Interference as Noise: Friend or Foe?
Alex Dytso, Daniela Tuninetti, and Natasha Devroye

TL;DR
This paper demonstrates that treating interference as noise with non-Gaussian mixed inputs achieves near-optimal capacity in two-user Gaussian interference channels across all regimes, challenging the traditional view of interference as solely a foe.
Contribution
It introduces the use of mixed discrete-Gaussian inputs for interference channels, showing their effectiveness in achieving near-capacity without joint decoding or time sharing.
Findings
TINnoTS achieves capacity region within a constant or logarithmic gap.
Mixed inputs with discrete components act as effective common messages.
TINnoTS is gDoG optimal across all interference regimes.
Abstract
This paper shows that for the two-user Gaussian Interference Channel (G-IC) Treating Interference as Noise without Time Sharing (TINnoTS) achieves the closure of the capacity region to within either a constant gap, or to within a gap of the order O(logln(min(S,I))) where S is the largest Signal to Noise Ratio (SNR) on the direct links and I is the largest Interference to Noise Ratio (INR) on the cross links. As a consequence, TINnoTS is optimal from a generalized Degrees of Freedom (gDoF) perspective for all channel gains except for a subset of zero measure. TINnoTS with Gaussian inputs is known to be optimal to within 1/2 bit for a subset of the weak interference regime. Surprisingly, this paper shows that TINnoTS is gDoG optimal in all parameter regimes, even in the strong and very strong interference regimes where joint decoding of Gaussian inputs is optimal. For approximate…
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Taxonomy
TopicsWireless Communication Security Techniques · Cooperative Communication and Network Coding · Advanced MIMO Systems Optimization
