Underlay device-to-device (D2D) communications improve the spectral efficiency by simultaneously allowing direct communication between D2D-users on the same channels as cellular-users (CUs). However, most related works consider perfect channel-state-information (CSI) with single-antenna transmissions and usually assign each channel to one D2D pair. In this work, we formulate an optimization problem for maximizing the aggregate rate of all D2D pairs and CUs in single and multiple antenna configurations under imperfect CSI, by optimizing channel and power resources. Our formulation guarantees probability of outage below a specified threshold and fairness in channel allocation across D2D pairs. The resulting problem is a stochastic-mixed-integer-non-convex problem, we solve it approximately by alternating between power-allocation and channel-assignment sub-problems. The stochastic objective and outage constraints are addressed by the concept of order-of-statistics in the single-antenna case and the Bernstein-type inequality in the multiple-antenna configuration. The power-allocation sub-problem is solved by exploiting a quadratic-transformation, while the channel-assignment sub-problem is solved by integer relaxation. Furthermore, two computationally efficient algorithms are proposed to approximately solve the problem in a partially decentralized manner. We also establish convergence guarantees for the different algorithms proposed in this work. Simulation results show that the proposed approach achieves higher throughput compared to the state-of-the-art alternatives.

中文翻译：

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具有多天线和不完美 CSI 的底层干扰 D2D 网络的资源分配

底层设备到设备 (D2D) 通信通过同时允许 D2D 用户在与蜂窝用户 (CU) 相同的信道上进行直接通信来提高频谱效率。然而，大多数相关工作都考虑了具有单天线传输的完美通道状态信息 (CSI)，并且通常将每个通道分配给一个 D2D 对。在这项工作中，我们制定了一个优化问题，通过优化信道和功率资源，在不完美的 CSI 下最大化单天线和多天线配置中所有 D2D 对和 CU 的聚合速率。我们的公式保证了低于指定阈值的中断概率和跨 D2D 对的通道分配的公平性。由此产生的问题是一个随机混合整数非凸问题，我们通过在功率分配和信道分配子问题之间交替来近似解决它。随机目标和中断约束通过单天线情况下的统计顺序概念和多天线配置中的伯恩斯坦型不等式来解决。功率分配子问题通过利用二次变换来解决，而信道分配子问题通过整数松弛来解决。此外，提出了两种计算效率高的算法，以部分分散的方式近似地解决该问题。我们还为这项工作中提出的不同算法建立了收敛保证。仿真结果表明，与最先进的替代方案相比，所提出的方法实现了更高的吞吐量。随机目标和中断约束通过单天线情况下的统计顺序概念和多天线配置中的伯恩斯坦型不等式来解决。功率分配子问题通过利用二次变换来解决，而信道分配子问题通过整数松弛来解决。此外，提出了两种计算效率高的算法，以部分分散的方式近似地解决该问题。我们还为这项工作中提出的不同算法建立了收敛保证。仿真结果表明，与最先进的替代方案相比，所提出的方法实现了更高的吞吐量。随机目标和中断约束通过单天线情况下的统计顺序概念和多天线配置中的伯恩斯坦型不等式来解决。功率分配子问题通过利用二次变换来解决，而信道分配子问题通过整数松弛来解决。此外，提出了两种计算效率高的算法，以部分分散的方式近似地解决该问题。我们还为这项工作中提出的不同算法建立了收敛保证。仿真结果表明，与最先进的替代方案相比，所提出的方法实现了更高的吞吐量。