2022
DOI: 10.48550/arxiv.2210.05928
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Nonlocal Reconfigurable Intelligent Surfaces for Wireless Communication: Modeling and Physical Layer Aspects

Abstract: Delivering wireless ultrahigh-speed access at wider coverage is becoming considerably challenging due to the prohibitive investment costs per user and the necessary shift to range-limited millimeter-wave (mmWave) transmissions. Reconfigurable intelligent surfaces (RIS) are expected to extend the reach of mmWave and TeraHz signals more cost-effectively in situations where fiber backhaul and fronthaul are not accessible or infrastructure densification is costly. This paper investigates some challenges facing thi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
0
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(5 citation statements)
references
References 32 publications
0
0
0
Order By: Relevance
“…wherein γ 0 is a regularization parameter to be tuned. By vectorizing the cost function in (9) and defining C ≜ (B T ⊗ A) ∈ C M N ×K 2 it follows that: 3 Without loss of generality, α is taken to be real valued since any phase can be included in the precoding matrix F. 4 The constraint 7e is needed if an amplifier is introduced within the port connection for better gain [37].…”
Section: Constrained Optimization Of Symmetric Permutation Matrixmentioning
confidence: 99%
See 4 more Smart Citations
“…wherein γ 0 is a regularization parameter to be tuned. By vectorizing the cost function in (9) and defining C ≜ (B T ⊗ A) ∈ C M N ×K 2 it follows that: 3 Without loss of generality, α is taken to be real valued since any phase can be included in the precoding matrix F. 4 The constraint 7e is needed if an amplifier is introduced within the port connection for better gain [37].…”
Section: Constrained Optimization Of Symmetric Permutation Matrixmentioning
confidence: 99%
“…This appreciably reduces the incurred signaling overhead and operational complexity for RIS-aided systems. In fact, the control overhead scales only logarithmically with the RedRIS size [37] in contrast to the reflective RIS where the control overhead scales linearly with the number of phase shifters [40], [41] and even more so in BD-RIS systems. Although the lens-type RedRIS is a passive network element, it can be integrated with two-port amplifiers contrarily to the reflective RIS which would require reflection-mode amplifiers where stability becomes a major issue [37], [42].…”
Section: Introduction a Backgroundmentioning
confidence: 99%
See 3 more Smart Citations