심병효 교수

In this paper, we present a novel algorithmic noise-tolerance (ANT) technique referred to as reduced precision redundancy (RPR). RPR requires a reduced precision replica whose output can be employed as the corrected output in case the original system computes erroneously. When combined with voltage overscaling (VOS), the resulting soft digital signal processing system achieves up to 60% and 44% energy savings with no loss in the signal-to-noise ratio (SNR) for receive filtering in a QPSK system

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

In this paper, we present energy-efficient soft error-tolerant techniques for digital signal processing (DSP) systems. The proposed technique, referred to as algorithmic soft error-tolerance (ASET), employs low-complexity estimators of a main DSP block to achieve reliable operation in the presence of soft errors. Three distinct ASET techniques - spatial, temporal and spatio-temporal- are presented. For frequency selective finite-impulse response (FIR) filtering, it is shown that the proposed tec

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, we present a near ML-achieving sphere decoding algorithm that reduces the number of search operations in the sphere-constrained search. Specifically, by adding a probabilistic noise constraint on top of the sphere constraint, a more stringent necessary condition is provided, particularly at an early stage, and, hence, branches unlikely to be survived are removed in the early stage of s

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

We propose a low-power digital filtering technique based on voltage overscaling (VOS) and a novel algorithmic noise-tolerant (ANT) technique referred to as reduced precision redundancy (RPR). VOS implies scaling of the supply voltage beyond the critical voltage required for correct operation. RPR involves having a reduced precision replica whose output can be employed as the final output in case the original filter computes erroneously. In addition, an LSB estimator is also employed to compensat

In this paper, we consider a detection problem of the underdetermined system when the input vector is sparse and its elements are chosen from a set of finite alphabets. This scenario is popular and embraces many of current and future wireless communication systems. We show that a simple modification of multipath matching pursuit (MMP), recently proposed parallel greedy search algorithm, is effective in recovering the discrete and sparse input signals. We also show that the addition of cross vali

In this paper, we present energy-efficient soft error (SE)-tolerant techniques for digital signal processing (DSP) systems. The proposed technique, referred to as algorithmic soft error-tolerance (ASET), employs an low-complexity estimator of a main DSP block to guarantee reliability in presence of soft errors either in the MDSP or the estimator. For FIR filtering, it is shown that the proposed technique provides robustness to soft error rates of up to P/sub er/=10/sup -2/ in single-event upset

근래 전 세계적으로 스마트 폰의 수요가 급증하면서 기존의 3G 표준에 비해 높은 데이터 전송률을 제공하는 long term evolution (LTE) 서비스가 활발히 보급되고 있다. 특히, 이동통신 강국인 우리나라는 LTE의 최신 릴리즈인 LTE-Advanced (LTE-A) 서비스를 최근 시작하였다. 높은 데이터 전송률을 얻기 위한 LTE와 LTE-A 시스템의 핵심기술로 다중입출력 안테나 (multiple-input-multiple-output; MIMO)기술을 들 수 있다. MIMO 기술은 주파수와 전력의 증가 없이 안테나 수에 비례하는 채널용량을 얻을 수 있는 장점으로 큰 주목을 받아왔으며 다양한 측면에서 진화 발전이 이루어지고 있다. 본 논문에서는 단일사용자 MIMO에서 다중사용자 MIMO, 그리고 최근 주목받고 있는 대용량 MIMO까지 MIMO기술의 이론적 배경 및 시스템을 구현하기 위해 필요한 고려사항들을 살펴본다. Recent exploration of smart-ph

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 path metric, proposed method accounts for the contribution of non-causal symbols with the aid of per-path minimum mean square error (MMSE) symbol estimation. The ML and MMSE combined cost metric results in the tight necessary condition for sphere decision a

A complexity analysis of discrete multitone (DMT) and single-carrier modulation (SCM) in the context of a very high-speed digital subscriber line (VDSL) is presented in this paper. In addition to the traditional arithmetic complexity measures such as the number of multiply-and-accumulate (MAC) operations, we also compute the memory requirements. Furthermore, we normalize these metrics with respect to the number of information bits transmitted (rate normalized) and scale with respect to data path

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> 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 resul

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.

In this paper, we propose a radius-adaptive sphere decoding algorithm that reduces the number of operations in sphere- constrained search while achieving performance close to ML decoding. Specifically, by adding a probabilistic noise constraint on top of sphere constraint, a more stringent necessary condition is provided, particularly at an early stage, and hence many branches that are unlikely to be selected are removed in the early stage of sphere search. From the simulation in a frequency sel

In this paper, we present an algorithmic noise tolerance (ANT) technique for low-power digital signal processing systems. The proposed technique employs a low-complexity forward-backward predictor to correct errors in a main DSP (MDSP) block due to voltage overscaling, which is an ultra low-voltage operating condition. For a frequency selective FIR filtering, it is shown that the proposed technique achieves up to 43% power savings over an optimally voltage scaled MDSP with a 5% area overhead.