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1. A Survey on Multi-AP Coordination Approaches Over Emerging WLANs: Future Directions and Open Challenges

   https://doi.org/10.1109/COMST.2023.3344167  

   Verma, Shikhar; Rodrigues, Tiago_Koketsu; Kawamoto, Yuichi; Fouda, Mostafa M; Kato, Nei (December 2023, IEEE Communications Surveys & Tutorials)

   Recent advancements in wireless local area network (WLAN) technology include IEEE 802.11be and 802.11ay, often known as Wi-Fi 7 and WiGig, respectively. The goal of these developments is to provide Extremely High Throughput (EHT) and low latency to meet the demands of future applications like as 8K videos, augmented and virtual reality, the Internet of Things, telesurgery, and other developing technologies. IEEE 802.11be includes new features such as 320 MHz bandwidth, multi-link operation, Multi-user Multi-Input Multi-Output, orthogonal frequency-division multiple access, and Multiple-Access Point (multi-AP) coordination (MAP-Co) to achieve EHT. With the increase in the number of overlapping APs and inter-AP interference, researchers have focused on studying MAP-Co approaches for coordinated transmission in IEEE 802.11be, making MAP-Co a key feature of future WLANs. Moreover, similar issues may arise in EHF bands WLAN, particularly for standards beyond IEEE 802.11ay. This has prompted researchers to investigate the implementation of MAP-Co over future 802.11ay WLANs. Thus, in this article, we provide a comprehensive review of the state-of-the-art MAP-Co features and their shortcomings concerning emerging WLAN. Finally, we discuss several novel future directions and open challenges for MAP-Co. 

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2. QaSAL: QoS-aware State-Augmented Learnable Algorithms for Coexistence of 5G NR-U/Wi-Fi

   https://doi.org/10.1109/CISS64860.2025.10944641  

   Fasihi, Mohammad Reza; Mark, Brian L (March 2025, IEEE)

   With the increasing demand for wireless connectivity, ensuring the efficient coexistence of multiple radio access technologies in shared unlicensed spectrum has become an important issue. This paper focuses on optimizing Medium Access Control (MAC) parameters to enhance the coexistence of 5G New Radio in Unlicensed Spectrum (NR-U) and Wi-Fi networks operating in unlicensed spectrum with multiple priority classes of traffic that may have varying quality-of-service (QoS) requirements. In this context, we tackle the coexistence parameter management problem by introducing a QoS-aware State-Augmented Learnable (QaSAL) framework, designed to improve network performance under various traffic conditions. Our approach augments the state representation with constraint information, enabling dynamic policy adjustments to enforce QoS requirements effectively. Simulation results validate the effectiveness of QaSAL in managing NR-U and Wi-Fi coexistence, demonstrating improved channel access fairness while satisfying a latency constraint for high-priority traffic. 

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3. Machine Learning Enhanced Channel Selection for Unlicensed LTE

   https://doi.org/10.1109/DySPAN.2019.8935859  

   Tonnemacher, Matthew; Tarver, Chance; Cavallar, Joseph; Camp, Joseph (November 2019, 2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN))

   We propose a mechanism for unlicensed LTE channel selection that not only takes into account interference to and from Wi-Fi access points but also considers other LTE operators in the unlicensed band. By collecting channel utilization statistics and sharing this information periodically with other unlicensed LTE eNBs, each eNB can improve their channel selection given their limited knowledge of the full topology. While comparing our algorithm to existing solutions, we find that the similarity between sensed Wi-Fi occupation at neighboring eNBs greatly impacts the performance of channel selection algorithms. To achieve better performance across diverse scenarios, we expand on our statistical channel selection formulation to include reinforcement learning, thereby balancing the shared contextual information with historical performance. We simulate operation in the unlicensed band using our channel selection algorithm and show how Wi-Fi load and inter-cell interference estimation can jointly be used to select transmission channels for all small cells in the network. Our approaches lead to an increase in user-perceived throughput and spectral efficiency across the entire band when compared to the greedy channel selection. 

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4. Traffic Priority-Aware 5G NR-U/Wi-Fi Coexistence with Deep Reinforcement Learning

   https://doi.org/10.1109/VTC2024-Fall63153.2024.10757867  

   Fasihi, Mohammad Reza; Mark, Brian L (October 2024, IEEE)

   Coexistence of 5G new radio unlicensed (NR-U) and Wi-Fi is highly prone to the collisions among NR-U gNBs (5G base stations) and Wi-Fi APs (access points). To improve performance and fairness for both networks, various collision resolution mechanisms have been proposed to replace the simple listen-before-talk (LBT) scheme used in the current 5G standard. We address two gaps in the literature: first, the lack of a comprehensive performance comparison among the proposed collision resolution mechanisms and second, the impact of multiple traffic priority classes. Through extensive simulations, we compare the performance of several recently proposed collision resolution mechanisms for NR-U/Wi-Fi coexistence. We extend one of these mechanisms to handle multiple traffic priorities. We then develop a traffic-aware multi-objective deep reinforcement learning algorithm for the scenario of coexistence of high-priority traffic gNB user equipment (UE) with multiple lower-priority traffic UEs and Wi-Fi stations. The objective is to ensure low latency for high-priority gNB traffic while increasing the airtime fairness among the NR-U and Wi-Fi networks. Our simulation results show that the proposed algorithm lowers the channel access delay of high-priority traffic while improving the fairness among both networks. 

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5. Cnoidal Waves for Accessible High Power and Wide-Band Microresonator Frequency Combs

   Kholmyanskiy, Dora; Gat, Omri (March 2019, FRISNO15: FRench-Israel Symposium on Non-Linear & Quantum Optics)

   Pumped Kerr microresonators have recently emerged as a promising source of optical frequency combs. The production of octave-spanning spectrum by dispersive waves and consequent demonstration of carrier-envelope phase locking has paved the way toward a wide fi eld of comb applications. Nevertheless, there remain some obstacles before the goal of a simple off-the-shelf comb source is achieved. Current microcomb implementations rely on cavity solitons, and several of the present limitations of microcombs are tied to those of soliton waveforms. Cavity solitons exist only in a small red-detuned region of the pump parameters, where waveforms suffer from thermal instabilities. Furthermore, solitons are always obtained in the multistable regime, and therefore cannot be continuously connected to cw, so that elaborate, often non-deterministic, access protocols are needed to produce them. Another issue is that because solitons are accompanied by a strong pedestal, their comb power efficiency is low. 

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