WiFi has become a term that a majority of people on earth today are familiar with. The one that has progressed towards being the preferred wireless technology enabling the explosion of wirelessly connected devices.
According to the Telecom Ministry data, India’s internet consumption increased by 13% during the lockdown. This rise in demand signals a change based on the increased adoption of Work from Home and heightened consumption of the OTT content. Additionally, this increase in demand also captures how data demand from regular households upsurged in comparison to commercial areas.
While there is a global effort to get ubiquitous wireless connectivity for all, even in its current state, it has a great effect on how our society works, plays, and lives. Perhaps you’re the person who has a relative in a different country and is using Wi-Fi to make a fast, cost-effective video call to stay in touch. Or maybe you’re a doctor in a hospital who uses Wi-Fi on your laptop to access
Enterprise Wireless Local Area Network (WLAN) Market 2021 Global Leading Companies Analysis, Revenue, Trends and Forecasts 2027
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Wireless Networking Market to See Booming Growth | Microchip Technology, Intel, Qualcomm
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The Myiro-1 handheld spectrophotometre.
Techkon USA (Danvers, MA), a leader in high-precision colour-measurement solutions for the global print and packaging industries, has partnered with Konica Minolta USA (Ramsey, NJ) to promote and distribute the Myiro-1, a highly accurate handheld spectrophotometre designed for colour management and ICC profiling applications, to the North American market. “From its initial product inception, Myiro-1 was designed to be the most accurate and repeatable, low cost, spectrophotometre to meet the high-end colour profiling needs of the photography, commercial print, packaging and signage industries,” said the companies. “Up until now, these markets have long been served by products that have under-delivered on measurement consistency and overall product reliability. Myiro-1 promises to change the current market perception of low-cost spectrophotometres and profiling with its unrivaled measurement accuracy, repeatability, build quality and produ
Publication Details
Y. Luo & K. Chin, Learning to Bond in Dense WLANs with Random Traffic Demands, IEEE Transactions on Vehicular Technology, vol. 69, (10) pp. 11868-11879, 2020.
Abstract
© 1967-2012 IEEE. The Access Points (APs) in a Wireless Local Area Network (WLAN) must be assigned one or more channels to meet traffic demands from users. To date, prior works on channel assignment assume APs have a fixed traffic demand, meaning they do not consider or adapt to spatio-temporal changes in traffic demands. To this end, we leverage Deep Reinforcement Learning (DRL), where we equip APs with a DRL-based channel assignment solution, to maximize the average number of slots in which an AP has sufficient bandwidth to meet user demands. Our APs learn from their historical traffic loads and assign themselves partially overlapping channels with minimal interference. Simulation results show that our DRL solution leads to APs satisfying 60% more user demands as compared to fixed and greedy