時空調變(Spatial modulation)是近年推出新的多天線輸入多天線輸出(MIMO)技術，主要透過天線的編碼，以達到提高信息量，以及減少發射端的射頻電路鏈(radio frequency chains, Rf chains)，時空調變有一個缺點，就是他對於信息量也有所限制，最主要的原因是因為一次一根天線的傳送，為了解決此問題廣義時空調變(generalized spatial modulation, GSM)被提了出來，與單天線時空調變有所不同，廣義時空調變在一個時間點可以讓多根天線同時傳送信號，此總做法可以大大增加頻譜使用效率，相比於多天線輸入多天線輸出系統 ，廣義時空調變可以有效解決天線之間互相干擾，時空調變最主要的解調方式是最大似然法則(maximum likelihood, ML)，但是隨著天線數量的增加，最大似然法則的複雜度也會跟著增加，為了減少複雜度，許多方法相繼被提出來，他們都能減少運算複雜度，以及維持它的錯誤率。

在這篇論文裡，我有模擬了ordered-blocked MMSE，此方法可以降低搜索複雜度，但是錯誤率沒有辦法吻合最大似然法則解，為了改善錯誤率效能，另一個新的解調方法重新被導入ordered-blocked MMSE，藉由模擬，我們將證明此方法能可以改善最大似然法的複雜度，以及降低ordered-blocked MMSE的錯誤率

There is a new MIMO technology referred to as spatial modulation, which has been proposed recently. This main ideal of this technology is that some antennas are activated in each time slot. The information bits are used to choose which antenna are activated. By using this method information throughput can be increased and reduced the number of RF chains. Compared to the MIMO system, the GSM system can also reduce the inter antenna combination interference (ICI).
The optimal method to demodulate the signal is based on the maximum likelihood (ML) detection. However, its complexity will grow very fast. In order to reduce
complexity and maintain bit error rate. There are many ways to solve this problem. In this thesis I first simulate a method referred to as the ordered-blocked MMSE method, where MMSE is the abbreviation of minimum mean-squares error.
This method can reduce the search complexity; however, the bit error rate
has no way to fit the result of ML detection. In this thesis, a new method is introduced for the ordered-block MMSE. By the simulation, we show that this method can improve the performance of the ordered-block MMSE and ML detection.

[1] G. D. Goutham Simha, S. Koila, R. Mans and U. Sripati, "Modified signal design for multistream spatial modulation over spatially correlated channels," International Conf. Comput, Commun,Infor, Udupi, 2017, pp. 612-617
[2] Y. Samayoa, M. Kock, H. Blume and J. Ostermann, "Low-Cost Channel Sounder Design Based on Software-Defined Radio and OFDM," IEEE Int .Conf. Commun, Chicago, IL, USA, 2018, pp. 1-5
[3] Y. Sun, J. Wang and C. Pan, "A polynomial expansion based detection: A low-complexity approach for generalised spatial modulation over transmit antenna correlation, Wireless Commun, Valencia, 2017, pp. 1830-1833.
[4] C. Chen, C. Li and Y. Huang, "An Improved Ordered-Block MMSE Detector for Generalized Spatial Modulation," IEEE Commun Lett, vol. 19, no. 5, pp. 707-710, May 2015,
[5] T. Liu, C. Chen and C. Liu, "Fast Maximum Likelihood Detection of the Generalized Spatially Modulated Signals Using Successive Sphere Decoding Algorithms," IEEE Commun. Lett, vol. 23, no. 4, pp. 656-659, April 2019
[6] S. Afridi and S. A. Hassan, "Spectrally efficient adaptive generalized spatial modulation MIMO systems," IEEE Conf, Commun, Network, Conf, Las Vegas, NV, 2017, pp. 260-263
[7] C. Hung and W. Chung, "An improved MMSE-based MIMO detection using low-complexity constellation search," 2010 IEEE Globe, Workshops, Miami, FL, 2010, pp. 746-750
[8] N. Ma, A. Wang, C. Han and Y. Ji, "Adaptive joint mapping generalised spatial modulation," IEEE Int.Conf, Commun, Beijing, 2012, pp. 520-523
[9] G. Kaddoum and E. Soujeri, "On the comparison between code-index modulation and spatial modulation techniques," Int. Conf. Infor, Commun, Tech Research , Abu Dhabi, 2015, pp. 24-27
[10] Y. Wang, W. Liu, M. Jin, S. Jang and J. M. Kim, "FQAM/FPSK modulation for spatial modulation systems," Int. Conf,Infor, Commun, Tech Convergence, Jeju, 2016, pp. 511-515,
. [11] G. D. Goutham Simha, S. Koila, R. Mans and U. Sripati, "Modified signal design for multistream spatial modulation over spatially correlated channels," 2017 Int. Conf.on Advances in Computing, Communications and Informatics (ICACCI), Udupi, 2017, pp. 612-617