Optimization of two-way communication with ARQ feedback

In this paper, we study ARQ feedback in the context of two-way wireless communications. In particular, we consider two nodes which wish to exchange data over a frequency division duplex, time-varying wireless additive white Gaussian noise with Rayleigh fading, channel. In two-way scenarios, unlike the more well studied one-way data scenarios, the data and resources allocated to feedback and channel estimation may share the same link, leading to interesting tradeoffs. To analyze these, we present a two-way framework in which 1) training (estimation of channel state), 2) feedback (in the form of ARQ), and 3) data are taken into account, and share the same noisy fading channel. We obtain an expression which captures the tradeoffs between allocating resources for these three tasks on the overall throughput achievable in each direction, which we numerically evaluate. In particular, we obtain the optimal resource allocations corresponding to different channel conditions, SNR regimes, and receiver feedback protocols under fast and slow fading conditions.