5G connectivity has become essential to integrate rural communities into the broader digital economy and support critical applications like remote education and remote surgery. A major hindrance to expanding rural broadband coverage, especially in developing countries, is the high cost of installing 5G base stations. Hence, there is a need to reduce the cost of a 5G base station without degrading its performance. Our work proposes a novel approach to efficiently utilize the polar code encoders in a 5G base station. The idea is to use the idle time of the polar encoders during downlink transmission for error correction in the 5G data plane. Polar codes have conventionally been used in the 5G control plane, while LDPC codes are used in the data plane. We perform detailed characterization experiments to show the advantages of using polar codes in the data plane as well. Further, to intelligently distribute the user data packets among the available compute nodes, we propose a set of novel resource allocation algorithms and compare their performance with other algorithms in the literature. Using our proposed optimization techniques, we achieve a 17% reduction in the cost of a 5G base station. Simultaneously, we are able to improve the performance by 24% compared to a conventional base station.

翻译：5G连接已成为将农村社区融入更广泛的数字经济并支持远程教育和远程手术等关键应用的必要条件。扩大农村宽带覆盖的主要障碍（尤其是在发展中国家）是安装5G基站的高昂成本。因此，有必要在不降低性能的情况下降低5G基站的成本。我们的工作提出了一种新颖的方法，以高效利用5G基站中的极化码编码器。其核心思想是在下行链路传输期间利用极化编码器的空闲时间进行5G数据平面的纠错。极化码传统上用于5G控制平面，而LDPC码用于数据平面。我们进行了详细的表征实验，以展示在数据平面中也使用极化码的优势。此外，为了在可用计算节点之间智能分配用户数据包，我们提出了一组新颖的资源分配算法，并将其性能与文献中的其他算法进行了比较。采用我们提出的优化技术，我们实现了5G基站成本降低17%。与此同时，与传统基站相比，我们能够将性能提升24%。