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The aim of this study was to examine the impact of 3-dimensional (3D) computed tomographic (CT) guided procedural planning for left atrial appendage (LAA) occlusion on the early operator WATCHMAN learning curve.Traditional WATCHMAN implantation is dependent on 2-dimensional transesophageal echocardiographic (TEE) sizing and intraprocedural guidance.LAA occlusion with the WATCHMAN device was performed...
This paper presents an iterative soft decision based lattice reduction (LR) aided Schnorr-Euchner (SE) multiple-input-multiple-output (MIMO) decoding algorithm, which reduces the gap in performance between suboptimal K-best and maximum likelihood (ML) detectors. Following IEEE 802.16e standard, we develop an iterative soft decoding algorithm for 4×4 MIMO with different modulation schemes. Using this...
This paper presents an iterative soft decision based adaptive K-best multiple-input-multiple-output (MIMO) decoding algorithm. It has the flexibility of changing the list size, K with respect to the channel condition, although the accurate measurement of signal to noise ratio (SNR) is not required. Moreover, the concept of iterative soft decision based lattice reduction (LR)-aided minimum mean square...
Lattice reduction (LR) aided detectors mitigate the exponentially increasing complexity of large multiple-input, multiple-output (MIMO) systems while achieving near-optimal performance with low computational complexity. In this paper, a channel-adaptive complex-domain LR-aided K-best MIMO detector is presented that reduces the gap between the K-best sphere decoding (SD) detector and the maximum likelihood...
The challenges in satellite communication (SatCom) include but not limited to the customary complications of telecommunication such as channel condition, signal to noise ratio (SNR), etc. SatCom system is also prone to transient and permanent radiations hazards. Hence, in spite of the harsh environmental factors (weather phenomena, solar events, etc), a SatCom system must maintain reliable and predictable...
This paper presents a very-large-scale integration (VLSI) design to reconstruct compressively sensed data. The proposed digital design recovers signal compressed by specific analog-to-digital converter (ADC). Our design is based on a modified iterative hard threshold (IHT) reconstruction algorithm to adapt unknown and varying degree of sparsity of the signal. The algorithm is composed empirically...
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