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A joint optimization method for data offloading in D2D-enabled cellular networks

机译:启用D2D的蜂窝网络中数据卸载的联合优化方法

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Device-to-device (D2D) communication is a promising technique for traffic offloading in next-generation cellular systems. In this paper, we study the D2D-assisted cellular traffic offloading (DACTO) problem, where Wi-Fi Direct technology is employed in D2D communication in consideration of its wide communication coverage and high transmission rate. Taking into account the user traffic demands and population distributions, we formulate the DACTO problem as a "Min-Max" problem, in which the operator energy consumption is minimized and meanwhile the user satisfaction is maximized. The DACTO is proven to be a NP-complete problem and is difficult to tackle with the increasing number of population. To achieve a feasible solution, we convert the DACTO problem into an approximate combination optimization problem, and develop a backpack algorithm combined with an improved Hungarian algorithm to solve it. Simulation results show that the proposed method achieves the near-optimal solution for the DACTO problem.
机译:设备到设备(D2D)通信是用于下一代蜂窝系统中的流量分流的一种有前途的技术。在本文中,我们研究了D2D辅助的蜂窝流量卸载(DACTO)问题,考虑到其广泛的通信覆盖范围和高传输速率,在D2D通信中采用了Wi-Fi Direct技术。考虑到用户流量需求和人口分布,我们将DACTO问题表述为“最小-最大”问题,在该问题中,运营商的能耗降到了最低,同时用户满意度得到了最大化。 DACTO被证明是一个NP完全问题,并且随着人口数量的增加而难以解决。为了实现可行的解决方案,我们将DACTO问题转换为近似组合优化问题,并开发了一种与改进的匈牙利算法相结合的背包算法来解决该问题。仿真结果表明,所提出的方法解决了DACTO问题的近似最优解。

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