Efficient Approximation Algorithms for Multi-Antennae Largest Weight Data Retrieval
Longkun Guo, Hong Shen, Wenxing Zhu

TL;DR
This paper introduces a highly efficient approximation algorithm for the $ ext{delta}$-antennae largest weight data retrieval problem in wireless networks, significantly improving computational complexity while maintaining a near-optimal ratio.
Contribution
The paper presents the first ratio $1-rac{1}{e}- ext{ extepsilon}$ approximation algorithm for the general $ ext{delta}$ALWDR problem with improved time complexity.
Findings
Achieved a $1-rac{1}{e}- ext{ extepsilon}$ approximation ratio.
Reduced the algorithm's time complexity from exponential to polynomial in key parameters.
Provided a new approach for handling data items appearing multiple times across segments.
Abstract
In a mobile network, wireless data broadcast over channels (frequencies) is a powerful means for distributed dissemination of data to clients who access the channels through multi-antennae equipped on their mobile devices. The -antennae largest weight data retrieval (ALWDR) problem is to compute a schedule for downloading a subset of data items that has a maximum total weight using antennae in a given time interval. In this paper, we propose a ratio approximation algorithm for the -antennae largest weight data retrieval (ALWDR) problem that has the same ratio as the known result but a significantly improved time complexity of from when \cite{lu2014data}. To our knowledge, our algorithm represents…
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