Premium
Enriching self‐organizing networks use cases with opportunistic features: a coverage and capacity optimization paradigm
Author(s) -
Karvounas Dimitrios,
Vlacheas Panagiotis,
Georgakopoulos Andreas,
Stavroulaki Vera,
Demestichas Panagiotis
Publication year - 2013
Publication title -
international journal of network management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 28
eISSN - 1099-1190
pISSN - 1055-7148
DOI - 10.1002/nem.1829
Subject(s) - computer science , constraint (computer aided design) , throughput , exploit , distributed computing , control reconfiguration , quality of service , base station , computer network , resource (disambiguation) , macro , cellular network , resource allocation , service (business) , telecommunications , computer security , embedded system , mechanical engineering , programming language , economy , engineering , economics , wireless
SUMMARY Self‐organizing networks (SONs) have been introduced into long‐term evolution in order to configure and optimize the network in an autonomic manner. However, in some situations the reconfiguration of the entire network is not the most cost‐efficient solution. Consequently, opportunistic networks have been introduced as operator‐governed, coordinated extensions of the infrastructure that are created dynamically where and when they are needed, exploiting the radio environment. This work proposes an enhanced SON functional architecture (FA) with opportunistic features in order to handle such situations through the manipulation of ONs. In addition, the proposed FA is utilized in a coverage and capacity optimization use case, where small cells are deployed in order to extend the capacity of a macro base station (BS). Users opportunistically exploit the resources (i.e. resource blocks) of the small cells. In addition, the small cells are configured to the optimal power level in order to maximize the users’ throughput without causing interference to the other users. Two different approaches of controlling the interference among the macro BS and the small cells are presented, namely soft constraint and hard constraint cases. Furthermore, apart from maximizing the users’ throughput, emphasis is given to the fairness among the users and on the quality‐of‐service provision through a proper resource allocation. The evaluation proved that when small cells are introduced the system's throughput is increased by 12.76% when the macro BS and the small cells cannot use the same resource blocks simultaneously (hard constraint case) and by 8.25% when the reuse is possible. Copyright © 2013 John Wiley & Sons, Ltd.