Low-complexity turbo receivers for multiple antenna space-time coded systems via variational inference

We first introduce a unified framework for variational inference and estimation in the cases where an exact inference becomes computationally intractable. Specifically, approximate inference via a variational minimization technique is obtained by operating a generic message-passing algorithm in the distributed factor graph where the coupling between the multiple Markov chains is removed by minimizing the cross-entropy between the original and the variational objective functions. Importantly, we demonstrate how this framework can be used in deriving low-complexity turbo receiver structures for various space-time coded multiple transmitter multiple receiver antenna systems over multipath fading channels. Moreover, we show that some already known turbo BLAST (Bell Labs layered space-time) receiver structures can be interpreted as exact realizations of the message-passing algorithm operating in the distributed variational factor graph. Despite the significant reduction in complexity, the initial performance simulations has shown that the derived turbo receivers are able to provide close to optimal performance.