Heterogeneous network deployment represents one of the main enhancements of future LTE-A networks to increase spectrum efficiency. However, the achievable improvements are limited by the interference that arises from a co-channel allocation of the cells. This paper proposes two cognitive resource allocation methods that work using the angle of arrival of the signals instead of the channel state information. Both methods reduce the interference towards the macro-cell User Equipments (MUEs) using Zero Forcing Beamforming to avoid transmission in the MUEs direction. At the same time they maximize the capacity of the femto-cell with a suitable allocation of the time-frequency resources to the femto-cell UEs (FUEs). The performance of the proposed methods is compared with that of a conventional maximum gain beamforming and conventional zero forcing beamforming. The results show that the proposed methods achieve a good trade off between maximization of the femto-cell capacity and reduction of the interference level at the MUEs side.
Bartoli, G., Fantacci, R., Marabissi, D., Pucci, M. (2014). Resource Allocation schemes for Cognitive LTE-A Femto-cells using Zero Forcing Beamforming and Users Selection. In 2014 IEEE Global Communications Conference (pp.3447-3452). New York : IEEE [10.1109/GLOCOM.2014.7037341].
Resource Allocation schemes for Cognitive LTE-A Femto-cells using Zero Forcing Beamforming and Users Selection
BARTOLI, GIULIO;
2014-01-01
Abstract
Heterogeneous network deployment represents one of the main enhancements of future LTE-A networks to increase spectrum efficiency. However, the achievable improvements are limited by the interference that arises from a co-channel allocation of the cells. This paper proposes two cognitive resource allocation methods that work using the angle of arrival of the signals instead of the channel state information. Both methods reduce the interference towards the macro-cell User Equipments (MUEs) using Zero Forcing Beamforming to avoid transmission in the MUEs direction. At the same time they maximize the capacity of the femto-cell with a suitable allocation of the time-frequency resources to the femto-cell UEs (FUEs). The performance of the proposed methods is compared with that of a conventional maximum gain beamforming and conventional zero forcing beamforming. The results show that the proposed methods achieve a good trade off between maximization of the femto-cell capacity and reduction of the interference level at the MUEs side.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1218780