Access probability optimization for streaming media transmission in heterogeneous cellular networks
Access probability optimization for streaming media transmission in heterogeneous cellular networks
复制标题
异构蜂窝网络流媒体传输的接入概率优化
DOI：
10.1007/s11276-022-03014-9
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发表时间：
2022-07
影响因子：
3
通讯作者：
Xingwei Wang
中科院分区：
文献类型：
--
作者：
Jie Jia;Linjiao Xia;Pengshuo Ji;Jian Chen;Xingwei Wang
本文研究了FemtoCaching技术，旨在最大化异构蜂窝网络中流媒体传输的接入概率。首先，根据网络拓扑结构和用户与流媒体的关系，提出了五种流媒体部署方案。其次，提出了一种自适应流媒体部署的匹配算法，其中FemtoCaching可以动态调整。第三，结合信道分配、功率分配和缓存部署，建立了一个联合问题。针对这一问题，提出了一种匹配算法和遗传算法相结合的联合优化算法，以最大化流媒体传输的接入概率。仿真实验表明：（1）基于该算法的网络中所有用户访问流媒体的平均接入概率与现有算法相比有较大提高;（2）性能随信道数和微基站存储容量的增加而提高，随用户数的增加而降低。
FemtoCaching technology, aiming at maximizing the access probability of streaming media transmission in heterogeneous cellular networks, is investigated in this paper. Firstly, five kinds of streaming media deployment schemes are proposed based on the network topology and the relationship between users and streaming media. Secondly, a matching algorithm for adaptive streaming media deployment is proposed, where the FemtoCaching can be adjusted dynamically. Thirdly, a joint problem is formulated combined with the channel assignment, the power allocation, and the caching deployment. To address this problem, we propose a joint optimization algorithm combining matching algorithm and genetic algorithm to maximize the access probability of streaming media transmission. Simulation experiments demonstrate that: (1) the average access probability of all users accessing streaming media in the network based on the proposed algorithm compared with recent works can be greatly improved, and (2) the performance increases with increasing the number of channels and the storage capacity of micro base stations, but decreases with increasing the number of users.
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