本論文提出一以傳統分佈型K-最佳演算法為基礎的低複雜度K-最佳多輸入輸出解碼器，本解碼器結合了兩種可適性自動調節機制來達到比傳統分佈型K-最佳演算法還低的運算複雜度，分別為適應性連續消除機制與適應性K值選取機制。
適應性連續消除機制的原理為於每一層解碼訊號時計算每個母點的中心點，運用這些中心點的相同性來判斷是否執行連續消除演算法。然而適應性K值選取機制的原理不同於傳統適應性K值選取機制需要估測SNR大小來調整K值大小，所提出之機制僅需使用每一層中最小與次小的PED來決定K值大小，並且提出一套關於K值選取的設計流程，使適應性K值選取機制能更有效率得被使用。
與傳統分佈型K-最佳演算法作比較，所提出之演算法因加入這兩種可適性機制後能在錯誤率不提高為前提下擁有更低的運算複雜度，並且設計適當的電路架構使其能更有效率的降低功率消耗。
最後本論文使用SMIMS VeriEnterprise Xilinx FPGA板驗證其電路功能，並且以TSMC-90nm製程實現所提出之解碼器。該晶片核心面積為0.740 mm x 0.738 mm，當晶片操作於125MHz以及1V的工作電壓下其功率消耗為22mW，並且訊號最大吞吐量可達124Mbps。

The thesis proposed a low complexity K-best MIMO detector based onconventional distributed K-best(DKB).The proposed algorithm combines two self-adjusting mechanisms which are adaptive successive interference cancellation (ADSIC) and adaptive K value chooser (ADK).
The principle of ADSIC is to determine the execution of SIC based on the similarity of center-points. The center-points can be found first by calculating every root’s signal in each layer, then identify the one that has the least partial Euclidian distance (PED). After contrasting the one with each other, make a decision to execute SIC by the statistic of the same cases.
The goal of the other mechanism is that ADK choose an appropriate K value at each layer by non-SNR measurement. The purpose is to put forward a design flow by selecting the appropriate threshold value and estimating the order of noise by the smallest PED and the second smaller PED.
The proposed algorithm has lower computational complexity comparing with conventional DKB due to smaller BER loss; in addition, lower power consumption is achieved by utilizing architecture with gated clock.
In order to verify the function of the algorithm, a chip is implemented using TSMC 90nm Technology and SMIMS VeriEnterprise Xilinx FPGA verification board. The functionality of the chip is validated with core size of 0.740 mm x 0.738 mm, clock frequency of 125MHz, power consumption of 22mW and maximum throughput of 124Mbps.

[1] E. Perahia, R. Stacey, Next Generation Wireless LANs: Throughput, Robustness, and Reliability in 802.11n. Cambridge University Press, Sep. 2008.
[2] IEEE.802.11n standard
[3] J.Akhtar and D. Gesbert, “Spatial multiplexing over correlated mimo channels with a closed-form precoder,” IEEE Transactions on Wireless Communications, vol. 4, pp. 2400-2409, 2005.
[4] A. Burg, M. Borgmanr, M. Wenk, C. Studer, and H. Bolcskei, ”Advanced receiver algorithms for mimo wireless communications, “ in IEEE DATE’06, vol. 1, 2006.
[5] M. Shabany and P. Su, K. and Gulak , “A Pipeline Scalable High-throughput Implementation of a Near-ML K-Best Complex Lattice Decoder,” in ISCASP, pp.3173-3176,2008.
[6] H. Kawai, K. Higuchi, N. Maeda, and M. Sawahashi, “Adaptive Control of Surviving Symbol Replica Candidates in QRM-MLD for OFDM MIMO Multiplexing,” IEEE Journal on Selected Areas in Communications, Vol. 24, pp. 1130-1140, 2006
[7] A. S. K. Mondal, S.; Eltawil, “Architecture Optimizations for Low-Power K-best mimo decoders,” IEEE Transactions on Vehicular Technology, Vol. 58, pp. 3145-3153, 2008.
[8] S. Verdu, Multiuser detection, p. 369-409. Cambridge University Press, 1998.
[9] R. Fasthuber, D. Min Li; Novo, P. Raghavan, L. Van Der Perre, and F. Catthoor, "Novel energy-efficient scalable soft-output ssfe mimo detector architectures," in SAMOS ’09. International Symposium on Systems, Architectures, Modeling and Simulation, 2009., pp. 165-171.
[10] P. Shabany, M. and Gulak , “A 0.13um CMOS 655Mb/s 4x4-QAM K-Best MIMO Detector,” in IEEE International Solid-State Circuits Conference – Digest of Technical Paper, 2009. ISSCC 2009., pp.256-257, 2009.
[11] H. L. Lin, R. Chang, and H. L. Chen “A High-Speed SDM-MIMO Decoder Using Efficient Candidate Searching for Wireless Communication,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 55, pp. 289-293, 2008.
[12] C.-H. Liao, T.-P. Wang, and T.-D. Chiueh, “A 74.8 mW Soft-Output Detector IC for 8x8 spatial-multiplexing mimo communications,” IEEE Journal of Solid-State Circuits, vol. 45, pp. 411-421, 2010.
[13] Z. Guo and P. Nilsson, “Algorithm and implementation of the K-best sphere decoding for mimo detection,” IEEE Journal on Selected Areas Communications, vol. 24,pp. 491–503, 2006.
[14] R. Shariat-Yazdi and T. Kwasniewski, “Configurable k-best mimo detector architecture,” in ISCCSP 2008. 3ed International Symposium on Communication , Control and Signal Processing, 2008., pp. 1565–1569, 2008.
[15] M. Wenk, M. Zellweger, A. Burg, N. Felber, and W. Fichtner, “K-best mimo detection VLSI architectures achieving up to 424 Mbps,” in 2006 IEEE International Symposium on Circuits and Systems, pp. 1151-1154, 2006.
[16] A. Burg, M. Borgmann, M. Wenk, M. Zellweger, W. Fichtner, and H. Bolcskei, “VLSI implementation of mimo detection using the sphere decoding algorithm,” IEEE Journal of Solid-State Circuits, vol. 40, pp. 1566–1577, 2005.