In this paper, we consider a heterogeneous network consisting of both macro Base Station (MBS) and pico Base Stations (PBSs) in order to provide a spectrum allocation and mode selection in device-to-device (D2D) communications. A number of Component Carriers (CC) are considered available for allocation to the MBS and PBSs that are being utilized through carrier aggregation (CA) while mode selection decisions are made by each BS in order to balance between power consumption minimization and UE data rate requirements. A power minimization (energy-efficient) problem is formulated in order to provide a joint spectrum allocation and mode selection solution. This problem is solved using a state of the art optimization method known as proximal algorithm. First, a non-cooperative (centralized) solution is provided and second, a cooperative (distributed) employing distributed proximal algorithm is devised reducing the induced complexity. The cooperative solution is achieved by implementing distributed alternating direction method of multipliers (D-ADMM). Simulation results are carried out for all cases that reveal the energy efficient spectrum allocation and mode selection according under certain channels’ conditions that can balance between achieving high data rate requirements and power minimization. Finally, useful insights are presented such as complexity, convergence, delay and actual implementation of such a solution for the future wireless networks.

中文翻译：

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异构网络中D2D通信的高能效频谱分配和模式选择

在本文中，我们考虑由宏基站（MBS）和微微基站（PBS）组成的异构网络，以便在设备到设备（D2D）通信中提供频谱分配和模式选择。许多分量载波（CC）被认为可用于分配给通过载波聚合（CA）使用的MBS和PBS，同时每个BS做出模式选择决定，以便在功耗最小化和UE数据速率要求之间取得平衡。为了提供联合的频谱分配和模式选择解决方案，制定了功率最小化（节能）问题。使用称为近端算法的最先进的优化方法可以解决此问题。首先，提供非合作（集中）解决方案，其次，设计了一种采用分布式近端算法的协作（分布式）合作伙伴，以减少所引起的复杂性。协作解决方案是通过实现乘法器的分布式交替方向方法（D-ADMM）来实现的。针对所有情况进行了仿真结果，揭示了在某些信道条件下可以实现高数据速率要求和功率最小化之间平衡的节能频谱分配和模式选择。最后，提出了有用的见解，例如复杂性，收敛性，延迟以及这种解决方案对未来无线网络的实际实施。针对所有情况进行了仿真结果，揭示了在某些信道条件下可以实现高数据速率要求与功率最小化之间取得平衡的节能频谱分配和模式选择。最后，提出了有用的见解，例如复杂性，收敛性，延迟以及针对未来无线网络的这种解决方案的实际实现。针对所有情况进行了仿真结果，揭示了在某些信道条件下可以实现高数据速率要求与功率最小化之间取得平衡的节能频谱分配和模式选择。最后，提出了有用的见解，例如复杂性，收敛性，延迟以及针对未来无线网络的这种解决方案的实际实现。