通道估測且天線修正應用於毫米波混合式波束賦形系統

在毫米波波段中擁有頻寬大的優點，但為了補償高途徑損失，系統利用混合式波束賦形達到高傳輸速度。另一方面，大規模天線陣列也因毫米波長短而得以實現，若在分時多工系統下有通道互惠的特性，更可利用上行的通道設計下行通道的波束賦形。因此如何有效率的取得通道資訊應用於波束賦形將成為重要的課題，其主要的挑戰來自於兩個面相，第一點是大規模的天線矩陣讓取得通道資訊需要更多的訓練時間，第二點是在波束賦形前訊號為低訊雜比使得通道資訊無法準確估計。所幸毫米波在角度域上有稀少的特性，因此我們可以將毫米波的通道估測問題轉換成利用壓縮感知的最佳化問題解之。在此篇的論文中，我們利用傳統正交匹配追求演算法(OMP) 解出最佳解，此演算法將會被預設的閾值或是通道所擁有的路徑數所限制。然而，傳統的演算法並沒有將相似但不正確的抵達角(AoA)及出發角(AoD)對踢除，因此，在修正的正交匹配追求的演算法考慮此點，並且利用內插法的方式降低複雜度，避免使用高精準度的搜尋庫。此演算法特別適用於多路徑的通道之中。此外，在實際系統中，因接收路徑以及傳送路徑的電路增益不同使得通道互惠的特性被破壞。為了使上下行通道保持對稱，系統必須實行天線修正，而在考慮全陣列的混合式波束賦形下，我們利用空氣修正演算法來使通道互惠的特性重現。

關鍵字

混合式波束賦形；壓縮感知；大規模天線陣列；天線修正；通道估測；分時多工系統

並列摘要

In millimeter wave (mmWave) systems, hybrid beamforming is employed for compensating high pass loss due to its channel property and achieving high data rate thanks to the wide bandwidth. Therefore, in massive Multi-input Multi-Output (MIMO) and time division duplexing (TDD) systems, efficient channel estimation and antenna calibration are critical problems to guarantee the beamforming performance. The main challenge to channel estimation is under large scale antennas and low signal-to-noise ratio scenario before beamforming. Since mmWave channel is sparse in the angular domain, the channel estimation can be converted into compressive sensing problem. In conventional estimation by grid-based orthogonal matching pursuit (OMP), optimization problem is constrained by either threshold or known the number of paths. These methods do not consider those similar but correct angle of arrival(AoA) or angle of Departure (AoD) pairs. A modification of OMP algorithm is to not only check correct pairs but also minimize the quantization error. The proposed algorithm offers better accuracy to estimate pairs in multipath cases. In addition, the systems in TDD mode are able to leverage its benefit of the channel reciprocity. However, this symmetry does not hold due to RF chain mismatches. In this paper, antenna calibration is also discussed under hybrid beamforming structures by over-the-air technique in order to retrieve the channel reciprocity.

並列關鍵字

massive MIMO ； hybrid beamforming ； channel estimation ； compressive sensing ； antenna calibration ； channel reciprocity

參考文獻

[1] J. G. Andrews, S. Buzzi, W. Choi, S. V. Hanly, A. Lozano, A. C. K.Soong, and J. C. Zhang, “What will 5G be?” IEEE J. Select. Areas Commun., vol. 32, no. 6, pp. 1065–1082, June 2014.

[3] A. Alkhateeb, G. Leus, and R. W. H. Jr., “Compressed sensing based multi-user millimeter wave systems: How many measurements are needed?” pp. 2909–2913, Apr. 2015.

[4] A. Alkhateed, O. E. Ayach, G. Leus, and R. W. H. Jr., “Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems,”IEEE Journal of Selected Topic in Signal Processing, vol. 8, no. 5, pp. 831–846, Oct. 2014.

[6] S. Bazzi and W. Xu, “A Simple Over-the-Air Hardware Calibration Procedure in TDD systems,” Personal, Indoor, and Mobile Radio Communications, Sept. 2016.

[7] A. M. Sayeed, “Deconstructing Multiantenna Fading Channels,” IEEE Transactions on Signal Processing, Oct. 2002.

國際替代計量

通道估測且天線修正應用於毫米波混合式波束賦形系統

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