This paper considers wireless-powered relaying multiple-input-multiple-output (MIMO) communication, where all four nodes (information source, energy source, relay, and destination) are equipped with multiple antennas. Orthogonal frequency division multiplexing (OFDM) is applied for information processing to compensate the frequency selectivity of communication channels between the information source and the relay and between the relay and the destination as these nodes are assumed to be located far apart from each. The relay is equipped with a full-duplexing interface for harvesting energy not only from the wireless transmission of the dedicated energy source but also from its own transmission while relaying the source information to the destination. The problem of designing the optimal power allocation over OFDM subcarriers and transmit antennas to maximize the overall spectral efficiency is addressed. Due to a very large number of subcarriers, this design problem poses a large-scale nonconvex optimization problem involving a few thousand variables of power allocation, which is very computationally challenging. A novel path-following algorithm is proposed for computation. Based on the developed closed-form calculation of linear computational complexity at each iteration, the proposed algorithm rapidly converges to an optimal solution. Compared to the best existing solvers, the computational complexity of the proposed algorithm is reduced at least 105 times, making it very efficient and practical for online computation while existing solvers are ineffective. Numerical results for a practical simulation setting show promising results by achieving high spectral efficiency.

中文翻译：

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具有能量回收接口的基于 MIMO-OFDM 的无线供电中继通信

本文考虑无线供电中继多输入多输出 (MIMO) 通信，其中所有四个节点（信息源、能源、中继和目的地）都配备了多个天线。正交频分复用 (OFDM) 用于信息处理以补偿信息源和中继之间以及中继和目的地之间的通信信道的频率选择性，因为这些节点被假定为彼此相距很远。中继器配备全双工接口，不仅可以从专用能量源的无线传输中获取能量，还可以从自身传输中获取能量，同时将源信息中继到目的地。解决了设计 OFDM 子载波和发射天线上的最佳功率分配以最大化整体频谱效率的问题。由于子载波数量非常多，这个设计问题带来了涉及数千个功率分配变量的大规模非凸优化问题，这在计算上非常具有挑战性。提出了一种新的路径跟踪算法进行计算。基于在每次迭代中开发的线性计算复杂度的封闭形式计算，所提出的算法快速收敛到最优解。与现有的最佳求解器相比，该算法的计算复杂度至少降低了 105 倍，使其在现有求解器无效的情况下在线计算非常有效和实用。