2021
DOI: 10.1109/twc.2020.3022297
|View full text |Cite
|
Sign up to set email alerts
|

Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
220
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
3
2
1

Relationship

1
5

Authors

Journals

citations
Cited by 262 publications
(233 citation statements)
references
References 43 publications
1
220
0
Order By: Relevance
“…For comparison, we consider three benchmark schemes: 1) the fast-timescale scheme which employs the I-CSI and adopts the alternating optimization (AO) algorithm in [26] under shortterm rate constraints of the users (with the same rate value as that for the case of long-term rate constraint for each user), 2) the TTS scheme in [31], where the weighted sum-rate maximization problem (the user weights are set to 1) is solved for IRS phase-shift optimization and the active beamforming design problem in each time slot (with fixed IRS phase shifts) is solved by transforming it into an SOCP problem as in [44] that is then solved by CVX [33] (this scheme is abbreviated as TTS-WSRMax in the following), and 3) the random phase-shift scheme where the phase shifts at the IRS are randomly generated at each time slot for introducing artificial channel fading to enhance the multiuser channel diversity, while the active beamforming is designed by adopting the same method as in the TTS-WSRMax scheme with fixed IRS phase shifts.…”
Section: Simulation Resultsmentioning
confidence: 99%
See 4 more Smart Citations
“…For comparison, we consider three benchmark schemes: 1) the fast-timescale scheme which employs the I-CSI and adopts the alternating optimization (AO) algorithm in [26] under shortterm rate constraints of the users (with the same rate value as that for the case of long-term rate constraint for each user), 2) the TTS scheme in [31], where the weighted sum-rate maximization problem (the user weights are set to 1) is solved for IRS phase-shift optimization and the active beamforming design problem in each time slot (with fixed IRS phase shifts) is solved by transforming it into an SOCP problem as in [44] that is then solved by CVX [33] (this scheme is abbreviated as TTS-WSRMax in the following), and 3) the random phase-shift scheme where the phase shifts at the IRS are randomly generated at each time slot for introducing artificial channel fading to enhance the multiuser channel diversity, while the active beamforming is designed by adopting the same method as in the TTS-WSRMax scheme with fixed IRS phase shifts.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…, denoting the reflection amplitudes and phase shifts, respectively. For simplicity, we assume a n = 1, ∀n ∈ N to maximize the signal reflection [31]. n k denotes the independent and identically distributed (i.i.d.)…”
Section: A System Modelmentioning
confidence: 99%
See 3 more Smart Citations