@inproceedings{
 title = {Radio Environment Maps for 5G Cognitive Radio Network},
 type = {inproceedings},
 year = {2019},
 keywords = {5G,Cognitive Radio,Network Function Virtualization,REM,SDN},
 id = {11b55a91-0bf4-3271-ad27-d52ada5f5939},
 created = {2020-02-29T16:57:44.873Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.950Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Kakalou2019},
 private_publication = {false},
 abstract = {Radio Environment Maps (REMs) have been introduced as a powerful tool in Cognitive Radio Networks to manage inter-transmitter interference. In the evolution of 5G heterogeneous ecosystem REMs are forced to be transformed to a more powerful tool hosting the diverse needs of an immense network. This paper reviews REMs and proposes an enhanced REM architecture for integration in the 5G network.},
 bibtype = {inproceedings},
 author = {Kakalou, Ioanna and Psannis, Kostas and Goudos, Sotirios K. and Yioultsis, Traianos V. and Kantartzis, Nikolaos V. and Ishibashi, Yutaka},
 doi = {10.1109/MOCAST.2019.8741554},
 booktitle = {2019 8th International Conference on Modern Circuits and Systems Technologies, MOCAST 2019}
}

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