Quasi axis-symmetric integrated lens antennas: Design rules and experimental/manufacturing trade-offs at millimeter-wave frequencies

2005 ◽  
Vol 48 (1) ◽  
pp. 20-29 ◽  
Author(s):  
Ronan Sauleau ◽  
Barbara Barès
2019 ◽  
Vol 48 (1) ◽  
pp. 84-102
Author(s):  
Amard Afzalian ◽  
Hossein Miar‐Naimi ◽  
Massoud Dousti

2019 ◽  
Vol 19 (2) ◽  
pp. 33-58 ◽  
Author(s):  
Han Yan ◽  
Sridhar Ramesh ◽  
Timothy Gallagher ◽  
Curtis Ling ◽  
Danijela Cabric
Keyword(s):  

2013 ◽  
Vol 176 (5-6) ◽  
pp. 684-690 ◽  
Author(s):  
Tom Nitta ◽  
Kenichi Karatsu ◽  
Yutaro Sekimoto ◽  
Masato Naruse ◽  
Masakazu Sekine ◽  
...  

2017 ◽  
Vol 65 (12) ◽  
pp. 6453-6473 ◽  
Author(s):  
Marc Imbert ◽  
Jordi Romeu ◽  
Mariano Baquero-Escudero ◽  
Maria-Teresa Martinez-Ingles ◽  
Jose-Maria Molina-Garcia-Pardo ◽  
...  

2001 ◽  
Vol 33 (11) ◽  
pp. 949-962 ◽  
Author(s):  
LESLIE OLIN MORGAN ◽  
RICHARD L. DANIELS ◽  
PANOS KOUVELIS

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1599
Author(s):  
Alexander Marinšek ◽  
Daan Delabie ◽  
Lieven De Strycker ◽  
Liesbet Van der Perre

Emerging applications in fields such as extended reality require both a high throughput and low latency. The millimeter-wave (mmWave) spectrum is considered because of the potential in the large available bandwidth. The present work studies mmWave Wi-Fi physical layer latency management mechanisms, a key factor in providing low-latency communications for time-critical applications. We calculate physical layer latency in an ideal scenario and simulate it using a tailor-made simulation framework, based on the IEEE 802.11ad standard. Assessing data reception quality over a noisy channel yielded latency’s dependency on transmission parameters, channel noise, and digital baseband tuning. Latency in function of the modulation and coding scheme was found to span 0.28–2.71 ms in the ideal scenario, whereas simulation results also revealed its tight bond with the demapping algorithm and the number of low-density parity-check decoder iterations. The findings yielded tuning parameter combinations for reaching Pareto optimality either by constraining the bit error rate and optimizing latency or the other way around. Our assessment shows that trade-offs can and have to be made to provide sufficiently reliable low-latency communication. In good channel conditions, one may benefit from both the very high throughput and low latency; yet, in more adverse situations, lower modulation orders and additional coding overhead are a necessity.


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