The bootstrap in ATSC 3.0 is expected to act as a universal wake-up signal for various wireless systems in addition to broadcast network. However, the signaling decoding performance of the standardized bootstrap degrades significantly in channels of fast time-variation and strong multipath. Furthermore, part of available bandwidth is reserved to ensure the compatibility with mobile communication network (MCN), which puts a limitation on the performance improvement. In this paper, to make the best of the available bandwidth, we introduce the bandwidth-concerned version information to enable an adaptive bandwidth configuration for the proposed bootstrap. Moreover, a 2-D signaling scheme is used to increase signaling capacity by selecting different gold sequences in frequency domain (FD) and simultaneously applying cyclic shift in time domain (TD). At the receiver side, we first provide improved estimators of symbol timing offset (STO) and fine frequency offset (FFO) for the bootstrap with special TD structure. Meanwhile, a learning-based binary classifier taking the output of STO estimator as training data is provided to generate an SNR-independent threshold for spectrum sensing without requiring the knowledge of channel conditions nor noise estimator. Afterwards, an inverse fast Fourier transform (IFFT)-based algorithm is used to decode FD signaling in the presence of unknown TD signaling, which allows 3-bit higher signaling capacity. Numerical analysis and simulation results demonstrate that the proposed adaptive bootstrap design as well as corresponding receiver algorithms significantly outperform the standardized one in terms of synchronization, detection and signaling decoding.

中文翻译：

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混合地面广播和移动通信网络的自适应引导设计

除了广播网络之外，ATSC 3.0 中的引导程序有望充当各种无线系统的通用唤醒信号。然而，标准化自举的信令解码性能在快速时变和强多径的信道中显着下降。此外，为了保证与移动通信网络（MCN）的兼容性，保留了部分可用带宽，这限制了性能提升。在本文中，为了充分利用可用带宽，我们引入了与带宽相关的版本信息，以便为所提议的引导程序启用自适应带宽配置。此外，2-D 信令方案用于通过在频域 (FD) 中选择不同的黄金序列并同时在时域 (TD) 中应用循环移位来增加信令容量。在接收端，我们首先为具有特殊 TD 结构的引导程序提供改进的符号时序偏移 (STO) 和精细频率偏移 (FFO) 估计器。同时，提供了一种以 STO 估计器的输出作为训练数据的基于学习的二元分类器，以生成与 SNR 无关的频谱感知阈值，而无需了解信道条件和噪声估计器。之后，在存在未知 TD 信令的情况下，使用基于逆快速傅里叶变换 (IFFT) 的算法对 FD 信令进行解码，这允许 3 位更高的信令容量。数值分析和仿真结果表明，所提出的自适应引导设计以及相应的接收器算法在同步、检测和信令解码方面明显优于标准化算法。