  Adaptive Power Allocation (PA) algorithms with different criteria for a
cooperative Multiple-Input Multiple-Output (MIMO) network equipped with
Distributed Space-Time Coding (DSTC) are proposed and evaluated. Joint
constrained optimization algorithms to determine the power allocation
parameters, the channel parameters and the receive filter are proposed for each
transmitted stream in each link. Linear receive filter and maximum-likelihood
(ML) detection are considered with Amplify-and-Forward (AF) and
Decode-and-Forward (DF) cooperation strategies. In the proposed algorithms, the
elements in the PA matrices are optimized at the destination node and then
transmitted back to the relay nodes via a feedback channel. The effects of the
feedback errors are considered. Linear MMSE expressions and the PA matrices
depend on each other and are updated iteratively. Stochastic gradient (SG)
algorithms are developed with reduced computational complexity. Simulation
results show that the proposed algorithms obtain significant performance gains
as compared to existing power allocation schemes.
