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Optimality of Treating Interference as Noise: A Combinatorial Perspective

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arxiv 1504.00041 v2 pith:PPKOX2TV submitted 2015-03-31 cs.IT math.IT

classification cs.ITmath.IT
keywords itlinqinterferencepowerproblemregioncontrolflashlinqnetworks
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For single-antenna Gaussian interference channels, we re-formulate the problem of determining the Generalized Degrees of Freedom (GDoF) region achievable by treating interference as Gaussian noise (TIN) derived in [3] from a combinatorial perspective. We show that the TIN power control problem can be cast into an assignment problem, such that the globally optimal power allocation variables can be obtained by well-known polynomial time algorithms. Furthermore, the expression of the TIN-Achievable GDoF region (TINA region) can be substantially simplified with the aid of maximum weighted matchings. We also provide conditions under which the TINA region is a convex polytope that relax those in [3]. For these new conditions, together with a channel connectivity (i.e., interference topology) condition, we show TIN optimality for a new class of interference networks that is not included, nor includes, the class found in [3]. Building on the above insights, we consider the problem of joint link scheduling and power control in wireless networks, which has been widely studied as a basic physical layer mechanism for device-to-device (D2D) communications. Inspired by the relaxed TIN channel strength condition as well as the assignment-based power allocation, we propose a low-complexity GDoF-based distributed link scheduling and power control mechanism (ITLinQ+) that improves upon the ITLinQ scheme proposed in [4] and further improves over the heuristic approach known as FlashLinQ. It is demonstrated by simulation that ITLinQ+ provides significant average network throughput gains over both ITLinQ and FlashLinQ, and yet still maintains the same level of implementation complexity. More notably, the energy efficiency of the newly proposed ITLinQ+ is substantially larger than that of ITLinQ and FlashLinQ, which is desirable for D2D networks formed by battery-powered devices.

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  1. Deep Unfolding of Fixed-Point Based Algorithm for Weighted Sum Rate Maximization

    cs.IT 2025-01 reject novelty 4.0 of 10

    A deep-unfolded primal-dual power control algorithm reaches about 101 percent of the FPLinQ benchmark in under 10 iterations, but its convergence theorem relies on a false monotonicity lemma.

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