臺灣博碩士論文加值系統

空間多工輔助廣義空間調變(Spatial Multiplexing Aided Generalized Spatial Modulation, SMx-GSM)本質上是結合了垂直貝爾實驗室分層空時結構 (Vertical Bell Labs Layered Space-Time) 跟空間調變 (Generalized Spatial Modulation, GSM)來達到高傳輸速率的技術。在傳送端，將傳送天線分割成數個群組，而每一個群組都是使用GSM來作調變，因此不需要大量的射頻(Radio Frequency chain)電路且在接收端不會造成嚴重的多通道干擾(Inter-Channel Interference)。跟一般的廣義空間調變(Generalized Spatial Modulation)比起來，藉由SMx-GSM符元之特性，使得高傳輸速率系統得以實現。
在本篇論文中，我們提出了一種低複雜度的偵測器適用於SMx-GSM，是使用樹狀搜尋演算法並利用低複雜度的比較公式來找尋事後機率比較大的天線組合跟訊號之集合來去作最佳偵測。從模擬的結果來看，不僅能大幅降低偵測複雜度，使得高傳輸速率的系統具有可行性。

Spatial-Multiplexing aided Generalized Spatial Modulation (SMx-GSM) is essentially a combination of Vertical Bell Labs Layered Space-Time and Generalized Spatial Modulation (GSM) to achieve a high transmission rate technology. In transmitter, the transmit antennas are divided into several groups and each group use GSM technique. Therefore, we don’t need a lot of Radio Frequency chain to transmit signal and will not cause serious inter-channel interference. Compare to the conventional GSM, we can implement high transmission rate system by using the characteristics of SMx-GSM symbols at receiver.
In this thesis, we explain a low-complexity detector for SMx-GSM. We use tree search algorithm and utilize a low-complexity cost function to find a set of transmit antenna combinations with maximum a posteriori probability for optimal detection. From the results of the simulation, the detection complexity can be greatly reduced, that make high-rate system feasible.

論文審定書 i
誌謝 ii
中文摘要 iii
ABSTRACT iv
CONTENT v
圖次 vii
表次 ix
Chapter 1 導論 1
1.1 研究動機 3
1.2 論文架構 3
Chapter 2 系統介紹 5
2.1 多輸入多輸出系統之介紹 5
2.1.1 空間多樣 5
2.1.2 空間多工 6
2.2 空間調變系統之基本架構 7
Chapter 3 空間多工輔助空間調變系統之偵測器 10
3.1 閘值輔助壓縮感知偵測器 11
3.2 碼字輔助樹狀搜尋偵測器 13
Chapter 4 空間多工輔助廣義空間調變系統之偵測器 19
4.1 閘值輔助壓縮感知偵測器 20
4.2 碼字輔助樹狀搜尋偵測器 22
Chapter 5 模擬結果與討論 24
5.1 空間多工輔助空間調變偵測器之錯誤率與複雜度比較 24
5.2 空間多工輔助廣義空間調變偵測器之錯誤率與複雜度比較 36
Chapter 6 結論 39
參考文獻 40
中英對照表 46
縮寫對照表 49

[1]S. Alamouti, “A simple transmit diversity technique for wireless communications,” IEEE J. Sel. Areas Commun., vol. 16, no. 8, pp. 1451–1458, Oct. 1998.
[2]V. Tarokh, N. Seshadri, and A. Calderbank, “Space-time codes for high data rate wireless communication: Performance criterion and code construction,” IEEE Trans. Inf. Theory, vol. 44, no. 2, pp. 744–765, Mar. 1998.
[3]H. El Gamal, “On the robustness of space-time coding,” IEEE Trans. Signal Process., vol. 50, no. 10, pp. 2417–2428, Oct. 2002.
[4]G. J. Foschini, “Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas,” Bell Labs Tech. J., vol. 1, no. 2, pp. 41–59, Sep. 1996.
[5]L. Lu, G. Y. Li, A. L. Swindlehurst, A. Ashikhmin, and R. Zhang, “An overview of massive MIMO: benefits and challenges,” IEEE J. Sel. Topics Signal Process., vol. 8, no. 5, pp. 742–758, Oct. 2014.
[6]E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, “Massive MIMO for next generation wireless systems,” IEEE Commun. Mag., vol. 52, no. 2, pp. 186–195, Feb. 2014.
[7]S. Wang, Y. Li, M. Zhao, and J. Wang, “Energy efficient and low-complexity uplink transceiver for massive spatial modulation MIMO,” IEEE Trans. Veh. Technol., vol. 64, no. 10, pp. 4617–4632, Oct. 2015.
[8]C. T. Lin, W.R. Wu, and C. Y. Liu, “Low-complexity ML detectors for generalized spatial modulation systems,” IEEE Trans. Commun., vol. 63, no. 11, pp. 4214–4230, Nov. 2015.
[9]Y. Xiao, Z. Yang, L. Dan, P. Yang, L. Yin, and W. Xiang, “Low complexity signal detection for generalized spatial modulation,” IEEE Commun. Lett., vol. 18, no. 3, pp. 403–406, Mar. 2014.
[10]C. E. Chen, C. H. Li, and Y. H. Huang, “An improved ordered-block MMSE detector for generalized spatial modulation,” IEEE Commun. Lett., vol. 19, no. 5, pp. 707–710, May 2015.
[11]R. Mesleh, H. Haas, S. Sinanovic, C. W. Ahn, and S. Yun, “Spatial modulation,” IEEE Trans. Veh. Technol., vol. 57, no. 4, pp. 2228–2241, July 2008.
[12]J. Jeganathan, A. Ghrayeb, and L. Szczecinski, “Spatial modulation: optimal detection and performance analysis,” IEEE Commun. Lett., vol. 12, no. 8, pp. 545–547, Aug. 2008.
[13]A. Younis, N. Serafimovski, R. Mesleh, and H. Haas, “Generalised spatial modulation,” in Proc. Conf. Rec. 44th Asilomar Conf. Signals, Syst. Comput., Pacific Grove, CA, USA, Nov. 2010, pp. 1498–1502.
[14]M. Di Renzo, H. Haas, and P. M. Grant, “Spatial modulation for multipleantenna wireless systems: A survey,” IEEE Commun. Mag., vol. 49, no. 12, pp. 182–191, Dec. 2011.
[15]A. Stavridis, S. Sinanovic, M. Di Renzo, and H. Haas, “Energy evaluation of spatial modulation at a multi-antenna base station,” in Proc. IEEE VTC-fall, Sep. 2013, pp. 1–5.
[16]N. Serafimovski , A. Younis, R. Mesleh, P. Chambers, M. Di Renzo, C. X. Wang “Practical implementation of spatial modulation,” IEEE Trans. Veh. Technol., vol. 62, no. 9, pp. 4511–4523, Nov. 2013.
[17]A. Younis, S. Sinanovic, M. Di Renzo, R. Mesleh, and H. Haas, “Generalised sphere decoding for spatial modulation,” IEEE Trans. Commun., vol. 61, no. 7, pp. 2805–2815, July 2013.
[18]M. Di Renzo, H. Haas, A. Ghrayeb, S. Sugiura, and L. Hanzo, “Spatial modulation for generalized MIMO: Challenges, opportunities, and implementation,” Proc. IEEE, vol. 102, no. 1, pp. 56–103, Jan. 2014.
[19]P. Yang, M. Di Renzo, Y. Xiao, S. Li, and L. Hanzo, “Design guidelines for spatial modulation,” IEEE Commun. Surv. Tuts., vol. 17, no. 1, pp. 6–26, May 2014.
[20]W. Liu, N. Wang, M. Jin, and H. Xu, “Denoising detection for the generalized spatial modulation system using sparse property,” IEEE Commun. Lett., vol. 18, no. 1, pp. 22–25, Jan. 2014.
[21]L. Xiao, L. Dan, Y. Zhang, Y. Xiao, P. Yang, and S. Li, “A low-complexity detection scheme for generalized spatial modulation sided single carrier systems, ” IEEE Commun. Lett., vol. 19, no. 6, pp. 1069–1072, June 2015.
[22]L. Xiao, P. Yang, Y. Zhao, Y. Xiao, J. Liu, and S. Li, “Low-complexity tree search-based detection algorithms for generalized spatial modulation aided single carrier systems,” in Proc. IEEE ICC, Kuala Lumpur, Malaysia, May 2016, pp. 1–6.
[23]S. Fan, Y. Xiao, L. Xiao, P. Yang, R. Shi, and K. Deng, “Improved layered message passing algorithms for large-scale generalized spatial modulation systems,” IEEE Wireless Commun. Lett., vol. 7, no. 1, pp. 66–69, Feb. 2018.
[24]J. A. Cal-Braz and R. Sampaio-Neto, “Low-complexity sphere decoding detector for generalized spatial modulation systems,” IEEE Commun. Lett., vol. 18, no. 6, pp. 949–952, June 2014.
[25]B. Zheng, M. Wen, F. Chen, N. Huang, F. Ji, and H. Yu, “The K-Best sphere decoding for soft detection of generalized spatial modulation,” IEEE Trans. Commun., vol. 65, no. 11, pp. 4803–4816, Nov. 2017.
[26]C. Yang, P. Cheng, Z. Chen, J. A. Zhang, Y. Xiao, and L. Gui, “Near-ML low-complexity detection for generalized spatial modulation”, IEEE Commun. Lett., vol. 20, no. 3, pp. 618–621, Mar. 2016.
[27]L. Xiao, P. Yang, Y. Xiao, S. Fan, M. D. Renzo, W. Xiang, and S. Li, “Efficient compressed sensing detectors for generalized spatial modulation systems,” IEEE Trans. Veh. Technol., vol. 66, no. 2, pp. 1284–1298, Feb. 2018.
[28]L. Xiao, Y. Xiao, C. Xu, X. Lei, P. Yang, S. Li, and L. Hanzo, “Compressed-sensing assisted spatial multiplexing aided spatial modulation,” IEEE Trans. Wireless Commun., vol. 17, no. 2, pp. 794–807, Feb. 2018.
[29]X. Q. Jiang, M. Wen, J. Li, and W. Duan, “Distributed generalized spatial modulation based on chinese remainder theorem,” IEEE Commun. Lett., vol. 21, no. 7, pp. 1501–1504, July 2017.
[30]H. Y. Yoon and T. H. Kim, "Low-complexity symbol detection for generalized spatial modulation MIMO systems," in Proc. IEEE VTC-fall, Sep. 2017, pp. 1–5.
[31]C. P. Li, S. H. Wang, and K. C. Chan, “Low complexity transmitter architectures for SFBC MIMO-OFDM Systems,” IEEE Trans. Commun., vol. 60, no. 6, pp. 1712–1718, June 2012.


[32]S. H. Wang and C. P. Li, “A low-complexity PAPR reduction scheme for SFBC MIMO-OFDM systems,” IEEE Signal Processing Letters, vol. 16, no. 11, pp. 941-944, Nov. 2009.
[33]W. J. Huang, W. W. Hu, C. P. Li, and J. C. Chen, “Novel metric-based PAPR reduction schemes for MC-CDMA systems,” IEEE Trans. Veh. Technol., vol. 64, no. 9, pp. 3982–3989, Sep. 2015.
[34]S. H. Wang, K. C. Lee, and C. P. Li, “A low-complexity architecture for PAPR reduction in OFDM systems with near-optimal performance,” IEEE Trans. Veh. Technol., vol. 65, no. 1, pp. 169–179, Jan. 2016.
[35]K. C. Lee, C. P. Li, T. Y. Wang, and H. J. Li, “Performance analysis of dual-hop amplify-and-forward systems with multiple antennas and co-channel interference,” IEEE Trans. Wireless Commun., vol. 13, no. 6, pp. 3070–3087, June 2014.
[36]S. H. Wang, C. P. Li, K. C. Lee, and H. J. Su, ‘‘A novel low-complexity precoded OFDM system with reduced PAPR,’’ IEEE Trans. Signal Process., vol. 63, no. 6, pp. 1366–1376, Mar. 2015.
[37]W. C. Huang, C. P. Li, and H. J. Li, “An investigation into the noise variance and the SNR estimators in imperfectly-synchronized OFDM systems,” IEEE Trans. Commun., vol. 9, no. 3, pp. 1159–1167, Mar. 2010.
[38]W. C. Huang, Y. S. Yang, and C. P. Li, “A new pilot architecture for sub-band uplink OFDMA systems,” IEEE Trans. Broadcast., vol. 59, no. 3, pp. 461–470, Sep. 2013.
[39]M. L. Wang, C. P. Li, and W. J. Huang, “Semiblind channel estimation and precoding scheme in two-way multirelay networks,” IEEE Trans. Signal Process., vol. 65, no. 10, pp. 2576–2587, May. 2017.
[40]K. Chan, Y. Chen, C. Wu and C. Li, "Achieving full diversity on a single-carrier distributed QOSFBC transmission scheme utilizing PAPR reduction," IEEE Trans. Commun., vol. 66, no. 4, pp. 1636–1648, Apr. 2018