dc.contributor.author | Vijayandran, Luxmiram | |
dc.contributor.author | Byun, Sang-Soon | |
dc.contributor.author | Øien, Geir Egil | |
dc.contributor.author | Ekman, Torbjörn | |
dc.date.accessioned | 2019-10-15T08:10:52Z | |
dc.date.available | 2019-10-15T08:10:52Z | |
dc.date.created | 2013-01-14T21:00:15Z | |
dc.date.issued | 2012 | |
dc.identifier.issn | 1687-1472 | |
dc.identifier.uri | http://hdl.handle.net/11250/2622149 | |
dc.description.abstract | We revisit the widely investigated problem of maximizing the centralized sum-rate capacity in a cognitive radio network. We consider an interference-limited multi-user multi-channel environment, with a transmit sum-power constraint over all channels as well as an aggregate average interference constraint towards multiple primary users. Until very recently only sub-optimal algorithms were proposed due to the inherent non-convexity of the problem. Yet, the problem at hand has been neglected in the large-scale setting (i.e., number of nodes and channels) as usually encountered in practical scenarios. To tackle this issue, we first propose an exact mathematical adaptation of the well-known successive convex geometric programming with condensation approximations (SCVX) to better cope with large systems while keeping the convergence proof intact. Alternatively, we also propose a novel efficient low-complexity heuristic algorithm, ELCI. ELCI is an iterative approach, where the constraints are handled alternately based on the special property of the optimal solution, with a particular power update formulation based on the KKT conditions of the problem. In order to demonstrate ELCI’s efficiency we compare it to two state-of-the-art algorithms, SCVX, and the recently proposed global optimum approach, MARL. The salient highlight of ELCI is the relatively fast and very good sub-optimal performance in large-scale CR systems. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | SpringerOpen | nb_NO |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Increasing sum-rate in large-scale cognitive radio networks by centralized power and spectrum allocation | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.source.volume | 2012 | nb_NO |
dc.source.journal | EURASIP Journal on Wireless Communications and Networking | nb_NO |
dc.source.issue | 362 | nb_NO |
dc.identifier.doi | 10.1186/1687-1499-2012-362 | |
dc.identifier.cristin | 988116 | |
dc.description.localcode | © 2012 Vijayandran et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | nb_NO |
cristin.unitcode | 194,63,35,0 | |
cristin.unitname | Institutt for elektroniske systemer | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |