Computational communication for three-dimensional dense coverage in 5G systems:architecture,approach and gain

Jinkun CHENG; Wei CHEN; Yuanming SHI

doi:10.11959/j.issn.1000-0801.2017118

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Computational communication for three-dimensional dense coverage in 5G systems:architecture,approach and gain

Topic:5G | 更新时间：2024-06-05

- Computational communication for three-dimensional dense coverage in 5G systems:architecture,approach and gain
- Telecommunications Science Vol. 33, Issue 6, Pages: 41-53(2017)
- 作者机构：
  
  1. 清华大学电子工程系，北京 100084
  2. 上海科技大学信息科学与技术学院，上海 201210
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2017118
  CLC： TP393
- Published Online：2017-06，
  
  Published：20 June 2017
- 稿件说明：
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Jinkun CHENG, Wei CHEN, Yuanming SHI. Computational communication for three-dimensional dense coverage in 5G systems:architecture,approach and gain[J]. Telecommunications science, 2017, 33(6): 41-53.
DOI：

Jinkun CHENG, Wei CHEN, Yuanming SHI. Computational communication for three-dimensional dense coverage in 5G systems:architecture,approach and gain[J]. Telecommunications science, 2017, 33(6): 41-53. DOI： 10.11959/j.issn.1000-0801.2017118.

摘要

提出了一种新型的室内密集立体覆盖的计算通信一体化架构，通过挖掘信道计算、容量计算以及网络资源优化计算之间的内在联系，并利用基于云计算和雾计算的密集分布式接入网络的优势，该架构完成了计算电磁学、计算信息论与大规模优化理论到计算通信理论的深度融合。介绍了该架构的实现方法，即以密集异构分布式无线接入网络作为通信接入网络基础架构，利用分布式的计算资源结合计算电磁学理论实现并行化的信道计算，据此进一步依据计算信息论实现容量计算，并基于大规模优化理论完成多用户的网络资源优化计算，最终实现由传播环境到信道容量与资源分配的计算通信。

Abstract

An integrated mobile computational communication architecture for three-dimensional dense coverage in indoor environment was proposed

and the proposed network architecture thus unified the computational electromagnetics

computational information theory and large-scale optimization into computational communication theory.Moreover

the implementation of the architecture was introduced.Specifically

the dense heterogeneous distributed radio access network was served as the wireless radio access network for the proposed computational communication architecture.Furthermore

computational electromagnetics based on channel propagation computing was implemented in parallel using the distributed computation resources.Given the exact channel propagation coefficients

the computational information theory based on channel capacity computation

as well as large-scale optimization based on multiuser network resource allocation were also achieved by the powerful computation resources.The proposed computational communication theory can thus compute the channel capacity and design power allocation scheme directly from propagation environment.

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Keywords

references

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