ITLGNISPSep 11, 2023

Beamforming in Wireless Coded-Caching Systems

arXiv:2309.05276v11 citationsh-index: 26
Originality Incremental advance
AI Analysis

This addresses network capacity issues for wireless systems, but it is incremental as it combines existing techniques with optimization.

The paper tackles capacity challenges in wireless transport networks by integrating beamforming and coded-caching strategies, resulting in significant reduction in peak backhaul traffic through gains in multicast opportunities and interference mitigation.

Increased capacity in the access network poses capacity challenges on the transport network due to the aggregated traffic. However, there are spatial and time correlation in the user data demands that could potentially be utilized. To that end, we investigate a wireless transport network architecture that integrates beamforming and coded-caching strategies. Especially, our proposed design entails a server with multiple antennas that broadcasts content to cache nodes responsible for serving users. Traditional caching methods face the limitation of relying on the individual memory with additional overhead. Hence, we develop an efficient genetic algorithm-based scheme for beam optimization in the coded-caching system. By exploiting the advantages of beamforming and coded-caching, the architecture achieves gains in terms of multicast opportunities, interference mitigation, and reduced peak backhaul traffic. A comparative analysis of this joint design with traditional, un-coded caching schemes is also conducted to assess the benefits of the proposed approach. Additionally, we examine the impact of various buffering and decoding methods on the performance of the coded-caching scheme. Our findings suggest that proper beamforming is useful in enhancing the effectiveness of the coded-caching technique, resulting in significant reduction in peak backhaul traffic.

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