• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.932-939
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• 2008

Recently lattice-reduction (LR) has been used in signal detection for multiple-input multiple-output (MIMO) systems. The conventional LR aided detection schemes are combinations of LR and signal detection methods such as zero-forcing (ZF) and minimum mean square error (MMSE) detection. In this paper, we propose the Lattice-Reduction-aided scheme based on extended noise variance matrix to search good candidate symbol set in quantization step. Then this scheme estimates transmitted symbol with Semidefinite Relaxation by candidate symbol set. Simulation results in a random MIMO system show that the proposed scheme exhibits improved performance and a slight increase in complexity.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.10
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• pp.75-82
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• 2008

In this paper, we propose an efficient symbol detection algorithm for multiple-input multiple-output spatial multiplexing (MIMO-SM) systems and present its design and implementation results. By enhancing the performance of the first detected symbol which causes error propagation, the proposed algorithm achieves a considerable performance gain as compared to the conventional sorted QR decomposition (SQRD) based detection and the ordered successive detection (OSD) algorithms. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by the simulation. In case of 16QAM MIMO-SM system with 4 transmit and 4 receive ($4{\times}4$) antennas, at $BER=10^{-3}$ the proposed algorithm obtains the gai improvement of about 2.5-13.5 dB over the conventional algorithms. The proposed detection algorithm was designed in a hardware description language (HDL) and synthesized to gate-level circuits using 0.18um 1.8V CMOS standard cell library. The results show that the proposed algorithm can be implemented without increasing the hardware costs significantly.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.609-621
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• 2015

Recently, a variety of reduced complexity soft-in soft-output detection algorithms have been introduced for iterative detection and decoding (IDD) systems. However, it is still challenging to implement soft-in soft-output detectors for MIMO systems due to heavy burden in computational complexity. In this paper, we propose a soft detection algorithm for MIMO systems which performs close to the full dimensional joint detection, yet offers significant complexity reduction over the existing detectors. The proposed algorithm, referred to as soft-input soft-output successive group (SSG) detector, detects a subset of symbols (called a symbol group) successively using a deliberately designed preprocessing to suppress the inter-group interference. In fact, the proposed preprocessor mitigates the effect of the interfering symbol groups successively using a priori information of the undetected groups and a posteriori information of the detected groups. Simulation results on realistic MIMO systems demonstrate that the proposed SSG detector achieves considerable complexity reduction over the conventional approaches with negligible performance loss.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.95-103
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• 2009

An efficient symbol time synchronization scheme for IEEE 802.11n MIMO-OFDM based WLAN systems using cyclic shift diversity (CSD) preamble is proposed. CSD is used to prevent unintentional beamforming when the same preamble signal is transmitted through transmit antennas. However, it is difficult to find a proper starting-point of the OFDM symbol with the conventional algorithms because of time offset by multi-peaks which are result from cross-correlation of received CSD preamble with a known short training symbol. In addition, the performance of symbol time sync. is affected by AGC and packet detection position. In this paper, an optimal symbol time synch. algorithm which is composed of the boundary detection scheme between LTS and OFDM symbols, the verification scheme for enhancement of boundary detection accuracy, and the SNR-varying threshold estimation scheme is proposed. Simulation result show that the proposed algorithm has performance gains of 4.3dB in SNR compared to the conventional algorithms at the rate of 1% sync. failure probability for $2{\times}2$ MIMO-OFDM system and 18dB at 0.1% when maximum frequency offset exists. It also can be applied to $4{\times}4$ MIMO-OFDM system without any modification. Hence, it is very suitable for MIMO-OFDM WLAN systems using CSD preamble.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5305-5321
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• 2016

In wireless communication, the multiple-input multiple-output (MIMO) system is a well-known approach to improve the reliability as well as the data rate. In MIMO systems, channel state information (CSI) is typically required at the receiver to detect transmitted signals; however, in practical systems, the CSI is imperfect and contains errors, which affect the overall system performance. In this paper, we propose a novel maximum likelihood (ML) scheme for MIMO systems that is robust to the CSI errors. We apply an optimization method to estimate an instantaneous covariance matrix of the CSI errors in order to improve the detection performance. Furthermore, we propose the employment of the list sphere decoding (LSD) scheme to reduce the computational complexity, which is capable of efficiently finding a reduced set of the candidate symbol vectors for the computation of the covariance matrix of the CSI errors. An iterative detection scheme is also proposed to further improve the detection performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.12-18
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• 2017

This paper presents a Dijkstra's-search-based sphere decoding (SD) algorithm with limited complexity for the symbol detection in MIMO communication systems. The Dijkstra search-based SD is efficient to achieve a near-optimal error rate in the MIMO symbol detection, but has a critical problem in that its complexity is variable and can correspond to that of the exhaustive search in the worst case. The proposed algorithm limits the computations while achieving a near-optimal error rate. Simulation results show that the error rate is near optimal even with the limited complexity.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.34-42
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• 2014

This paper presents a low-complexity and high-throughput symbol detector for two-spatial-stream multiple-input multiple-output systems based on the modified maximum-likelihood symbol detection algorithm. In the proposed symbol detector, the cost function is calculated incrementally employing a multi-cycle architecture so as to eliminate the complex multiplications for each symbol, and the slicing operations are performed hierarchically according to the range of constellation points by a pipelined architecture. The proposed architecture exhibits low hardware complexity while supporting complicated modulations such as 256 QAM. In addition, various modulations and antenna configurations are supported flexibly by reconfiguring the pipeline for the slicing operation. The proposed symbol detector is implemented with 38.7K logic gates in a $0.11-{\mu}m$ CMOS process and its throughput is 166 Mbps for $2{\times}$3 16-QAM and 80Mbps for $2{\times}3$ 64-QAM where the operating frequency is 478 MHz.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.1010-1015
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• 2009

In this paper, we propose a novel detection ordering technique for MIMO signal detection methods based on QR decomposition and successive interference cancellation (SIC). Recently, new signal detection methods for spatially multiplexed (SM) MIMO systems were proposed, where all the constellation points are tried as the first layer symbol, and the remaining layer symbols are estimated via SIC, producing candidate vectors. Finally, the ML metric values are calculated for the candidate vectors, that are again used to select the best symbol vector. It was also shown that the ordering method in the conventional V-BLAST is not suitable to these signal detection methods. In this paper, we propose a novel ordering method, and we show via computer simulations that the proposed ordering method improves the error performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3907-3923
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• 2020

An enhanced irregular repetition slotted ALOHA (IRSA) protocol is proposed by using polarization characteristic of satellite link and MIMO detection in low earth orbit (LEO) satellite networks, which is dubbed polarized MIMO IRSA (PM-IRSA). In the proposed scheme, one or two packets in one slot can be decoded by employing polarized MIMO detection, and more than two collided packets in multiple slots which can construct the virtual MIMO model can be decoded by the MIMO detection algorithm. The performance of the proposed scheme is analyzed with the density evolution (DE) approach and the degree distribution is optimized to maximize the system throughput by using a differential evolution. Numerical results certify our analysis and show that the normalized throughput of the proposed PM-IRSA can achieve 1.89 bits/symbol.