6533b852fe1ef96bd12aac03

RESEARCH PRODUCT

On optimal deployment of low power nodes for high frequency next generation wireless systems

Alexander SayenkoHämäläinen TimoMikhail Zolotukhin

subject

Computer Networks and CommunicationsComputer sciencegeneettiset algoritmitOptimal deployment050801 communication & media studies02 engineering and technologyrelaylangaton tiedonsiirtoBase station0508 media and communicationsoptimointigenetic algorithm0202 electrical engineering electronic engineering information engineeringWirelessWireless systemsta113ta213business.industry05 social sciencessmall cell020206 networking & telecommunicationsBackhaul (telecommunications)Software deploymentmulti-hop networkbusinessoptimizationlangattomat verkotComputer network

description

Recent development of wireless communication systems and standards is characterized by constant increase of allocated spectrum resources. Since lower frequency ranges cannot provide sufficient amount of bandwidth, new bands are allocated at higher frequencies, for which operators resort to deploy more base stations to ensure the same coverage and to utilize more efficiently higher frequencies spectrum. Striving for deployment flexibility, mobile operators can consider deploying low power nodes that could be either small cells connected via the wired backhaul or relays that utilize the same spectrum and the wireless access technology. However, even though low power nodes provide a greater flexibility in terms of where they can be deployed, they also create new challenges. In particular, it is often the case that operators need to balance carefully between how many additional low power nodes it is necessary to install versus potential gains of the whole system. Thus, in this study we aim to develop a model that can find optimal network configuration for low power nodes assisting operators network deployment process. The outcome of the analytical model is complemented by extensive dynamic system level simulations, by means of which we analyze overall system performance for the obtained solutions. We also show that deviations from optimal configurations can lead to significantly worse system performance. peerReviewed

https://doi.org/10.1016/j.comnet.2018.07.029