Article ; Online: QoS-Aware Resource Allocation with Pilot-Aided Channel Estimation for Heterogeneous Wireless Networks.
2022 Volume 22, Issue 12
Abstract: The deployment of heterogeneous networks (HetNets) is a way to increase the network capacity and release part of the traffic generated by users inside a cell to small-scale wireless networks for service. In this context, the main problem is managing the ... ...
Abstract | The deployment of heterogeneous networks (HetNets) is a way to increase the network capacity and release part of the traffic generated by users inside a cell to small-scale wireless networks for service. In this context, the main problem is managing the interference due to the coexistence of small cells and macro cells. In this paper, a QoS-aware Resource Allocation (RA) algorithm jointly working with admission control (AC) over a two-tier HetNet scenario is investigated in the presence of both the pilot-symbols for channel estimation and the channel estimation error. The RA algorithm allows two users, the macro cell user (CU) and small cell user (SU), to simultaneously share the same resource block. Moreover, system performance and fairness are improved by including adaptive power allocation to users over resource blocks. In the framework of RA with proportional rate constraints, a novel algorithm is designed by including the effects of pilot-aided channel estimation. The algorithm is able to distribute the same proportional rate to all CUs and SUs, even in the presence of channel estimation error. Relevant numerical results for the downlink of a two-tier HetNet with pilot-aided channel estimation show that the rate dispersion is driven to zero while the sum-rate is maximized, and the average user rate penalty with respect to a perfect-CSI scenario may rise to 20%. |
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MeSH term(s) | Algorithms ; Computer Communication Networks ; Resource Allocation ; Wireless Technology |
Language | English |
Publishing date | 2022-06-16 |
Publishing country | Switzerland |
Document type | Journal Article |
ZDB-ID | 2052857-7 |
ISSN | 1424-8220 ; 1424-8220 |
ISSN (online) | 1424-8220 |
ISSN | 1424-8220 |
DOI | 10.3390/s22124545 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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