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Algorithm and Architecture of Configurable Joint Detection and Decoding for MIMO Wireless Communications With Convolutional Codes

Algorithm and Architecture of Configurable Joint Detection and Decoding for MIMO Wireless Communications With Convolutional Codes This paper presents an algorithm and a VLSI architecture of a configurable joint detection and decoding (CJDD) scheme for multi-input multioutput (MIMO) wireless communication systems with convolutional codes. A novel tree-enumeration strategy is proposed such that the MIMO detection and decoding of convolutional codes can be conducted in single stage using a tree-searching engine. Moreover, this design can be configured to support different combinations of quadrature amplitude modulation (QAM) schemes as well as encoder code rates, and thus can be more practically deployed to real-world MIMO wireless systems. A formal outline of the proposed algorithm will be given and simulation results for 16-QAM and 64-QAM with rate-1/2 and rate-1/3 codes will be presented showing that, compared with the conventional separate scheme, the CJDD algorithm can greatly improve bit error rate (BER) performance with different system settings. In addition, the VLSI architecture and implementation of the CJDD approach will be illustrated. The architectures and circuits are designed to support configurability and flexibility while maintaining high efficiency and low complexity. The postlayout experimental results for 16-QAM and 64-QAM with rate-1/2 and rate-1/3 codes show that, compared with the previous configurable design, this architecture can achieve reduced or comparable complexity with improved BER performance.

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