This paper presents the VLSI implementation of a lattice-reduction-aided (LRA) detection system. The proposed system includes a QR decomposition, lattice reduction (LR) processor, and sorting-reduced (SR) K-best detector for 8 × 8 multiple-input multiple-output (MIMO) systems. The bit error rate of the proposed MIMO detection system only incurs approximately 3 dB of implementation loss compared with optimal maximum likelihood detection with 64-quadratic-amplitude modulation. The proposed processor can also support different throughput requirements by adjusting the stage number of LR. The SR K-best detector can achieve 3.1 Gb/s throughput with 0.24-ns latency. The throughput of the system reaches 585 Mb/s if one channel preprocessing can support 72 symbol detections. The corresponding energy per bit is 63 pJ/bit, which is the smallest value achieved to date. This paper presents the first VLSI implementation of a complete LRA K-best detector with an 8 × 8 dimension.Index Terms-K-best detector, lattice reduction (LR), multipleinput multiple-output (MIMO) detection.
This paper presents a configurable MIMO detector with QR decomposition and channel interpolation for 4 × 4 MIMO-OFDM systems. QR decomposition (QRD) processor and MIMO detector are usually investigated independently in the literature; however, this methodology usually limits operating condition to only slow fading channel. Therefore, this study jointly designs a hardware architecture for QR decomposition and MIMO detection without interface memory buffer, and the channel interpolation is also performed at the same time. This QR-based MIMO detector is implemented in a 90nm CMOS process with 2.02mm 2 core area. The chip consumes 56.8mW at 114MHz operating frequency with 1.0V supply and achieves 684Mbps throughput. The proposed chip, which performs one QRD and one MIMO detection for one OFDM symbol, is the first MIMO detector in the literature that supports real-time QR decomposition and MIMO detection for fast fading MIMO-OFDM systems.
I. INTRODUCTIONWireless communication systems are facing an increasing demand for higher data rate and quality of service. Multipleinput multiple-output (MIMO) technique has been adopted to offer higher throughput without bandwidth expansion or transmitter power increasing. The MIMO wireless technology based on orthogonal frequency division multiplexing (OFDM) modulation has also enjoyed great popularity in the recent wireless communication standards such as IEEE 802.11n, IEEE 802.16m, and 3GPP-LTE. The MIMO detector is one of the implementation challenges in the MIMO-OFDM system. The QR-based MIMO detector is a popular detection scheme due to its low complexity for implementation. However, most of the researches only focus on either the QR decomposition (QRD) [1], [2] or the detection itself [3], [4]. Researchers of the MIMO detectors usually assume that the channel are fixed in slow fading channel and all QR coefficients are obtained in parallel. To realize a fast-fading MIMO detector, this study proposes a modified interpolation-based QR decomposition (MIQRD) algorithm and a QR-based successive interference cancellation (SIC) detection with multiple-candidate selection scheme (MCS-QRSIC). The proposed MIQRD architecture supports 2 × 2, 2 × 4, and 4 × 4 MIMO configurations and has less complexity than the traditional method. The proposed MCS-QRSIC architecture has various candidates settings and does not need sorting operations in each layer. Because QRD and MIMO detection are both performed in one OFDM
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