P.-J. Chung, H. Du and J. Gondzio
Abstract
Transmit beamforming is a powerful technique for enhancing
performance of wireless communication systems. Most
existing transmit beamforming techniques require perfect
channel state information at the transmitter (CSIT), which
is typically not available in practice. In such situations,
the design should take errors in CSIT into account to
avoid performance degradation. Among two popular robust
designs, the stochastic approach exploits channel statistics
and optimizes the average system performance. The
maximin approach considers errors as deterministic and
optimizes the worst-case performance. The latter usually
leads to conservative results as the extreme (but rare)
conditions may occur at a very low probability. In this
work, we propose a more flexible approach that maximizes
the average signal-to-noise ratio (SNR) and takes the
extreme conditions into account proportionally. Simulation
results show that the proposed beamformer offers higher
robustness against channel estimation errors than several
popular transmit beamformers.
Key words: Wireless Communication Systems, Beamforming, Probabilistic Constraints, Robust Optimization.