While the exact capacity of large interference networks remains largely intractable, much progress has come about from alternative approaches. In particular, Generalized Degrees of Freedom (GDoF) region characterizations, combined with extremal network theory have significantly advanced the theoretical understanding of the basic scheme of treating interference as (Gaussian) noise (TIN) with power control, producing closed form solutions of the achievable GDoF region via implicit Fourier-Motzkin elimination of power-control variables, as well as extremal characterizations of the relative performance of TIN against other alternatives. The goal of this work is to develop this approach beyond TIN, especially to include successive interference cancellation (SIC). The first contribution is a closed form (i.e., depending only on the channel parameters) characterization of the achievable GDoF region for an SIC scheme for any specified decoding order at each receiver, and anyKuser network topology. This is followed by extremal network theoretic analysis, showing that the maximal sum-GDoF gain from SIC over TIN across all network topologies is precisely min(K,2L+1), when a total of up toLmessages can be successively decoded at every receiver. Remarkably, even when restricted to only weak interference settings where the benefits of SIC are not obvious, the extremal gain of SIC over TIN is shown to be significant, approachingL+1 for largeK. Networks that achieve these extremal gains are explicitly identified. The GDoF analysis is complemented with numerical simulations to illustrate how the insights translate to finite Signal-to-Noise Ratios.

Blind Interference Alignment (BIA) schemes create and exploit channel coherence patterns without the knowledge of channel realizations at transmitters, while beamforming schemes rely primarily on channel knowledge available to the transmitters without regard to channel coherence patterns. In order to explore the compatibility of these disparate ideas and the possibility of synergistic gains, this work studies the Degrees of Freedom (DoF) of the 2-user${(M_{1}\times N_{1})(M_{2}\times N_{2})}$Multiple-Input Multiple-Output (MIMO) Interference Channel (IC) where Transmitter 1 is equipped with reconfigurable antennas and has no channel knowledge, while Transmitter 2 has partial channel knowledge but no reconfigurable antennas. Taking a fundamental dimensional analysis perspective, the main question is to identify which antenna configurations allow synergistic DoF gains. The main results of this work are two-fold. The first result identifies antenna configurations where both reconfigurable antennas and partial channel knowledge are individually beneficial, as those where$M_{1}< N_{1}< \min (M_{2},N_{2})$. The second result shows that synergistic gains exist in each of these settings, over the best known solutions that rely on either reconfigurable antennas or partial channel knowledge alone. Coding schemes that jointly exploit partial channel knowledge and reconfigurable antennas emerge as a byproduct of the analysis.