Robust Transceiver Design for Full-Duplex Decode-and-Forward Relay-Assisted MIMO Systems
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Robust transceiver design against unresolvable system uncertainties is of crucial importance for reliable communication. For instance, full-duplex communication suffers from such uncertainties when canceling the self-interference, since some residual self-interference (RSI) remains uncanceled due to imperfect channel knowledge. We consider a MIMO multi-hop system, where the source, the relay and the destination are equipped with multiple antennas. The considered decode-and-forward (DF) hybrid relay can operate in either half-duplex or full-duplex mode, and the mode changes adaptively depending on the RSI strength. We investigate a robust transceiver design problem, which maximizes the throughput rate of the worstcase RSI under the self-interference channel uncertainty bound constraint. The yielded problem turns out to be a non-convex optimization problem, where the non-convex objective is optimized over the cone of semidefinite matrices. Without loss of generality, we simplify the problem to the optimization over multiple scalar parameters using majorization theory. Furthermore, we propose an efficient algorithm to obtain a local optimal solution iteratively. Eventually, we obtain insights on the optimal antenna allocation at the relay input-frontend and output-frontend, for relay reception and transmission, respectively. Interestingly, given a number of antennas at the relay, the robustness improves if more antennas are allocated to reception than to transmission.
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