标题： 干扰约束的D2D网络定价 显示英文标题

标题： Interference-Constrained Pricing for D2D Networks

摘要： 设备到设备（D2D）通信在蜂窝网络下的概念为提高系统性能带来了潜在的好处，但也带来了新的挑战，如干扰管理。 在本文中，我们提出了一种定价框架，用于从D2D用户到蜂窝系统的干扰管理，其中基站（BS）通过定价D2D用户引起的交叉层干扰来保护自己（或其服务的蜂窝用户）。 构建了一个斯塔克尔伯格博弈来模拟BS和D2D用户之间的互动。 具体来说，BS在干扰温度约束下设定价格以最大化其收益（或任何期望的效用）。 对于给定的价格，D2D用户竞争性地调整其功率分配策略以实现个体效用最大化。 我们首先通过非合作博弈理论分析D2D用户之间的竞争，并提出了一种基于迭代的分布式功率分配算法。 然后，根据BS了解的网络信息多少，我们开发了两种最优算法，一种是使用有限网络信息的统一定价，另一种是使用全局网络信息的差异化定价。 统一定价算法可以通过完全分布式的方式实现，并且需要BS和D2D用户之间最少的信息交换，而差异化定价算法是部分分布式的，并且不需要BS和D2D用户之间的迭代。 然后提出了一种次优的差异化定价方案以降低复杂度，并且可以以完全分布式的方式实现。 进行了大量仿真以验证所提出的框架和算法。 显示英文摘要

摘要： The concept of device-to-device (D2D) communications underlaying cellular networks opens up potential benefits for improving system performance but also brings new challenges such as interference management. In this paper, we propose a pricing framework for interference management from the D2D users to the cellular system, where the base station (BS) protects itself (or its serving cellular users) by pricing the crosstier interference caused from the D2D users. A Stackelberg game is formulated to model the interactions between the BS and D2D users. Specifically, the BS sets prices to a maximize its revenue (or any desired utility) subject to an interference temperature constraint. For given prices, the D2D users competitively adapt their power allocation strategies for individual utility maximization. We first analyze the competition among the D2D users by noncooperative game theory and an iterative based distributed power allocation algorithm is proposed. Then, depending on how much network information the BS knows, we develop two optimal algorithms, one for uniform pricing with limited network information and the other for differentiated pricing with global network information. The uniform pricing algorithm can be implemented by a fully distributed manner and requires minimum information exchange between the BS and D2D users, and the differentiated pricing algorithm is partially distributed and requires no iteration between the BS and D2D users. Then a suboptimal differentiated pricing scheme is proposed to reduce complexity and it can be implemented in a fully distributed fashion. Extensive simulations are conducted to verify the proposed framework and algorithms.