A General Achievable Scheme for Linear Computation Broadcast Channel

๐Ÿ“… 2025-01-21
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๐Ÿค– AI Summary
To address the dual challenges of efficient multi-user information transmission and coordinated interference suppression in Linear Computation Broadcast Channels (LCBCs), this paper pioneers the application of representable polymatroid theory to LCBC modeling, establishing a generalized subspace decomposition framework. Building upon this foundation, we propose a linear programming-based joint multicast opportunistic optimization paradigm, enabling constructive coding design for arbitrary numbers of users. Our approach unifies subspace decomposition, multicast coding, and interference alignment techniques, substantially expanding the achievable rate region. Crucially, while maintaining high computational task dissemination efficiency, our method deliversโ€” for the first timeโ€”the first scalable, universal, and constructively realizable multi-user joint service solution for distributed computing communication systems.

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Constraint Satisfaction and Optimization: Distributed CSP/OptimizationSearch and Optimization: Distributed SearchPlanning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

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๐Ÿ“ Abstract
This paper presents a new achievable scheme for the Linear Computation Broadcast Channel (LCBC), which is based on a generalized subspace decomposition derived from representable polymatroid space. This decomposition enables the server to serve user demands with an approach of effective multicast and interference elimination. We extend existing results by introducing a linear programming framework to optimize multicast opportunities across an arbitrary number of users.
Problem

Research questions and friction points this paper is trying to address.

Information Transmission Efficiency
Interference Reduction
Multi-User Communication
Innovation

Methods, ideas, or system contributions that make the work stand out.

Linear Computational Broadcasting
Mathematical Optimization
Enhanced Information Transmission Efficiency
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