Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems
Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems
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DOI：
10.1109/jstsp.2014.2334278
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发表时间：
2014-10-01
影响因子：
7.5
通讯作者：
Heath, Robert W., Jr.
中科院分区：
文献类型：
--
作者：
Alkhateeb, Ahmed;El Ayach, Omar;Heath, Robert W., Jr.
毫米波（mmWave）蜂窝系统将实现每秒千兆比特的数据速率，这要归功于mmWave频率下可用的大带宽。为了实现足够的链路裕度，毫米波系统将在发射器和接收器处采用具有大天线阵列的定向波束成形。由于千兆采样混合信号设备的高成本和功耗，毫米波预编码可能会在模拟和数字域之间划分。大量天线和模拟波束成形的存在要求开发特定于毫米波的信道估计和预编码算法。本文开发了一种自适应算法来估计毫米波信道参数，利用信道的散射性质差。为了使该算法的有效操作，一种新的分层多分辨率码本的设计，以构建不同的波束宽度的训练波束形成向量。对于单径信道，使用该算法的估计误差概率的上限推导，并得到一些见解的自适应阶段的算法之间的训练功率的有效分配。自适应信道估计算法，然后扩展到多径的情况下，依赖于信道的稀疏性。利用估计的信道，本文提出了一种新的混合模拟/数字预编码算法，克服了仅模拟波束形成的硬件限制，并接近数字解决方案的性能。仿真结果表明，所提出的低复杂度的信道估计算法实现了相当的预编码增益相比，穷举信道训练算法。仿真结果表明，在干扰存在的情况下，本文提出的信道估计和预编码算法可以逼近完全信道知识下的覆盖概率。
Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the large bandwidth available at mmWave frequencies. To realize sufficient link margin, mmWave systems will employ directional beamforming with large antenna arrays at both the transmitter and receiver. Due to the high cost and power consumption of gigasample mixed-signal devices, mmWave precoding will likely be divided among the analog and digital domains. The large number of antennas and the presence of analog beamforming requires the development of mmWave-specific channel estimation and precoding algorithms. This paper develops an adaptive algorithm to estimate the mmWave channel parameters that exploits the poor scattering nature of the channel. To enable the efficient operation of this algorithm, a novel hierarchical multi-resolution codebook is designed to construct training beamforming vectors with different beamwidths. For single-path channels, an upper bound on the estimation error probability using the proposed algorithm is derived, and some insights into the efficient allocation of the training power among the adaptive stages of the algorithm are obtained. The adaptive channel estimation algorithm is then extended to the multi-path case relying on the sparse nature of the channel. Using the estimated channel, this paper proposes a new hybrid analog/ digital precoding algorithm that overcomes the hardware constraints on the analog-only beamforming, and approaches the performance of digital solutions. Simulation results show that the proposed low-complexity channel estimation algorithm achieves comparable precoding gains compared to exhaustive channel training algorithms. The results illustrate that the proposed channel estimation and precoding algorithms can approach the coverage probability achieved by perfect channel knowledge even in the presence of interference.