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Fundamentals of Treating Interference as Noise


Treating interference as noise (TIN) when it is sufficiently weak is one of the key principles of interference management for wireless networks. This dissertation revisits the optimality of TIN from an information theoretic perspective. It is shown that for K-user Gaussian interference channels, TIN achieves all points in the capacity region to within a constant gap, if for each user, the desired signal strength is no weaker than the sum of the strengths of the strongest interference caused by the user and the strongest interference suffered by the user (with all signal strengths measured in dB scale). We also extend the optimality of TIN to more general settings, including interference networks with general message sets, compound networks and MIMO interference channels, and characterize the secure capacity region within a constant gap for the identified TIN-optimal interference channels with secrecy constraints. Moreover, combining TIN with interference avoidance, we formulate a joint signal space and signal level optimization problem and propose a baseline decomposition approach.

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