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QR decomposition is a fundamental operation widely used in various signal detection schemes for multiple-input multiple-output (MIMO) systems. In this brief, a high-throughput converted form QR factorization (QRF) is investigated. The proposed two-phase computing scheme starts with a direct form factorization followed by a postprocessing using simple row/column permutations. Using coordinate rotation digital computer (CORDIC) algorithm, a massively parallel array architecture consisting of pipelined and folded CORDIC modules is developed to enhance the throughput. In addition, chaining mode operation is supported, where five successive signal vector updates can be performed the following every factorization. The chip implementation result in TSMC 0.18- $\mu $ m CMOS process indicates the design, with an equivalent gate count 192100, can operate at 200 MHz and accomplish 25-M complex-valued QRF per second. This suggests a highest 3-Gb/s data rate for signal detections in a $4 \times 4$ MIMO system. The proposed design also outperforms other designs in two compound performance indices, i.e., data rate normalized with respect to gate count and power consumption, respectively. [ABSTRACT FROM PUBLISHER]

Blind channel estimation based on a subspace-based algorithm for single-input single-output cyclic-prefixed single-carrier systems is proposed in this brief. The proposed method is different from conventional subspace-based approaches, which exploit the original complex structure of the received data symbols. In contrast, we separate the real part and the imaginary part of the received complex symbols and then exploit these two kinds of symbols to construct the signal model. The noise subspace can then be established to estimate the channel impulse response (CIR) using a subspace algorithm when real symbols, such as binary phase shift keying or pulse amplitude modulation symbols, are applied. The real part and the imaginary part of the CIR can be estimated individually and simultaneously with only a sign ambiguity. With the aid of repetition index, the proposed method is workable even if few data blocks are available. Simulation results demonstrate that the proposed approach outperforms conventional methods in normalized mean-squared error under static channel environments. [ABSTRACT FROM PUBLISHER]