Byonghyo Shim

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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(More)
As a greedy algorithm to recover sparse signals from compressed measurements, orthogonal matching pursuit (OMP) algorithm has received much attention in recent years. In this paper, we introduce an extension of the OMP for pursuing efficiency in reconstructing sparse signals. Our approach, henceforth referred to as generalized OMP (gOMP), is literally a(More)
Orthogonal matching pursuit (OMP) is a greedy search algorithm popularly being used for the recovery of compressive sensed sparse signals. In this correspondence, we show that if the isometry constant &#x03B4;<i>K</i>+1 of the sensing matrix &#x03A6; satisfies &#x03B4;<i>K</i>+1 &lt;; 1/(1/&#x221A;<i>K</i>+1) then the OMP algorithm can perfectly recover(More)
Recently, the mobile communication industry is moving rapidly towards long-term evolution (LTE) systems. The leading carriers and vendors are committed to launching LTE service in the near future and, in fact, number of major operators such as Verizon has initiated LTE service already. LTE aims to provide improved service quality over 3G systems in terms of(More)
In this paper, we propose an algorithm referred to as multipath matching pursuit (MMP) that investigates multiple promising candidates to recover sparse signals from compressed measurements. Our method is inspired by the fact that the problem to find the candidate that minimizes the residual is readily modeled as a combinatoric tree search problem and the(More)
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(More)
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(More)
In this paper, we present energy-efficient soft error (E-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(More)
Block diagonalization (BD) algorithm is a generalization of the channel inversion that converts multiuser multiinput multi-output (MIMO) broadcast channel into single-user MIMO channel without inter-user interference. In this paper, we combine the BD technique with a minimum mean square error vector precoding (MMSE-VP) for achieving further gain in(More)