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作者(中文):馬振翔
作者(外文):Ma, Chen-Hsiang
論文名稱(中文):Design and Implementation of 3GPP-LTE MIMO-OFDM Baseband Processor with Reduced-Complexity MIMO Detector and Precode Codebook Searcher
論文名稱(外文):適用於3GPP-LTE之多輸入多輸出正交分頻多工處理器配合低複雜度檢測器與預編碼碼簿搜尋器之設計與實現
指導教授(中文):黃元豪
指導教授(外文):Huang, Yuan-Hao
口試委員(中文):蔡佩芸
黃穎聰
學位類別:碩士
校院名稱:國立清華大學
系所名稱:電機工程學系
學號:9761603
出版年(民國):100
畢業學年度:99
語文別:英文
論文頁數:104
中文關鍵詞:預編碼碼簿多輸入多輸出分頻正交第三代合作夥伴計畫-長期演進技術
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In recent decades, the demand of the communication devices increasing rapidly, so the
transmission technology of the communication devices is developed fast. The 3GPP-
LTE is one of the most popular specification in 4G mobile communication market.
In this thesis, we propose the design of a 4 × 4 MIMO-OFDM baseband downlink receiver
with low-complexity MIMO detection and codebook selection based on [8]. In order to
reduce the hardware cost from [8], we try to reduce the complexity in the algorithm
viewpoint and hardware sharing viewpoint. For example, because the MIMO detec-
tion which have lots 4 × 4 matrix operations is high complexity circuit, we adopt the
Strassen’s algorithm to reduce its complexity in hardware sharing viewpoint. Besides,
we demonstrate that the precoding matrix do not any effect for increasing the BER
performance in four-layer transmission case, so we could reduce the complexity for the
codebook selection algorithm by outputing a fixed index to transmitter in the algorithm
viewpoint.
Finally, we follow the cell-based design flow to implement the proposed design with
UMC Faraday 90nm CMOS technology, and we show the simulation results in nWave
and FPGA. Then, we compare proposed blocks with those in [8], and show how much
we improve.
在近十年中,人們對於通訊設備的需求與品質與日俱增,因此通訊設備的傳輸技術也迅速的蓬勃發展。以當今而言,多輸入多輸出分頻正交(MIMO-OFDM)則是目前無線通訊最主要的傳送技術,而本篇論文所研究的第三代合作夥伴計畫-長期演進技術(3GPP-LTE)則是使用這項技術並且是目前第四代通訊市場中相當熱門的一個技術。在本論文中,我們依據[8]提出一個多輸入輸出分頻正交(MIMO-OFDM)基頻處理器配合低複雜度檢測器與預編碼碼簿搜尋器。為了減少[8]的硬體,我們主要從減少演算法的複雜度與硬體共享這兩個方向的觀點下手。舉個例子,因為多天線多輸出檢測器擁有非常多的4x4複數矩陣乘法與複數加法,這對於設計來說是個相當大且複雜的電路,因此我們根據硬體共享的觀點,使用Strassen’s演算法來簡化這個電路的複雜度。此外我們證實了預編碼矩陣在四層傳輸中無法降低錯誤率,在我們得到這部分的結論後,我們回頭將有關於碼簿選擇的演算法做了一些修改,最後修改為在我們在四層傳輸的情況下會固定輸出一個預先設定好的數值,而這是從演算法上化簡的一個例子。最後,我們根據cell-based的設計流程,使用UMC 90nm cell library實現我們所提出的設計,另外,在我們的模擬成果是使用nWave與現場可編程邏輯閘陣列(FPGA)來呈現。此外,我們比較我們的架構與[8]的差別,並且呈現我們所增進的部分。
1 Introduction
1.1 Research Motivation
1.2 Organization of This Thesis
2 MIMO-OFDM and 3GPP LTE Standard
2.1 Multiple-Input Multiple-Output Technology
2.2 Orthogonal Frequency Division Multiplexing
2.2.1 Characteristics of OFDM Signal
2.2.2 FFT and IFFT
2.2.3 Cyclic Prefix
2.3 3GPP-LTE Standard[1]
2.3.1 Structure and Parameters
2.3.2 General Structure for Downlink Transmitter
2.3.3 Modulation Mapper
2.3.4 Layer Mapper
2.3.5 Precoding
2.3.6 Reference Signals
2.3.7 Synchronization Signals
3 Baseband Channel Model
3.1 3GPP Spatial Channel Model[2][3]
3.1.1 BS and UE Array Topologies and Spatial Parameters
3.1.2 General definitions and parameters
3.1.3 Environments
3.1.4 Channel Coefficients
3.2 Additive White Gaussian Noise
3.3 Carrier Frequency Offset
3.4 Sampling Clock Offset
4 Baseband Downlink MIMO Receiver System Design and Algorithm
4.1 Symbol Decision[4]
4.2 Carrier Frequency Offset Estimation and Compensation
4.2.1 Fractional Carrier Frequency Offset Estimation
4.2.2 Integral Carrier Frequency Offset Estimation
4.2.3 Carrier Frequency Offset Compensation
4.3 Sampling Clock Offset Estimation and Compensation
4.4 Channel Estimation
4.5 MIMO Detection
4.6 Codebook Selection[5]
5 The Complexity Reduction of MIMO Detection and Codebook Selection
5.1 The Complexity Reduction of MIMO Detection
5.1.1 Strassen’s Algorithm[6][7]
5.1.2 MIMO Detection with The Strassen’s Algorithm
5.2 Complexity Reduction of Codebook Selection
5.2.1 Combination between MSE Criterion and CS Criterion
5.2.2 Proof about Performance Evaluation for Different Codebook Index Feedback Time
5.2.3 Reducing Calculation Methodology
6 Hardware Implementation
6.1 Introduction
6.2 The Proposed MIMO Detection Circuit
6.3 The Proposed Codebook Selection Circuit
6.4 Fixed-point Simulation
6.5 Simulation
6.6 Comparison
7 Conclusion
[1] Evolved Universal Terrestrial Radio Access(E-UTRA); Physical Channels and Mudulation(Rel.10), 3GPP Std. TS 36.211, Rev. 10.0.0, Dec. 2010.
[2] Spatial channel model for Multiple Input Multiple Output (MIMO) simulations (Rel.8), 3GPP Std. TR 25.996, Rev. 8.0.0, Dec. 2008.
[3] J. Salo and G. Del Galdo and J. Salmmi, et al., “”MATLAB implementation of the 3GPP Spatial Channel Model (3GPP TR 25.996)”,” http://www.tkk.fi/Units/Radio/scm, Jan. 2005.
[4] E. Z. X. Z. H. Zhao and W.Wang, “”Synchronization Algorithm for MIMO OFDM
Systems”,” IEEE Commun. Society, Feb 2005.
[5] D. J. Love and R. W. H. Jr., “”Limited Feedback Unitary Precoding for Spatial
Multiplexing Systems”,” IEEE Trans. Inf. Theory, vol. 51, no. 8, Aug 2005.
[6] V. Strassen, “Gaussian elimination is not optimal,” in Numer. Math, 1969, vol. 13, pp. 354–356.
[7] S. M. Balle and P. C. Hansen, Advances in Parallel Algorithms. IOS Press, 1994, pp. 22–30.
[8] C.-C. Lee, “Design of a 4x4 MIMO-OFDM Down-Link Receiver for 3GPP-LTE,”
M. Eng. thesis, National Tsing Hua University, Hsinchu, Taiwan, Aug. 2009.
[9] Extending Codeword to Layer Mapping for Efficient Support of Restransmission,
3GPP Std. R1-074 382 Ericsson, 2007.
[10] Physical layer aspect for evolved Universal Terrestrial Radio Access (UTRA) (Rel.7), 3GPP Std. TR 25.814, Rev. 7.1.0, Oct. 2006.
[11] T.-D. Chiueh and P.-Y. Tsai, OFDM Baseband Receiver Design for Wireless Com-
munications. Wiley, 2007.
[12] (2010) Smims. [Online]. Available: http://www.smims.com/
 
 
 
 
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