  This paper focuses on linear beamforming design and power allocation strategy
for ergodic rate optimization in a two-user Multiple-Input-Single-Output (MISO)
system with statistical and delayed channel state information at the
transmitter (CSIT). We propose a transmission strategy, denoted as Statistical
Alternative MAT (SAMAT), which exploits both channel statistics and delayed
CSIT. Firstly, with statistical CSIT only, we focus on statistical beamforming
(SBF) design that maximizes a lower bound on the ergodic sum-rate. Secondly,
relying on both statistical and delayed CSIT, an iterative algorithm is
proposed to compute the precoding vectors of Alternative MAT (AMAT), originally
proposed by Yang et al., which maximizes an approximation of the ergodic
sum-rate with equal power allocation. Finally, via proper power allocation, the
SAMAT framework is proposed to softly bridge between SBF and AMAT for an
arbitrary number of transmit antennas and signal-to-noise ratio (SNR). A
necessary condition for the power allocation optimization is identified from
the Karush-Kuhn-Tucker (KKT) conditions. The optimum power allocation to
maximize an ergodic sum-rate approximation is computed using Sequential
Quadratic Programming (SQP). Simulation results show that the proposed SAMAT
scheme yields a significant sum-rate enhancement over both SBF and AMAT.
