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Multiuser Detection via Compressive Sensing
Byonghyo Shim,Byungkwen Song IEEE 2012 IEEE communications letters Vol.16 No.7
<P>In this paper, we consider a multiuser detection technique when the signal sparsity is changing over time. The key ingredient of our method is a clever switching between the CS reconstruction algorithm and classical detection depending on the sparsity level of the signals being detected. Since none of these approaches is uniformly better in a situation where the sparsity level is varying, proposed switching algorithm can effectively combine the merits of both. We show that the proposed switching algorithm provides substantial performance gain over individual algorithms in the multiuser detection of CDMA downlink.</P>
Joint Modulation Classification and Detection Using Sphere Decoding
Byonghyo Shim,Insung Kang IEEE 2009 IEEE signal processing letters Vol.16 No.9
<P>In this letter, we propose a simple yet effective modulation classification method for maximum likelihood multiuser detection. Our method is a modification of generalized likelihood ratio test (GLRT) that approximates the optimal classifier in the Bayesian sense. We show that the proposed method can be implemented by modifying the sphere decoding algorithm to support multimodulation. Simulation results in multiuser detection in high-speed downlink packet access (HSDPA) system show that the proposed method offers considerable performance gain over conventional RAKE and MMSE algorithms.</P>
Near ML-achieving Lattice Search for Multiple Antenna Systems
Byonghyo Shim,Byungju Lee,Sunho Park 대한전자공학회 2008 ICEIC:International Conference on Electronics, Inf Vol.1 No.1
In this paper, we present a near ML-achieving sphere search technique that reduces the number of search operations significantly over existing sphere decoding (SD) algorithms. While the SD algorithm relies only on causal symbols in evaluating sequential cost metrics, the proposed method accounts for the contribution of non-causal symbols with an aid of perpath minimum mean square error (MMSE) symbol estimation. From the simulations performed over multi-input multi-output (MIMO) wireless channels, it is shown that the computational complexity of the proposed algorithm is substantially smaller than the existing SD algorithms while providing negligible performance loss.
On further reduction of complexity in tree pruning based sphere search
Byonghyo Shim,Insung Kang IEEE 2010 IEEE TRANSACTIONS ON COMMUNICATIONS Vol.58 No.2
<P>In this letter, we propose an extension of the probabilistic tree pruning sphere decoding (PTP-SD) algorithm that provides further improvement of the computational complexity with minimal extra cost and negligible performance penalty. In contrast to the PTP-SD that considers the tightening of necessary conditions in the sphere search using per-layer radius adjustment, the proposed method focuses on the sphere radius control strategy when a candidate lattice point is found. For this purpose, the dynamic radius update strategy depending on the lattice point found as well as the lattice independent radius selection scheme are jointly exploited. As a result, while maintaining the effectiveness of the PTP-SD, further reduction of the computational complexity, in particular for high SNR regime, can be achieved. From simulations in multiple-input and multiple-output (MIMO) channels, it is shown that the proposed method provides a considerable improvement in complexity with near-ML performance.</P>
Decision-Feedback Closest Lattice Point Search for UMTS HSPA System
Byonghyo Shim,Abrishamkar, F.,Insung Kang IEEE 2009 IEEE signal processing letters Vol.16 No.12
<P>This letter considers a low-complexity multiuser detection based on the closest lattice point search (CLPS) for high speed packet access (HSPA) system. Instead of attempting to solve the ML detection problem in the presence of intersymbol and inter-cell interference, we utilize interference cancelled chips obtained from a bidirectional decision feedback operation to detect symbols. As a result, the worst case complexity of the CLPS is bounded to a controllable level irrespective of multipath spans. From the simulation on single and multi cell downlink communications in HSPA systems, we show that the proposed method offers substantial performance gain over conventional RAKE and MMSE equalizer.</P>
Nonlinear preprocessing method for detecting peaks from gas chromatograms
Shim, Byonghyo,Min, Hyeyoung,Yoon, Sungroh BioMed Central 2009 BMC bioinformatics Vol.10 No.-
<P><B>Background</B></P><P>The problem of locating valid peaks from data corrupted by noise frequently arises while analyzing experimental data. In various biological and chemical data analysis tasks, peak detection thus constitutes a critical preprocessing step that greatly affects downstream analysis and eventual quality of experiments. Many existing techniques require the users to adjust parameters by trial and error, which is error-prone, time-consuming and often leads to incorrect analysis results. Worse, conventional approaches tend to report an excessive number of false alarms by finding fictitious peaks generated by mere noise.</P><P><B>Results</B></P><P>We have designed a novel peak detection method that can significantly reduce parameter sensitivity, yet providing excellent peak detection performance and negligible false alarm rates from gas chromatographic data. The key feature of our new algorithm is the successive use of peak enhancement algorithms that are deliberately designed for a gradual improvement of peak detection quality. We tested our approach with real gas chromatograms as well as intentionally contaminated spectra that contain Gaussian or speckle-type noise.</P><P><B>Conclusion</B></P><P>Our results demonstrate that the proposed method can achieve near perfect peak detection performance while maintaining very small false alarm probabilities in case of gas chromatograms. Given the fact that biological signals appear in the form of peaks in various experimental data and that the propose method can easily be extended to such data, our approach will be a useful and robust tool that can help researchers highlight valid signals in their noisy measurements.</P>