[{"status":"public","file":[{"relation":"main_file","content_type":"application/pdf","file_id":"33855","file_name":"preprint.pdf","access_level":"open_access","file_size":2521656,"creator":"stschn","date_created":"2022-10-20T16:41:10Z","date_updated":"2022-10-20T16:41:10Z"}],"abstract":[{"lang":"eng","text":"Macrodiversity is a key technique to increase the capacity of mobile networks. It can be realized using coordinated multipoint (CoMP), simultaneously connecting users to multiple overlapping cells. Selecting which users to serve by how many and which cells is NP-hard but needs to happen continuously in real time as users move and channel state changes. Existing approaches often require strict assumptions about or perfect knowledge of the underlying radio system, its resource allocation scheme, or user movements, none of which is readily available in practice.\r\n\r\nInstead, we propose three novel self-learning and self-adapting approaches using model-free deep reinforcement learning (DRL): DeepCoMP, DD-CoMP, and D3-CoMP. DeepCoMP leverages central observations and control of all users to select cells almost optimally. DD-CoMP and D3-CoMP use multi-agent DRL, which allows distributed, robust, and highly scalable coordination. All three approaches learn from experience and self-adapt to varying scenarios, reaching 2x higher Quality of Experience than other approaches. They have very few built-in assumptions and do not need prior system knowledge, making them more robust to change and better applicable in practice than existing approaches."}],"type":"working_paper","language":[{"iso":"eng"}],"file_date_updated":"2022-10-20T16:41:10Z","keyword":["mobility management","coordinated multipoint","CoMP","cell selection","resource management","reinforcement learning","multi agent","MARL","self-learning","self-adaptation","QoE"],"ddc":["004"],"department":[{"_id":"75"}],"user_id":"477","_id":"33854","project":[{"name":"SFB 901 - C: SFB 901 - Project Area C","_id":"4"},{"name":"SFB 901 - C4: SFB 901 - Subproject C4","_id":"16"},{"_id":"1","name":"SFB 901: SFB 901"}],"citation":{"apa":"Schneider, S. B., Karl, H., Khalili, R., &#38; Hecker, A. (2021). <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>.","short":"S.B. Schneider, H. Karl, R. Khalili, A. Hecker, DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning, 2021.","mla":"Schneider, Stefan Balthasar, et al. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>. 2021.","bibtex":"@book{Schneider_Karl_Khalili_Hecker_2021, title={DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning}, author={Schneider, Stefan Balthasar and Karl, Holger and Khalili, Ramin and Hecker, Artur}, year={2021} }","ama":"Schneider SB, Karl H, Khalili R, Hecker A. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>.; 2021.","chicago":"Schneider, Stefan Balthasar, Holger Karl, Ramin Khalili, and Artur Hecker. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>, 2021.","ieee":"S. B. Schneider, H. Karl, R. Khalili, and A. Hecker, <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>. 2021."},"year":"2021","has_accepted_license":"1","title":"DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning","author":[{"id":"35343","full_name":"Schneider, Stefan Balthasar","last_name":"Schneider","orcid":"0000-0001-8210-4011","first_name":"Stefan Balthasar"},{"last_name":"Karl","id":"126","full_name":"Karl, Holger","first_name":"Holger"},{"first_name":"Ramin","full_name":"Khalili, Ramin","last_name":"Khalili"},{"full_name":"Hecker, Artur","last_name":"Hecker","first_name":"Artur"}],"date_created":"2022-10-20T16:44:19Z","oa":"1","date_updated":"2022-11-18T09:59:27Z"},{"title":"A Novel Similarity Measure for Positioning Cellular Phones by a Comparison With a Database of Signal Power Levels","date_created":"2019-07-12T05:28:29Z","year":"2007","issue":"1","language":[{"iso":"eng"}],"keyword":["cellular phone positioning","cellular radio","measured signal power levels","mobile handsets","mobility management (mobile radio)"],"abstract":[{"lang":"eng","text":"In this paper, we propose a novel similarity measure to be used for localizing mobile terminals by comparing measured signal power levels with a database of predictions. The proposed measure provides the possibility to incorporate inherent information about signal power level measurements requested by the serving base station but not reported by the mobile terminal. Increased positioning accuracy was observed both in simulations and with real field data"}],"publication":"IEEE Transactions on Vehicular Technology","doi":"10.1109/TVT.2006.889563","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2007/HaPe07.pdf","open_access":"1"}],"volume":56,"author":[{"last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242","first_name":"Reinhold"},{"first_name":"Sven","last_name":"Peschke","full_name":"Peschke, Sven"}],"oa":"1","date_updated":"2022-01-06T06:51:08Z","intvolume":"        56","page":"368-372","citation":{"ama":"Haeb-Umbach R, Peschke S. A Novel Similarity Measure for Positioning Cellular Phones by a Comparison With a Database of Signal Power Levels. <i>IEEE Transactions on Vehicular Technology</i>. 2007;56(1):368-372. doi:<a href=\"https://doi.org/10.1109/TVT.2006.889563\">10.1109/TVT.2006.889563</a>","ieee":"R. Haeb-Umbach and S. Peschke, “A Novel Similarity Measure for Positioning Cellular Phones by a Comparison With a Database of Signal Power Levels,” <i>IEEE Transactions on Vehicular Technology</i>, vol. 56, no. 1, pp. 368–372, 2007.","chicago":"Haeb-Umbach, Reinhold, and Sven Peschke. “A Novel Similarity Measure for Positioning Cellular Phones by a Comparison With a Database of Signal Power Levels.” <i>IEEE Transactions on Vehicular Technology</i> 56, no. 1 (2007): 368–72. <a href=\"https://doi.org/10.1109/TVT.2006.889563\">https://doi.org/10.1109/TVT.2006.889563</a>.","apa":"Haeb-Umbach, R., &#38; Peschke, S. (2007). A Novel Similarity Measure for Positioning Cellular Phones by a Comparison With a Database of Signal Power Levels. <i>IEEE Transactions on Vehicular Technology</i>, <i>56</i>(1), 368–372. <a href=\"https://doi.org/10.1109/TVT.2006.889563\">https://doi.org/10.1109/TVT.2006.889563</a>","short":"R. Haeb-Umbach, S. Peschke, IEEE Transactions on Vehicular Technology 56 (2007) 368–372.","mla":"Haeb-Umbach, Reinhold, and Sven Peschke. “A Novel Similarity Measure for Positioning Cellular Phones by a Comparison With a Database of Signal Power Levels.” <i>IEEE Transactions on Vehicular Technology</i>, vol. 56, no. 1, 2007, pp. 368–72, doi:<a href=\"https://doi.org/10.1109/TVT.2006.889563\">10.1109/TVT.2006.889563</a>.","bibtex":"@article{Haeb-Umbach_Peschke_2007, title={A Novel Similarity Measure for Positioning Cellular Phones by a Comparison With a Database of Signal Power Levels}, volume={56}, DOI={<a href=\"https://doi.org/10.1109/TVT.2006.889563\">10.1109/TVT.2006.889563</a>}, number={1}, journal={IEEE Transactions on Vehicular Technology}, author={Haeb-Umbach, Reinhold and Peschke, Sven}, year={2007}, pages={368–372} }"},"department":[{"_id":"54"}],"user_id":"44006","_id":"11799","status":"public","type":"journal_article"}]