221], and high peak-to-average-power ratio (PAPR) [222], [223].”
- Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO (2015, methodology): “We adopt the widely used uniformly-spacing pilot placement with the spacing equal to the coherence bandwidth [21], which can reduce the correlation between different virtual angular domain channels, so that more diversity gain from the multiple sparse channels can be achieved.”