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PHY-Supported Frame Aggregation for Wireless Local Area Networks

机译:无线局域网中PHY支持的帧聚合

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An aggregate medium access control (MAC) service data unit (A-MSDU) contains multiple subframes with a single sequence number. Hence, it has a major drawback in environments with high error rates because if any subframes are corrupted, then the entire A-MSDU will be lost. In addition, performance of the A-MSDU depends strongly on the choice of parameters, such as frame size, modulation level, coding rate, and spatial mode. In this paper, a novel link-adaptation mechanism, dubbed physical (PHY)-supported frame aggregation (PSFA), is proposed over IEEE 802.11 networks, and its performance is analyzed. The proposed PSFA technique is based on a cross-layer interaction that enables joint optimization of various parameters between the PHY and MAC layers. This paper derives a new packet error rate (PER) expression for convolutionally coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems as an example. Then, this PER expression is used to efficiently estimate the link quality, given the channel conditions and system parameters, and most importantly, it is able to facilitate a parametric study of the cross-layer interaction. In the proposed PSFA algorithm, we present a rule for selecting the parameters so that MAC throughput is maximized. It is shown analytically and verified using Monte Carlo simulations that this choice of parameters can improve throughput performance significantly and also ensure quality of service (QoS) requirements compared to existing conventional algorithms.
机译:聚合媒体访问控制(MAC)服务数据单元(A-MSDU)包含具有单个序列号的多个子帧。因此,它在具有高错误率的环境中具有主要缺点,因为如果任何子帧被破坏,则整个A-MSDU将丢失。此外,A-MSDU的性能在很大程度上取决于对参数的选择,例如帧大小,调制级别,编码率和空间模式。本文提出了一种新的链路自适应机制,称为物理(PHY)支持的帧聚合(PSFA),它通过IEEE 802.11网络进行了性能分析。所提出的PSFA技术基于跨层交互,该交互使PHY和MAC层之间各种参数的联合优化成为可能。本文以卷积编码多输入多输出正交频分复用(MIMO-OFDM)系统为例,推导了一种新的误包率(PER)表达式。然后,在给定信道条件和系统参数的情况下,此PER表达式可用于有效地估计链路质量,最重要的是,它能够促进跨层交互的参数研究。在提出的PSFA算法中,我们提出了一个选择参数的规则,以使MAC吞吐量最大化。分析显示并使用蒙特卡洛模拟进行验证,与现有的常规算法相比,这种参数选择可以显着提高吞吐量性能,并确保服务质量(QoS)要求。

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