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Energy Efficiency and Traffic Offloading Optimization in Integrated Satellite/Terrestrial Radio Access Networks
IEEE Transactions on Wireless Communications ( IF 10.4 ) Pub Date : 2020-04-01 , DOI: 10.1109/twc.2020.2964236
Jian Li , Kaiping Xue , David S. L. Wei , Jianqing Liu , Yongdong Zhang

In order to cope with the explosive growth of mobile traffic, many traffic offloading schemes such as heterogenous networks have been developed to enhance network capacity of the Radio Access Network (RAN). Among them, networking of Low-Earth Orbit (LEO) satellites promises to significantly improve the RAN performance due to its economical prospect and advantages in high bandwidth and low latency. In this paper, by introducing the cache-enabled LEO satellite network as a part of RAN, we propose an integrated satellite/terrestrial cooperative transmission scheme to enable an energy-efficient RAN by offloading traffic from base stations through satellite’s broadcast transmission. Considering energy-constraints of satellites, we then formulate a nonlinear fractional programming problem aiming at optimizing transmission energy efficiency of the system. In order to effectively solve this problem, we transform it into an equivalent one, and then adopt iteration and sub-problem decomposition to obtain the optimal solution for each optimization variable, i.e., block placement, power allocation, and cache sharing variable. Numerical results show that compared with traditional terrestrial scheme, our cooperative transmission scheme achieves significant performance improvement in terms of traffic offloading and energy efficiency, especially in an environment of high request consistency degree.

中文翻译:

综合卫星/地面无线电接入网络中的能源效率和流量卸载优化

为了应对移动流量的爆发式增长,已经开发了许多流量分流方案,例如异构网络,以增强无线接入网络(RAN)的网络容量。其中,低地球轨道(LEO)卫星组网以其经济前景和高带宽、低时延等优势,有望显着提升RAN性能。在本文中,通过引入启用缓存的 LEO 卫星网络作为 RAN 的一部分,我们提出了一种集成的卫星/地面协作传输方案,通过卫星广播传输从基站卸载流量来实现节能的 RAN。考虑到卫星的能量约束,我们然后制定了一个非线性分数规划问题,旨在优化系统的传输能量效率。为了有效地解决这个问题,我们将其转化为等价的,然后通过迭代和子问题分解来获得每个优化变量的最优解,即块放置、功率分配和缓存共享变量。数值结果表明,与传统的地面方案相比,我们的协作传输方案在流量分流和能源效率方面取得了显着的性能提升,尤其是在请求一致性程度较高的环境下。
更新日期:2020-04-01
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