论文标题

具有有限的区块长传输的多源URLLC的波束形成设计

Beamforming Design for Multiuser uRLLC with Finite Blocklength Transmission

论文作者

He, Shiwen, An, Zhenyu, Zhu, Jianyue, Zhang, Jian, Huang, Yongming, Zhang, Yaoxue

论文摘要

在物联网(IoT)设备的爆炸性增长的驱动下,对延迟和可靠性,超可靠性和低潜伏期通信(URLLC)的要求很严格,已成为第五代(5G)和5G通信系统以外的三个关键通信方案之一。在本文中,我们重点介绍了下行链路多用户URLLC系统的波束形成设计问题。由于对可靠性和延迟的严格需求通常,简短的数据包传输是URLLC系统的有利形式,这表明文献不再适用Shannon的容量公式。通过有限的区块变速器,可实现的交付速率在很大程度上受到可靠性和延迟的影响。使用开发的可实现的输送率公式进行有限的区块长度传输,我们分别通过考虑最大的允许传输功率和最小速率要求,分别将感兴趣的问题作为加权总和最大化,能源效率最大化和用户公平性优化。值得指出的是,这是为下行链路多用户URLLC系统设计波束成形向量的第一项工作。为了解决这些非凸问题,通过分析可实现的交付率的功能,发现了一些重要的见解。例如,最低率要求可以通过低限制的信噪比加上噪声比率来实现。根据发现的结果,我们提供了算法来优化波束成型向量和功率分配,这些载体分配可以保证将其融合到具有低计算复杂性的配方问题的局部最佳解决方案。我们的仿真结果表明,我们提出的波束形成算法的表现优于现有文献中广泛使用的相等功率分配的零强度波束形成算法。

Driven by the explosive growth of Internet of Things (IoT) devices with stringent requirements on latency and reliability, ultra-reliability and low latency communication (uRLLC) has become one of the three key communication scenarios for the fifth generation (5G) and beyond 5G communication systems. In this paper, we focus on the beamforming design problem for the downlink multiuser uRLLC systems. Since the strict demand on the reliability and latency, in general, short packet transmission is a favorable form for uRLLC systems, which indicates the literature Shannon's capacity formula is no longer applicable. With the finite blocklength transmission, the achievable delivery rate is greatly influenced by the reliability and latency. Using the developed achievable delivery rate formula for finite blocklength transmission, we respectively formulate the problems of interest as the weighted sum rate maximization, energy efficiency maximization, and user fairness optimization by considering the maximum allowable transmission power and minimum rate requirement. It's worthy pointing out that this is the first work to design the beamforming vectors for the downlink multiuser uRLLC systems. To address these non-convex problems, some important insights have been discovered by analyzing the function of achievable delivery rate. For example, the minimum rate requirement can be realized by low bounded the signal-to-interference-plus-noise ratio. Based on the discovered results, we provide algorithms to optimize the beamforming vectors and power allocation, which are guaranteed to converge to a local optimum solution of the formulated problems with low computational complexity. Our simulation results reveal that our proposed beamforming algorithms outperform the zero-forcing beamforming algorithm with equal power allocation widely used in the existing literatures.

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