• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.2
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• pp.255-266
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• 2015

In this paper, a low-complexity and low-power soft output multiple input multiple output (MIMO) symbol detector is proposed for mobile devices with two transmit and two receive antennas. The proposed symbol detector can support both the spatial multiplexing mode and spatial diversity mode in single hardware and shows the optimal maximum likelihood (ML) performance. By applying a multi-stage pipeline structure and using a complex multiplier based on the polar-coordinate, the complexity of the proposed architecture is dramatically decreased. Also, by applying a clock-gating scheme to the internal modules for MIMO modes, the power consumption is also reduced. The proposed symbol detector was designed using a hardware description language (HDL) and implemented using a 65nm CMOS standard cell library. With the proposed architecture, the proposed MIMO detector takes up an area of approximately $0.31mm^2$ with 183K equivalent gates and achieves a 150Mbps throughput. Also, the power estimation results show that the proposed MIMO detector can reduce the power consumption by a maximum of 85% for the various test cases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.462-467
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• 2007

This paper proposes Minimum Distance Searching Algorithm (MDSA) which reduces the computational complexity (CC) of the ML, the kind of Spatial Multiplexing (SM) MIMO system. The MDSA searchs candidate symbols with a starting symbol, which is called reference bits. We used the linear receiver of MIMO techniques to find a starting symbol. The MDSA searchs the shortest path to a transmitted symbol using reference bits and Minimum Distance(MD) concept. The CC of MDSA is reduced to the 0.21% to the ML as the transmit antennas is 4 in 16QAM. The simulation result shows the BER of MDSA is nearly same to the BER of ML as the transmit antennas is 2 and the receive antennas is 3 in 16QAM and slightly degraded to the BER of ML as the transmit antennas is 4 and the receive antennas is 6 in QPSK.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.890-893
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• 2008

In this paper, we present a low complexity modified multi-level sphere decoder (SD) for multiple-input multiple-output (MIMO) systems employing quadrature amplitude modulation (QAM) signals. The proposed decoder, exploiting the multi-level structure of the QAM signal scheme, first decomposes the high-level constellation into low-level 4-QAM constellations, so-called sub-constellations. Then, it deploys SD in the sub-constellations in parallel. In addition, in the searching stage, it uses the optimal low-complexity sort method. Computer simulation results show that the proposed decoder can provide near optimal maximum-likelihood (ML) performance while it significantly reduces the computational load.

• Journal of information and communication convergence engineering
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• v.4 no.4
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• pp.151-154
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• 2006

In this work, a novel optimal multiuser detection (MUD) approach, which not only achieves the optimal maximum-likelihood (ML)-like performance but also has reasonably low computational complexity, for Space-time coded OFDM (ST-OFDM) systems is presented. In the proposed detection scheme, the signal model is firstly re-expressed into linearly equivalent one. Then, with the linearly equivalent signal model, a new jointly MUD algorithm is proposed to detect signals. The ML-like bit-error-rate (BER) performance and reasonably low complexity of the proposed detection are verified by computer simulations.

• Journal of information and communication convergence engineering
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• v.3 no.2
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• pp.76-79
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• 2005

In this paper, a low-complexity maximum-likelihood (ML) decoder based on QR decomposition, called real-valued LCMLDec decoder or RVLCMLDec for short, is proposed for the Vertical Bell Labs Layered Space-Time (V-BLAST) architecture, a promising candidate for providing high data rates in future fixed wireless communication systems [1]. Computer simulations, in comparison with other detection techniques, show that the proposed decoder is capable of providing the V­BLAST schemes with ML performance at low detection complexity

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.10
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• pp.841-849
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• 2012

This paper proposes an low-complexity soft-output multiple-input multiple-output (soft-MIMO) detection algorithm for achieving soft-output maximum-likelihood (soft-ML) performance under max-log approximation. The proposed algorithm is based on a parallel tree-search (PTS) applying a channel ordering by a sorted-QR decomposition (SQRD) with altered sort order. The empty-set problem that can occur in calculation of log-likelihood ratio (LLR) for each bit is solved by inserting additional nodes at each search level. Since only the closest node is inserted among nodes with opposite bit value to a selected node, the proposed node insertion scheme is very efficient in the perspective of computational complexity. The computational complexity of the proposed algorithm is approximately 37-74% of that of existing algorithms, and from simulation results for a $4{\times}4$ system, the proposed algorithm shows a performance degradation of less than 0.1dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.981-989
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• 2015

In a log likelihood ratio(LLR) calculation of the detected symbol, multiple-input multiple-output(MIMO) system applying an optimal or suboptimal algorithm such as a maximum likelihood(ML) detection, sphere decoding(SD), and QR decomposition with M-algorithm Maximum Likelihood Detection(QRM-MLD) suffers from exponential complexity growth with number of spatial streams and modulation order. In this paper, we propose a LLR calculation method with very low complexity in the QRM-MLD based symbol detector for a high order modulation based $N_T{\times}N_R$ MIMO system. It is able to approach bit error rate(BER) performance of full maximum likelihood detector to within 1 dB. We also analyze the BER performance through computer simulation to verify the validity of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.143-155
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• 2013

A low-complexity dual-user multiplexing scheme is proposed for a pair of mobiles equipped with single antenna operating over frequency-selective fading channels. The proposed scheme employs OFDM transmission scheme with a modified version of a space-frequency code and a low-complexity PIC-SIC group detection is invoked at the corresponding receiver. The BER performances of the proposed scheme are studied using LTE-like parameters through simulations and are compared against those of conventional ZF and ML schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.394-402
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• 2008

In this paper, we propose a novel soft output generation method for spatially multiplexed MIMO systems. The receiver complexity of spatially mutiplexed MIMO system is in proportion to the number of candidate vectors. The ML signal detection method considers all possible vectors as candidates, thereby achieving a high performance, however, its complexity is very high. Low complexity receiver techniques involving a small number of candidate vectors, provide soft output values of low reliability. In this paper, we propose a method to improve reliability of the soft output values obtained using a small number of candidate vectors.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.6
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• pp.700-705
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• 2012

This paper suggests the detecting method in which it uses the candidate symbol obtained through PI-SDR, the little computational complexity is required. By using the candidate symbol matrices obtained through PI-SDR, ZF and MMSE method was applied and the received signal was detected. The linear detecting method using PI-SDR candidate symbol is out of the performance than ML detecting method but the complexity is low. Because of using the symbol come close to the solution of ML, the proposed method's performance is better than the existing ZF and MMSE method.