Energy Minimization via Joint Caching and Power Control in Wireless Heterogeneous Networks

We study the problem of minimizing energy costs for content delivery in wireless heterogeneous networks by jointly optimizing caching and power control strategies. This can be equivalently cast as a problem of maximizing the joint caching and power gain subject to meeting minimum signal-to-interference-plus-noise ratio constraints. The offline version of this problem is NP-hard, but we show that there exist polynomial-time approximation algorithms producing solutions within a constant factor 1 - 1/ $e$ from the optimal. We further provide an adaptive algorithm based on projected subgradient ascent over a concave relaxation of the expected joint caching and power gain, which yields the same approximation guarantee. We show that our proposed algorithm outperforms the alternating optimization method and other baseline algorithms in a number of network scenarios, in total power consumption and run time.

我们通过联合优化缓存和功率控制策略来研究无线异构网络中内容交付的能量成本最小化问题。这可以等效地表述为在满足最小信干噪比约束的条件下最大化联合缓存和功率增益的问题。这个问题的离线版本是NP难的，但我们表明存在多项式时间近似算法，其产生的解与最优解的差距在常数因子$1 - \frac{1}{e}$之内。我们进一步提供了一种基于在期望联合缓存和功率增益的凹松弛上的投影次梯度上升的自适应算法，它具有相同的近似保证。我们表明，在许多网络场景中，我们提出的算法在总功耗和运行时间方面优于交替优化方法和其他基准算法。