Exploiting the short-term and long-term channel properties in space and time: Eigenbeamforming concepts for the BS in WCDMA

The deployment of adaptive antennas at base stations considerably increases the spectral efficiency of wireless communication systems. To reduce the computational complexity and increase performance of space-time (ST) processing, processing may take place in reduced dimension, i.e., pre-filtering takes place which is related to linear estimation theory based on second order statistics. To this end, long-term and short-term channel estimates are integrated into specific Tx/Rx systems. In this article, we present a new ST rake structure for uplink reception in WCDMA which operates in reduced dimension. Accordingly, our approach combines short-term and long-term spatial and temporal channel properties using an eigenanalysis. By choosing dominant eigenbeams in time and space, the algorithm enhances interference suppression as well as spatial and temporal receive diversity. In contrast to previously introduced well-known receiver structures, the ST eigenrake inherently adapts to different propagation environments and achieves higher spectral efficiency than other receivers. This is illustrated by Monte-Carlo simulations. Then we extend the proposed concept to the downlink. The downlink eigenbeamformer improves closed-loop downlink diversity compared to other proposals in standardization (3GPP) which only exploit short-term channel properties. Even though the short-term feedback rate remains unchanged, additional antenna elements can be included to increase antenna and diversity gain. We also present a tracking solution to the downlink eigenbeamforming in WCDMA. To this end, we propose a distributed implementation of the eigenspace/-beam tracking at the mobile terminal and base station (BS), respectively. Moreover, the specific nature of the deployed tracking scheme offers an advantageous feedback signalling.