大規模多重輸入多重輸出系統可針對新一代無線網路系統提供多方面的優勢，可以有更高的資料傳輸率、容納更多使用者和藉由傳送天線和接收天線的擺設和預先編碼處理的技術可有效降低不必要的輻射以至於提升輻射能量的使用率。而在近幾年之間，由於廣義空間調變能夠避免傳送天線的同步因而有效地降低傳送端和接收端的硬體複雜度並且提高多重輸入多重輸出系統的頻譜效率，此種結合天線組合和數位訊號調變作為傳送碼字的調變方法被廣泛的討論，甚至發展出只有天線組合作為傳送碼字的調變方法。現今已有很多關於廣義空間調變技術的硬式解調方法。現今效果較好的方法皆為依據空間調變的特性而設計的天線組合和所對應的調變訊號兩階段去估計，但卻要使用反矩陣的運算，在不想要使用高運算量的反矩陣運算的情況下，本篇論文提出使用類似低運算量的樹狀偵測，總枝節的運算數量雖然相對較多但各個枝節的運算複雜度相對低很多且此種設計可專注於應用在低密度竒偶查核碼上的軟式解調器，亦提出適用於解調端與解碼端的低密度奇偶查核碼的設計。最後以結果來看，我們提出的方法的複雜度相對於現今所提出的方法的複雜度相對低很多，且設計出來的低密度竒偶查核碼的錯誤率相當接近最大事後機率偵測法。

Massive multiple-input multiple-output system, has many advantages for wireless communication system, has higher data rate and accommodate more users. Due to generalized spatial modulation can effectively reduce hardware complexity and improve the spectral efficiency of multiple-input multiple-output system, it is a modulation method whitch combines the combination of transmit antennas and digital modulation as a transmission codeword and has been widely discussed in recent years. Nowadays, there are a lot of discussions about the hard-decision detections of generalized spatial modulation. The complexity of inverse matrix operations is high computational. Under these circumstances, we propose a detection method that is similar to tree search whitch has lower computation and present the soft-decision detections whitch is applicable to Low-density parity-check(LDPC) code. In view of the results, we have a tight performance loss compared to maximum a posteriori(MAP) detection.

E. G. Larsson et al. ``Massive MIMO for Next Generation Wireless Systems ” to appear, IEEE Commun. Mag.
L. Lu, G. Y. Li, A. L. Swindlehurst, A. Ashikhmin, and R. Zhang,``An overview of massive MIMO: benefits and challenges,” IEEE Journal of Selected Topics in Signal Processing, vol. 8, pp. 742–758, October 2014.
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.
Jeganathan, A. Ghrayeb, and L. Szczecinski, ``Spatial modulation: Optimal detection and performance analysis,” IEEE Commun. Lett., vol. 12, no. 8, Aug. 2008, pp.545–47.
A. Younis, N. Serafimovski, R. Mesleh and H. Haas, ``Generalised spatial modulation", Proc. 2010 ASILOMAR, pp. 1498-1502
J. Fu, C. Hou, W. Xiang, L. Yan and Y. Hou, ``Generalised spatial modulation with multiple active transmit Ten Brink, Stephan, Gerhard Kramer, and Alexei Ashikhmin. ``Design of low-density parity-check codes for modulation and detection,” Communications, IEEE Transactions on 52.4 (2004): 670-678.
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, 2014.
Chen, C.; Li, C.; Huang, Y. ``An Improved Ordered-Block MMSE Detector for Generalized Spatial Modulation", Communications Letters, IEEE, On page(s): 707 - 710 Volume: 19, Issue: 5, May 2015.
Chun-Tao Lin, Wen-Rong Wu, Chia-Yu Liu, ``Low-Complexity ML Detectors for Generalized Spatial Modulation Systems, ” IEEE Trans. Commun., vol. 63, pp. 4214-4230, Nov. 2015.
S. ten Brink, “ Convergence behavior of iteratively decoded parallel concatenated codes,” IEEE Trans. Commun., vol. 49, pp. 1727–1737, Oct. 2001.
T. Richardson, M. Shokrollahi, and R. Urbanke, "Design of capacity approaching irregular low-density parity-check codes," IEEE Trans. Inf. Theory, vol. 47, no. 2, pp. 619--637, Feb. 2001.