Beamforming and interference cancellation for capacity gain in mobile networks

Citation
S. Nordholm et al., Beamforming and interference cancellation for capacity gain in mobile networks, ANN OPER R, 98, 2000, pp. 235-253
Citations number
15
Categorie Soggetti
Engineering Mathematics
Journal title
ANNALS OF OPERATIONS RESEARCH
ISSN journal
02545330 → ACNP
Volume
98
Year of publication
2000
Pages
235 - 253
Database
ISI
SICI code
0254-5330(2000)98:<235:BAICFC>2.0.ZU;2-B
Abstract
The growth of wireless communication continues. There is a demand for more user capacity from new subscribers and new services such as wireless intern et. In order to meet these expectations new and improved technology must be developed. A way to increase the capacity of an existing mobile radio netw ork is to exploit the spatial domain in an efficient way. An antenna array adds spatial domain selectivity in order to improve the Carrier-to-Interfer ence ratio (C/J) as well as Signal-to-Noise Ratio (SNR). An adaptive antenn a array can further improve the Carrier-to-Interference ratio (CII) by supp ressing interfering signals and steer a beam towards the user. The suggeste d 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 interfere nce 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. T wo alternative strategies were chosen to cancel these interferers; use the other beamformer outputs as inputs to an adaptive interference canceller; o r regenerate the outputs from the other beamformer outputs and generate cle an signals which are used as inputs to adaptive interference cancellers. Resulting beamformer patterns as well as interference cancellation simulati on results are presented. Two different methods have been used to design th e beamformer weights, Least Square (LS) and minimax optimisation. In the mi nimax optimisation a semi-infinite linear programming approach was used. Al though the optimisation plays an essential role in the performance of the b eamformer, this paper is focused on the application rather then the optimis ation methods.