In this paper, we investigate joint subcarrier (SC) allocation, pairing and power loading for optimized energy efficiency (EE) in multiuser, multicell, multicarrier downlink decode-and-forward (DF) relay interference networks with computational awareness, i.e., taking computations-related energy into account. In order to maximize EE of the network, the transmission mode is adapted to instantaneous channel conditions. For the benefit of spectral-efficiency, both direct- and relayed transmission is allowed to use the same SCs simultaneously. Linearly rate-dependent power consumption of signal processing is considered. The formulated optimization problem is the nonconvex fractional mixed binary-integer programming problem, which has NP-hard complexity. Hence, we approximate the problem by the series of equivalent convex problems applying convex relaxation techniques such as a Successive Convex Approximation (SCA). Based on these transformations, we develop an iterative algorithm exploiting the Dinkelbach method to tackle the nonlinear fractional programming problem which maximizes EE of the system. Moreover, in our considerations, the total transmission power constraint and the minimum required rate constraints have been included. Simulation results demonstrate the effectiveness of our solution for future relay networks.

中文翻译：

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具有计算意识的节能无线中继网络

在本文中，我们研究了具有计算意识的多用户、多小区、多载波下行链路解码转发 (DF) 中继干扰网络中优化能效 (EE) 的联合副载波 (SC) 分配、配对和功率负载，即进行计算- 相关的能量考虑在内。为了最大化网络的EE，传输模式适应瞬时信道条件。为了频谱效率的好处，允许直接传输和中继传输同时使用相同的 SC。考虑了信号处理的线性速率相关功耗。公式化的优化问题是非凸分数阶混合二元整数规划问题，具有 NP-hard 复杂度。因此，我们通过应用凸松弛技术（例如连续凸逼近 (SCA)）的一系列等效凸问题来近似该问题。基于这些转换，我们开发了一种迭代算法，利用 Dinkelbach 方法来解决非线性分数规划问题，从而最大化系统的 EE。此外，在我们的考虑中，已包括总传输功率约束和最小所需速率约束。仿真结果证明了我们的解决方案对未来中继网络的有效性。包括总传输功率约束和最低要求速率约束。仿真结果证明了我们的解决方案对未来中继网络的有效性。包括总传输功率约束和最低要求速率约束。仿真结果证明了我们的解决方案对未来中继网络的有效性。