Forward-Aware Information Bottleneck-Based Vector Quantization for Noisy Channels

Hassanpour, Shayan; Monsees, Tobias; Wübben, Dirk; Dekorsy, Armin

doi:10.1109/tcomm.2020.3019447

Cited by 9 publications

(19 citation statements)

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“…In [49], the Noisy Source Coding (NSC) scenario of the Information Bottleneck (IB) method [1] has been extended to the Joint Source-Channel Coding (JSCC) setup for quantization of a single noisy observation (scalar/vector-valued) 1 . For that, the illustrated system model in Fig.…”

Section: Ib-based Jscc: a Brief Overview Of The Uniterminal Casementioning

confidence: 99%

“…with λ ≥ 0, denoting the counterpart relaxation of the upperbound, R, in (1). Utilizing Variational Calculus, it has been shown in [49] that for stationary points of the objective functional in (2), it holds (for each pair (y, z) ∈ Y ×Z)…”

Section: Ib-based Jscc: a Brief Overview Of The Uniterminal Casementioning

confidence: 99%

“…with β = 1 λ and ψ(y, β), being a normalization function, ensuring the resultant mapping's validity. Further, an iterative routine, termed Forward-Aware Vector Information Bottleneck (FAVIB), has been proposed in [49] that, indeed, carries out the Fixed-Point Iteration method on (3). The convergence of FAVIB to a local optimum of its objective functional has been proven as well, and it has been shown that this compression scheme enjoys inherent error-protection, capable of obviating the need for channel coding on the noisy forward link.…”

Section: Ib-based Jscc: a Brief Overview Of The Uniterminal Casementioning

confidence: 99%

“…Contributions: The full-format extension of the original IB method for NSC to uniterminal JSCC has been developed in [49], where an iterative algorithm, termed Forward-Aware Vector Information Bottleneck (FAVIB) has been proposed to tackle the underlying non-convex design problem. Herein, we concentrate on a particular instance of the multiterminal JSCC problem in which several observations from a given data source shall be compressed locally before getting transmitted over multiple noisy forward links to a (distant) processing unit.…”

Section: Introductionmentioning

confidence: 99%

“…Pursuing the IB philosophy, then we introduce the parallel and successive compression schemes, both enjoying a joint design of local quantizers and utilizing specific MI terms to quantify the informativity and compactness of their resultant outcomes. Subsequently, with a similar argument to [49], we characterize the form of stationary solutions regarding the considered distributed compression problems. Particularly, we find the stationary points obtained by the Lagrangian relaxation of the constrained optimization modeling of such problems.…”

Section: Introductionmentioning

confidence: 99%

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Forward-Aware Information Bottleneck-Based Vector Quantization: Multiterminal Extensions for Parallel and Successive Retrieval

Hassanpour

Wübben

Dekorsy

2021

IEEE Trans. Commun.

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Consider the following setup: Through a joint design, multiple observations of a remote data source shall be locally compressed before getting transmitted via several error-prone, rate-limited forward links to a (distant) processing unit. For addressing this specific instance of multiterminal Joint Source-Channel Coding problem, in this article, the foundational principle of the Information Bottleneck method is fully extended to obtain purely statistical design approaches, enjoying the Mutual Information as their fidelity criterion. Specifically, the forms of stationary points for two types of distributed compression schemes are characterized here. Subsequently, those acquired solutions are utilized as the centerpiece of the proposed generic, iterative algorithm, termed the Multiterminal Forward-Aware Vector Information Bottleneck (M-FAVIB), for addressing the design optimizations. Leveraging an unfolding trick, it will be proven that both distributed compression schemes fall into the category of Successive Upper-Bound Minimization, ensuring their convergence to a stationary point. Eventually, the effectiveness of the proposed compression schemes will be substantiated as well by means of numerical investigations over some typical transmission scenarios.

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Section: Ib-based Jscc: a Brief Overview Of The Uniterminal Casementioning

confidence: 99%

Section: Ib-based Jscc: a Brief Overview Of The Uniterminal Casementioning

confidence: 99%

Section: Ib-based Jscc: a Brief Overview Of The Uniterminal Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations