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In this brief, a high-speed space-division multiplexing (SDM) multiple-input-multiple output (MIMO) decoder using efficient candidate searching is proposed by exploiting the characteristics of QR decomposition and sphere decoder for high throughput rate and low hardware-complexity. A process of efficient candidate searching by shifting the center of constellation with scalable radius reduces the processing time and improves the operational frequency. The proposed architecture can operate at a 166-MHz clock frequency, and the core area is smaller than results from using the K-best SD algorithm since large memory is not required to store extreme candidate paths. In our implementation, the core area is 0.675 mm 2 using TSMC 90-nm technology. The average throughput of the proposed SDM-MIMO decoder is 95 Mbps with 64-QAM modulation at 30-dB signal-to-noise ratio.Index Terms-Digital communication, maximum-likelihood (ML) detection, space-division multiplexing (SDM) multiple-input-multiple output (MIMO) detector, sphere decoder, wireless systems.

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This paper presents a modi¯ed implementation of QR decomposition for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) detection based on the Givens rotation method. The QR decomposition hardware is constructed using the coordinate rotation digital computer (CORDIC) algorithm operating with fewer gate counts and lower power consumption than do triangular systolic array (TSA) structures. Accurate signal transmission is essential to wireless communication systems. Thus, a more e®ective data detection algorithm and precise channel estimation method play vital roles in MIMO systems. Implementing data detection with QR decomposition helps reduce the complexity of MIMO-OFDM detection. Implementation results reveal that the proposed recursive QR decomposition (RQRD) architecture has lower clock latency than do TSA structures, and has a smaller hardware area than do GramÀSchmidt structures.