On-Demand Channel Bonding in Heterogeneous WLANs: A Multi-Agent Deep Reinforcement Learning Approach
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Xiangming Wen | Zhaoming Lu | Hao Huang | Zhiqun Hu | Hang Qi | X. Wen | Zhaoming Lu | Zhiqun Hu | Hao Huang | H. Qi
[1] Yousri Daldoul,et al. IEEE 802.11ac: Effect of channel bonding on spectrum utilization in dense environments , 2017, 2017 IEEE International Conference on Communications (ICC).
[2] Yu Cheng,et al. Performance Analysis of Opportunistic Channel Bonding in Multi-Channel WLANs , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).
[3] Evgeny Khorov,et al. A Tutorial on IEEE 802.11ax High Efficiency WLANs , 2019, IEEE Communications Surveys & Tutorials.
[4] Peter Dayan,et al. Q-learning , 1992, Machine Learning.
[5] MoscibrodaThomas,et al. A case for adapting channel width in wireless networks , 2008 .
[6] Tho Le-Ngoc,et al. Self-organizing channel assignment for high density 802.11 WLANs , 2014, 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC).
[7] Yunnan Wu,et al. Load-aware spectrum distribution in Wireless LANs , 2008, 2008 IEEE International Conference on Network Protocols.
[8] Boris Bellalta,et al. Analysis of Dynamic Channel Bonding in Dense Networks of WLANs , 2015, IEEE Transactions on Mobile Computing.
[9] Ben Poole,et al. Categorical Reparametrization with Gumble-Softmax , 2017, ICLR 2017.
[10] Srikanth V. Krishnamurthy,et al. Auto-configuration of 802.11n WLANs , 2010, CoNEXT.
[11] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 2005, IEEE Transactions on Neural Networks.
[12] Michelle X. Gong,et al. Channel Bounding and MAC Protection Mechanisms for 802.11ac , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.
[13] Nada Golmie,et al. A Throughput Study for Channel Bonding in IEEE 802.11ac Networks , 2017, IEEE Communications Letters.
[14] Nada Golmie,et al. Dynamic Channel Bonding Algorithm for Densely Deployed 802.11ac Networks , 2019, IEEE Transactions on Communications.
[15] Matteo Cesana,et al. Understanding the WiFi usage of university students , 2016, 2016 International Wireless Communications and Mobile Computing Conference (IWCMC).
[16] A. Stelter. Channel width selection scheme for better utilisation of WLAN bandwidth , 2014 .
[17] Yuanyuan Yang,et al. Distributed channel assignment algorithms for 802.11n WLANs with heterogeneous clients , 2014, J. Parallel Distributed Comput..
[18] Zhu Han,et al. A Renewal Theory Based Analytical Model for Multi-Channel Random Access in IEEE 802.11ac/ax , 2019, IEEE Transactions on Mobile Computing.
[19] Félix Hernández-Campos,et al. Spatio-temporal modeling of traffic workload in a campus WLAN , 2006, WICON '06.
[20] Paramvir Bahl,et al. A case for adapting channel width in wireless networks , 2008, SIGCOMM '08.
[21] Jaume Barceló,et al. On the Interactions Between Multiple Overlapping WLANs Using Channel Bonding , 2014, IEEE Transactions on Vehicular Technology.
[22] Kang G. Shin,et al. Post-CCA and Reinforcement Learning Based Bandwidth Adaptation in 802.11ac Networks , 2018, IEEE Transactions on Mobile Computing.
[23] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[24] John N. Tsitsiklis,et al. Analysis of temporal-difference learning with function approximation , 1996, NIPS 1996.
[25] Dan Rubenstein,et al. Distributed self-stabilizing placement of replicated resources in emerging networks , 2005, IEEE/ACM Transactions on Networking.
[26] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[27] William A. Arbaugh,et al. Weighted coloring based channel assignment for WLANs , 2005, MOCO.
[28] Louiza Bouallouche-Medjkoune,et al. Performance study and enhancement of multichannel access methods in the future generation VHT WLAN , 2018, Future Gener. Comput. Syst..
[29] Kevin C. Almeroth,et al. The impact of channel bonding on 802.11n network management , 2011, CoNEXT '11.
[30] Yi Wu,et al. Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments , 2017, NIPS.
[31] Zhu Han,et al. Enabling efficient multi-channel bonding for IEEE 802.11ac WLANs , 2017, 2017 IEEE International Conference on Communications (ICC).
[32] Zhisheng Niu,et al. DeepNap: Data-Driven Base Station Sleeping Operations Through Deep Reinforcement Learning , 2018, IEEE Internet of Things Journal.
[33] Wei Zheng,et al. Artificial Intelligence-Based Handoff Management for Dense WLANs: A Deep Reinforcement Learning Approach , 2019, IEEE Access.
[34] Xu Chen,et al. To Bond or Not to Bond: An Optimal Channel Allocation Algorithm for Flexible Dynamic Channel Bonding in WLANs , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).
[35] Allen B. MacKenzie,et al. Adaptive channel bonding in wireless LANs under demand uncertainty , 2017, 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).
[36] Zhaoxing Li,et al. Modeling the TXOP Sharing Mechanism of IEEE 802.11ac Enhanced Distributed Channel Access in Non-Saturated Conditions , 2015, IEEE Communications Letters.
[37] Ranveer Chandra,et al. FLUID: Improving Throughputs in Enterprise Wireless LANs through Flexible Channelization , 2011, IEEE Transactions on Mobile Computing.
[38] Boris Bellalta,et al. To overlap or not to overlap: Enabling Channel Bonding in High Density WLANs , 2018, Comput. Networks.
[39] Lingwei Xu,et al. BP neural network-based ABEP performance prediction for mobile Internet of Things communication systems , 2019, Neural Computing and Applications.
[40] Boris Bellalta,et al. Channel Bonding in Short-Range WLANs , 2014 .
[41] Boris Bellalta,et al. Dynamic Channel Bonding in Spatially Distributed High-Density WLANs , 2018, IEEE Transactions on Mobile Computing.
[42] Ying-Chang Liang,et al. Applications of Deep Reinforcement Learning in Communications and Networking: A Survey , 2018, IEEE Communications Surveys & Tutorials.