正交分頻多工系統之時變通道下頻率偏移估測研究;A Study of Carrier Frequency Offset Estimation in OFDM Systems for Time-Varying Channels

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题名:	正交分頻多工系統之時變通道下頻率偏移估測研究;A Study of Carrier Frequency Offset Estimation in OFDM Systems for Time-Varying Channels
作者:	鄭南宏;Cheng, Nan-Hung
贡献者:	通訊工程學系
关键词:	載波頻率偏移;正交分頻多工;時變通道;Carrier frequency offset (CFO);Orthogonal frequency-division multiplexing (OFDM);Time-varying channels
日期:	2021-07-12
上传时间:	2021-12-07 12:29:20 (UTC+8)
出版者:	國立中央大學
摘要:	正交頻分多重接取是一種基於正交頻分多工的多重接取技術。在正交頻分多重接取系統中，載波頻率偏移不僅會導致載波之間失去正交性，從而導致載波間干擾，而且還會影響該系統中的不同用戶，如多重接取干擾。因此，頻率同步是防止系統性能下降的重要任務。我們提出了三種演算法來估測時變通道下正交頻分多工系統中的載波頻率偏移。在第一個方法中，我們提出一個針對多輸入多輸出–正交分頻多工系統進行載波頻率偏移與頻率選擇性通道響應聯合估測的方法。首先介紹多輸入多輸出–正交分頻多工系統的訊號模式，再以最大似然解為前提發展一個聯合估測演算法。該演算法可以分為三部分：在第一個部分我們利用去旋轉法估計出初始載波頻率偏移，並將之作頻域等化。第二部分以迭代法求得頻率峰值以強化載波頻率偏移估測方面的效能。第三部分採用了自適應程序，以獲取更新的載波頻率偏移估測並追?時變參數，包括時變載波頻率偏移和時變通道。此方法在計算上的複雜度遠低於以最大似然為基礎的網格搜索法，且在模擬結果的均方差方面也極接近克拉美-羅下限。模擬結果顯示這個新提出的聯合估測演算法跟以完美情形作通道估測在位元錯誤率方面的表現極為接近。模擬結果亦表明，該方法在Jakes的通道模型中具有可靠的追?性能。在第二種方法當中，我們在正交分頻多重接取系統中利用一個簡單的疊代方案做為盲蔽式載波頻率偏移算法，用以降低複雜度，並以自適應方式提出了一種時變載波頻率偏移自適應估測方法。該演算法中可以分為二部分：在第一個部分使用初始粗略估測的載波頻率偏移，採用疊代法獲得載波頻率偏移的估測。第二部分是使用建議的自適應程序來獲取更新的載波頻率偏移估測並追?時變參數。模擬結果證明，所提出的疊代及自適應方案具有效能，並且得出的均方誤差接近克拉美-羅下限。第三個方法當中，我們提出了一種在正交分頻多重接取系統具有較強抗干擾能力的載波頻率偏移估測演算法。考慮了正交分頻多重接取中的異質網路環境。在提出的演算法的第一部分中，瞭解如何在異質網路或高密度小型基地台環境下處理接收到的信號，並開發處理載波頻率偏移估測問題。第二部分是使用建議的自適應程序來獲取更新的載波頻率偏移估測並跟?時變參數。模擬結果證明了該方法的有效性，其性能接近克拉美-羅下限。 ;Orthogonal frequency division multiple access (OFDMA) is a multiple access technique based on orthogonal frequency division multiplexing (OFDM). In OFDMA systems, carrier frequency offsets (CFOs) not only cause the loss of orthogonality among the carriers, which leads to the inter-carrier interference (ICI), but also influence the different users in this system, as multiple-access interferences (MAI). Hence, frequency synchronization is an important task to prevent the performance degradation of the system. We propose three algorithms for estimating CFO in OFDM Systems for Time-Varying Channels. In the first algorithm, we present a joint time-variant CFO and frequency-selective channel response estimation scheme for multiple input multiple output–orthogonal frequency-division multiplexing (MIMO–OFDM) systems for mobile users. The signal model of the MIMO–OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. In a simulation, the mean squared error performance of the proposed algorithm is close to the Cramer–Rao lower bound (CRB). The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. In the second algorithm, we propose simple iteration schemes for blind CFO estimation algorithms in OFDMA systems to reduce complexity with an adaptive manner and present a time-variant CFO adaptive estimation method. In the first part of the proposed algorithm, with initial rough estimated CFOs, it employs iterative methods to obtain CFO estimates. And the second part is to use proposed adaptive process to obtain the updated CFO estimation and track the parameters’ time-variations. The simulation results demonstrate the efficacy of the proposed iteration and adaptive schemes and the Mean Squared Errors (MSEs) are near to the CRBs. The third proposed algorithm, we propose a CFO estimation algorithm with strong interference resistant capability for OFDMA systems. Heterogeneous networks (HetNet) environments in OFDMA are considered. In the first part of the proposed algorithm, how received signals are processed under the HetNet scenarios/dense small cells to deal with the CFO estimation problem is developed. And the second part is to use the proposed adaptive process to obtain the updated CFO estimation and track the parameters’ time-variations. The simulation results demonstrate the effectiveness of this method and the performances are close to the CRBs.
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