Compressive Initial Access and Beamforming Training for Millimeter-Wave Cellular Systems
Compressive Initial Access and Beamforming Training for Millimeter-Wave Cellular Systems
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DOI：
10.1109/jstsp.2019.2931206
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发表时间：
2019-01
影响因子：
7.5
通讯作者：
Han Yan;D. Cabric
中科院分区：
文献类型：
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作者：
Han Yan;D. Cabric
初始接入 (IA) 是蜂窝系统中的基本过程，其中用户设备 (UE) 检测基站 (BS) 并获取同步。由于毫米波（mmW）系统中需要使用天线阵列进行IA，BS同时进行波束训练以获取角度信道状态信息。最先进的定向 IA (DIA) 在 IA 中使用一组窄探测波束，依次测量不同的波束对，并确定最佳候选波束。然而，定向波束训练精度取决于扫描波束角分辨率，因此其改进需要额外的专用无线电资源、接入延迟和开销。为了解决DIA中的接入延迟和开销问题，本文提出使用准全向伪随机探测波束进行IA，并开发了一种无需额外无线电资源的联合初始接入和精细分辨率初始波束训练的算法。它全面模拟 IA 中遇到的实际定时和频率同步误差。我们分析了所提出的算法在定时同步误差下的漏检率，并考虑到 5G-NR 兼容的 IA 程序，进一步推导了频率偏移下的 Cramér–Rao 角度估计下界。为了适应 5G 以上标准演进中波束训练带宽不断增加的情况，我们设计了波束斜视鲁棒算法。对于 mmW 通道下的实际性能评估，我们在 28 GHz 下使用带有 mmMAGIC 模型的 QuaDRiGa 模拟器，以表明所提出的方法对 DIA 是有利的。当以相同的发现、训练后 SNR 和开销性能为目标时，与 DIA 相比，所提出的算法可以节省几个数量级的访问延迟。这一结论在半径高达 140 m 的毫米波微微蜂窝的各种传播环境和三维位置中均成立。此外，我们的结果表明，所提出的波束斜视鲁棒算法能够通过增加波束训练带宽来保持不受影响的性能。
Initial access (IA) is a fundamental procedure in cellular systems where user equipment (UE) detects base station (BS) and acquires synchronization. Due to the necessity of using antenna arrays for IA in millimeter-wave (mmW) systems, BS simultaneously performs beam training to acquire angular channel state information. The state-of-the-art directional IA (DIA) uses a set of narrow sounding beams in IA, where different beam pairs are sequentially measured, and the best candidate is determined. However, the directional beam training accuracy depends on scanning beam angular resolution, and consequently its improvement requires additional dedicated radio resources, access latency, and overhead. To remedy the problem of access latency and overhead in DIA, this paper proposes to use quasi-omni pseudorandom sounding beams for IA, and develops an algorithm for joint initial access and fine resolution initial beam training without requiring additional radio resources. It comprehensively models realistic timing and frequency synchronization errors encountered in IA. We provide the analysis of the proposed algorithm's miss detection rate under timing synchronization errors, and we further derive Cramér–Rao lower bound of angular estimation under frequency offset, considering the 5G-NR compliant IA procedure. To accommodate the ever increasing bandwidth for beam training in standard evolution beyond 5G, we design the beam squint robust algorithm. For realistic performance evaluation under mmW channels, we use QuaDRiGa simulator with mmMAGIC model at 28 GHz to show that the proposed approach is advantageous to DIA. The proposed algorithm offers orders of magnitude access latency saving compared to DIA, when the same discovery, post training SNR, and overhead performance are targeted. This conclusion holds true in various propagation environments and three-dimensional locations of a mmW pico-cell with up to 140 m radius. Furthermore, our results demonstrate that the proposed beam squint robust algorithm is able to retain unaffected performance with increased beam training bandwidth.