• ETRI Journal
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• v.35 no.3
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• pp.371-377
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• 2013

An effective signal detection algorithm with low complexity is presented for multiple-input multiple-output orthogonal frequency division multiplexing systems. The proposed technique, QR-MLD, combines the conventional maximum likelihood detection (MLD) algorithm and the QR algorithm, resulting in much lower complexity compared to MLD. The proposed technique is compared with a similar algorithm, showing that the complexity of the proposed technique with T=1 is a 95% improvement over that of MLD, at the expense of about a 2-dB signal-to-noise-ratio (SNR) degradation for a bit error rate (BER) of $10^{-3}$. Additionally, with T=2, the proposed technique reduces the complexity by 73% for multiplications and 80% for additions and enhances the SNR performance about 1 dB for a BER of $10^{-3}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.1-6
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• 2007

In this paper, a simplified new modulation classification method that utilizes likelihood function for received signal in an impaired AWGN channel environment. The proposed method provides the superior to ML method, although the likelihood under the assumption that each modulated signal is sent utilized. On the other hand, the ML method gets the performance characteristics of high computational complexity and weakness to channel impairment such as phase offsets and frequency offsets. The proposed method has lower computational complexity than that of the ML method. Moreover, the proposed method is robust to the channel impairment such as phase offsets and frequency offsets. The correct classification probabilities of the proposed method and the ML method are given for an AWGN channel with phase offsets and frequency offsets, which were simulated with extensive Monte-Carlo simulation. As shown in simulation resole, a more accurate classification performance both in phase offset environment and in frequency offset can be achieved with the low computational complexity of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.10A
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• pp.1000-1010
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• 2002

Partial response maximum-likelihood (PRML) and fixed-delay tree search with decision feedback (FDTS/DF) yield a sub-optimum performance in storage systems. However, they suffer from the inevitable complexity problems. this paper focuses on detection schemes to overcome the drawbacks of the sequence detections by exploiting minimum run-length d=2. It is expected that the proposed systems yield substantial reductions of both processing speed and receiver complexity. When combined with a decision feedback equalization (DFE), they prove to keep pace with the FDTS/DF with ${\tau}$=2 and even outperform the PR(1111)ML at normalized density S>5.6.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2525-2532
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• 2009

In this paper, a fast sphere decoder is proposed for the joint detection of phase-shift keying (PSK) signals in uncoded Vertical Bell Laboratories Layered Space Time (V-BLAST) systems. The proposed decoder, PSD, consists of preprocessing stage and search stage. The search stage of PSD relies on the depth-first branch-and-bound (BB) algorithm with "best-first" orders stored in lookup tables. Simulation results show that the PSD is able to provide the system with the maximum likelihood (ML) performance at low complexity.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.257-265
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• 2011

In this paper, a cooperative relaying protocol called soft-decision-and-forward (SDF) with multiple antennas in each node is introduced. SDF protocol exploits the soft decision source symbol values from the received signal at the relay node. For orthogonal transmission (OT), orthogonal codes including Alamouti code are used and for non-orthogonal transmission (NT), distributed space-time codes are designed by using a quasi-orthogonal space-time block code. The optimal maximum likelihood (ML) decoders for the proposed protocol with low decoding complexity are proposed. For OT, the ML decoders are derived as symbolwise decoders while for NT, the ML decoders are derived as pairwise decoders. It can be seen through simulations that SDF protocol outperforms AF protocol for both OT and NT.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.75-81
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• 2024

In this paper, we proposes a method for real-time processing of inter-floor noise problems by embedding TinyML, which includes a deep learning model, into ultra-low-power systems. The reason this method is feasible is because of lightweight deep learning model technology, which allows even systems with small computing resources to perform inference autonomously. The conventional method proposed to solve inter-floor noise problems was to send data collected from sensors to a server for analysis and processing. However, this centralized processing method has issues with high costs, complexity, and difficulty in real-time processing. In this paper, we address these limitations by employing On-Sensor AI using TinyML. The method presented in this paper is simple to install, cost-effective, and capable of processing problems in real-time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.336-342
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• 2003

Noise predictive maximum likelihood(NPML) detector embeds noise prediction/whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This thesis random sequences are applied to linear channel. In perpendicular magnetic recording density KP=2.5, NP(121)ML and NP(1221)ML detection system which is based on a noise predictive PR-equalized signal are evaluated by the Performance through a computing simulation. Therefore, NPML systems are implemented and are verified by VHDL.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.152-158
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• 2015

We consider the problem of designing independently operating local quantizers at nodes in distributed estimation systems, where many spatially distributed sensor nodes measure a parameter of interest, quantize these measurements, and send the quantized data to a fusion node, which conducts the parameter estimation. Motivated by the discussion that the estimation accuracy can be improved by using the quantized data with a high probability of occurrence, we propose an iterative algorithm with a simple design rule that produces quantizers by searching boundary values with an increased likelihood. We prove that this design rule generates a considerably reduced interval for finding the next boundary values, yielding a low design complexity. We demonstrate through extensive simulations that the proposed algorithm achieves a significant performance gain with respect to traditional quantizer designs. A comparison with the recently published novel algorithms further illustrates the benefit of the proposed technique in terms of performance and design complexity.

• Journal of information and communication convergence engineering
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• v.4 no.1
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• pp.5-9
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• 2006

In this paper, a low-complexity ML decoder based on QR decomposition, called LCMLDec decoder, is proposed for the V-BLAST with 2 transmit antennas. Then, it is combined with other suboptimal interference nulling and cancelling decoders originated form QR decomposition such as sorted QR or MMSE-SQRD decoder to generate efficient decoders that significantly improve the performance of the V-BLAST with more than 2 transmit antennas, at the expense of a small increase in complexity. Simulation results are provided to demonstrate the performances and complexities of the proposed decoders.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.110-116
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• 2005

In this paper, a low-complexity ML decoder based on QR decomposition, called LCMLDec decoder, is proposed for the V-BLAST with 2 transmit antennas. Then, it is combined with other suboptimal interference nulling and cancelling decoders originated form QR decomposition such as sorted QR or MMSE-SQRD decoder to generate efficient decoders that significantly improve the performance of the V_BLAST with more than 2 transmit antennas, at the expense of a small increase in complexity. Simulation results are provided to demonstrate the performances and complexities of the proposed decoders.