Beamforming and interference cancellation for capacity gain in mobile networks

Beamforming and interference cancellation for capacity gain in mobile networks

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Article ID: iaor20027
Country: Netherlands
Volume: 98
Issue: 1
Start Page Number: 235
End Page Number: 253
Publication Date: Dec 2000
Journal: Annals of Operations Research
Authors: , , ,
Keywords: semi-infinite programming
Abstract:

The growth of wireless communication continues. There is a demand for more user capacity from new subscribers and new services such as wireless internet. In order to meet these expectations new and improved technology must be developed. A way to increase the capacity of an existing mobile radio network is to exploit the spatial domain in an efficient way. An antenna array adds spatial domain selectivity in order to improve the Carrier-to-Interference ratio (C/I) as well as Signal-to-Noise Radio (SNR). An adaptive antenna array can further improve the Carrier-to-Interference ratio (C/I) by suppressing interfering signals and steer a beam towards the user. The suggested scheme is a combination of a beamformer and an interference canceller. The proposed structure is a circular array consisting of K omni-directional elements and combines fixed beamforming with interference cancelling. The fixed beamformers use a weight matrix to form multiple beams. The interference cancelling stage suppresses undesired signals, leaking into the desired beam. The desired signal is filtered out by the fixed beamforming structure. Due to the side-lobes, interfering signals will also be present in this beam. Two alternate strategies were chosen to cancel these interferers; use the other beamformer outputs as inputs to an adaptive interference canceller; or regenerate the outputs from the other beamformer outputs and generate clean signals which are used as inputs to adaptive interference cancellers. Resulting beamformer patterns as well as interference cancellation simulation results are presented. Two different methods have been used to design the beamformer weights, Least Square (LS) and minimax optimisation. In the minimax optimisation a semi-infinite linear programming approach was used. Although the optimisation plays an essential role in the performance of the beamformer, this paper is focused on the application rather than the optimisation methods.

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