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Energy-efficient joint content caching and small base station activation mechanism design in heterogeneous cellular networks

机译:异构蜂窝网络中的节能联合内容缓存和小型基站激活机制设计

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摘要

Heterogeneous cellular networks (HCNs), by introducing caching capability, has been considered as a promising technique in 5G era, which can bring contents closer to users to reduce the transmission delay, save scarce bandwidth resource. Although many works have been done for caching in HCNs, from an energy perspective, there still exists much space to develop a more energy-efficient system when considering the fact that the majority of base stations are under-utilized in the most of the time. Therefore, in this paper, by taking the activation mechanism for the base stations into account, we study a joint caching and activation mechanism design to further improve the energy efficiency, then we formulate the optimization problem as an Integer Linear Programming problem (ILP) to maximize the system energy saving. Due to the enormous computation complexity for finding the optimal solution, we introduced a Quantum-inspired Evolutionary Algorithm (QEA) to iteratively provide the global best solution. Numerical results show that our proposed algorithm presents an excellent performance, which is far better than the strategy of only considering caching without deactivation mechanism in the actual, normal situation. We also provide performance comparison among our QEA, random sleeping algorithm and greedy algorithm, numerical results illustrate our introduced QEA performs best in accuracy and global optimality.
机译:通过引入缓存功能,异构蜂窝网络(HCN)被认为是5G时代的一项有前途的技术,它可以使内容更接近用户,从而减少传输延迟,节省稀缺的带宽资源。尽管已经为在HCN中进行缓存进行了许多工作,但是从能源的角度来看,考虑到大多数基站在大多数时间未得到充分利用的事实,仍有很大的空间来开发更节能的系统。因此,在本文中,通过考虑基站的激活机制,我们研究了联合缓存和激活机制设计以进一步提高能效,然后将优化问题表述为整数线性规划问题(ILP)最大化系统节能。由于寻找最佳解决方案的巨大计算复杂性,我们引入了量子启发进化算法(QEA)来迭代地提供全局最佳解决方案。数值结果表明,本文提出的算法具有很好的性能,远胜于在实际,正常情况下仅考虑缓存而不停用机制的策略。我们还提供了QEA,随机睡眠算法和贪婪算法之间的性能比较,数值结果表明我们引入的QEA在准确性和全局最优性方面表现最佳。

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