Due to the continuous advancements of orthogonal frequency division multiplexing (OFDM) and multiple antenna techniques, multiuser multiple input multiple output (MU-MIMO) OFDM is a key enabler of both fourth and fifth generation networks. In this paper, we consider the problem of weighted sum-rate maximization under latency constraints in finite buffer multicell MU-MIMO OFDM systems. Unlike previous works, the optimization variables include the transceiver beamforming vectors, the scheduled packet size and the resources in the frequency and power domains. This problem is motivated by the observation that multicell MU-MIMO OFDM systems serve multiple quality of service classes and the system performance depends critically on both the transceiver design and the scheduling algorithm. Since this problem is non-convex, we resort to the max-plus queuing method and successive convex approximation. We propose both centralized and decentralized solutions, in which practical design aspects, such as signaling overhead, are considered. Finally, we compare the proposed framework with state-of-the-art algorithms in relevant scenarios, assuming a realistic channel model with space, frequency and time correlations. Numerical results indicate that our design provides significant gains over designs based on the wide-spread saturated buffers assumption, while also outperforming algorithms that consider a finite-buffer model. Due to the continuous advancements of orthogonal frequency division multiplexing (OFDM) and multiple antenna techniques, multiuser multiple input multiple output (MU-MIMO) OFDM is a key enabler of both fourth and fifth generation networks. In this paper, we consider the problem of weighted sum-rate maximization under latency constraints in finite buffer multicell MU-MIMO OFDM systems. Unlike previous works, the optimization variables include the transceiver beamforming vectors, the scheduled packet size and the resources in the frequency and power domains. This problem is motivated by the observation that multicell MU-MIMO OFDM systems serve multiple quality of service classes and the system performance depends critically on both the transceiver design and the scheduling algorithm. Since this problem is non-convex, we resort to the max-plus queuing method and successive convex approximation. We propose both centralized and decentralized solutions, in which practical design aspects, such as signaling overhead, are considered. Finally, we compare the proposed framework with state-of-the-art algorithms in relevant scenarios, assuming a realistic channel model with space, frequency and time correlations. Numerical results indicate that our design provides significant gains over designs based on the wide-spread saturated buffers assumption, while also outperforming algorithms that consider a finite-buffer model.

中文翻译：

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多小区 MU-MIMO 系统中时延约束下实现总速率最大化的联合资源分配和收发器设计


由于正交频分复用 (OFDM) 和多天线技术的不断进步，多用户多输入多输出 (MU-MIMO) OFDM 是第四代和第五代网络的关键推动因素。在本文中，我们考虑有限缓冲区多小区 MU-MIMO OFDM 系统中延迟约束下的加权和速率最大化问题。与之前的工作不同，优化变量包括收发器波束成形向量、调度的数据包大小以及频域和功率域中的资源。这个问题的产生是由于多小区 MU-MIMO OFDM 系统服务于多种服务质量等级，并且系统性能主要取决于收发器设计和调度算法。由于这个问题是非凸的，我们采用最大加排队方法和逐次凸逼近。我们提出了集中式和分散式解决方案，其中考虑了实际设计方面，例如信令开销。最后，我们假设具有空间、频率和时间相关性的现实信道模型，将所提出的框架与相关场景中最先进的算法进行比较。数值结果表明，与基于广泛饱和缓冲区假设的设计相比，我们的设计提供了显着的增益，同时也优于考虑有限缓冲区模型的算法。由于正交频分复用 (OFDM) 和多天线技术的不断进步，多用户多输入多输出 (MU-MIMO) OFDM 是第四代和第五代网络的关键推动因素。 在本文中，我们考虑有限缓冲区多小区 MU-MIMO OFDM 系统中延迟约束下的加权和速率最大化问题。与之前的工作不同，优化变量包括收发器波束成形向量、调度的数据包大小以及频域和功率域中的资源。这个问题的产生是由于观察到多小区 MU-MIMO OFDM 系统服务于多种服务质量等级，并且系统性能主要取决于收发器设计和调度算法。由于这个问题是非凸的，我们采用最大加排队方法和逐次凸逼近。我们提出了集中式和分散式解决方案，其中考虑了实际设计方面，例如信令开销。最后，我们假设具有空间、频率和时间相关性的现实信道模型，将所提出的框架与相关场景中最先进的算法进行比较。数值结果表明，与基于广泛饱和缓冲区假设的设计相比，我们的设计提供了显着的增益，同时也优于考虑有限缓冲区模型的算法。