In this paper, we investigate the resource allocation problem for a full-duplex (FD) massive multiple-input-multiple-output (mMIMO) multi-carrier (MC) decode and forward (DF) relay system which serves multiple MC single-antenna half-duplex (HD) nodes. In addition to the prior studies focusing on maximizing the sum-rate and energy efficiency, we focus on minimizing the overall delivery time for a given set of communication tasks to the user terminals. As our system is an FD MC system, we consider the impact of hardware distortions resulting in residual self-interference and inter-carrier leakage. We also consider that only limited channel state information is available. A joint power and sub-carrier allocation problem to maximize the sum-rate of the system is then formulated. Due to the intractable nature of the underlying problem, an iterative solution is proposed, employing the successive inner approximation (SIA) framework, with guaranteed convergence to the point that satisfies the Karush-Kuhn-Tucker (KKT) conditions. For the energy efficiency maximization problem, a two-stage iterative algorithm which follows the SIA and Dinkelbach algorithm is proposed. The operation of an FD mMIMO MC DF relay system is evaluated for different system parameters using numerical simulations. We also show the importance of considering delivery time minimization rather than sum-rate maximization, i.e., maximizing the sum-rate of the system does not necessarily minimize the overall delivery time. Numerical results show the significance of distortion-aware design for such systems and also the significant gain in terms of different objectives such as sum-rate, energy efficiency, and delivery time compared to its HD counterpart.

中文翻译：

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FD大规模MIMO中继网络的减损感知资源分配：总速率和交付时间优化观点

在本文中，我们研究了服务于多个MC单天线的全双工（FD）大规模多输入多输出（mMIMO）多载波（MC）解码和转发（DF）中继系统的资源分配问题半双工（HD）节点。除了专注于最大程度提高总效率和能效的现有研究之外，我们还专注于最大程度地缩短给定通信任务集到用户终端的总体交付时间。由于我们的系统是FD MC系统，因此我们考虑了硬件失真的影响，这会导致残留的自干扰和载波间泄漏。我们还认为只有有限的信道状态信息可用。然后制定了一个联合功率和子载波分配问题，以使系统的总速率最大化。由于潜在问题的棘手性质，提出了一种迭代方法，该方法采用了逐次内逼（SIA）框架，并保证了收敛到满足Karush-Kuhn-Tucker（KKT）条件的程度。针对能量效率最大化问题，提出了一种遵循SIA和Dinkelbach算法的两阶段迭代算法。使用数值模拟，针对不同的系统参数评估FD mMIMO MC DF中继系统的操作。我们还显示了考虑最小化交付时间而不是总和最大化的重要性，即，最大化系统的总和并不一定会最小化总交付时间。数值结果显示了此类系统的失真感知设计的重要性，以及在不同目标（例如总费率，能源效率，