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4. EP-based Joint Active User Detection and Channel Estimation for Massive Machine-Type Communications

Author

Ahn, Jinyoup, Shim, Byonghyo, and Lee, Kwang Bok

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Information Theory
Abstract

Massive machine-type communication (mMTC) is a newly introduced service category in 5G wireless communication systems to support a variety of Internet-of-Things (IoT) applications. In recovering sparsely represented multi-user vectors, compressed sensing based multi-user detection (CS-MUD) can be used. CS-MUD is a feasible solution to the grant-free uplink non-orthogonal multiple access (NOMA) environments. In CS-MUD, active user detection (AUD) and channel estimation (CE) should be performed before data detection. In this paper, we propose the expectation propagation based joint AUD and CE (EP-AUD/CE) technique for mMTC networks. The expectation propagation (EP) algorithm is a Bayesian framework that approximates a computationally intractable probability distribution to an easily tractable distribution. The proposed technique finds the best approximation of the posterior distribution of the sparse channel vector. Using the approximate distribution, AUD and CE are jointly performed. We show by numerical simulations that the proposed technique substantially enhances AUD and CE performances over competing algorithms., Comment: submitted for a possible future publication in IEEE Transactions on Communications

Published
2018
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13. MRI classification of interspinous ligament degeneration of the lumbar spine: intraobserver and interobserver reliability and the frequency of disagreement

Author

Keorochana, Gun, Taghavi, Cyrus E., Tzeng, Shiau-Tzu, Lee, Kwang-Bok, Liao, Jen-Chung, Yoo, Jeong Hyun, and Wang, Jeffrey C.

Subjects
Medicine & Public Health, Neurosurgery, Surgical Orthopedics, Lumbar spine, Degeneration, Interspinous ligament, Classification, Magnetic resonance imaging, Reliability
Abstract

Posterior spinal ligament pathology is becoming increasingly recognized as a significant cause of low back pain. Despite the growing clinical importance of interspinous ligament degeneration in low back pain patients, formal reliability studies for the magnetic resonance imaging (MRI) evaluation of interspinous ligaments have not been performed. We proposed an MRI classification system for interspinous ligament degeneration and conducted a comprehensive reliability and reproducibility assessment. Fifty patients who had low back pain with or without leg discomfort (26 males and 24 females) with a mean age of 48.8 years (range 23–85 years) were studied. The classification for lumbar interspinous ligament degeneration was developed on the basis of the literature using mid-sagittal T1- and T2-weighted images. Three spine surgeons independently graded a total of 200 interspinous ligament levels. Intraobserver and interobserver reliability were assessed by kappa statistics. The frequency of disagreement was also identified. The intraobserver agreement was excellent in all readers (kappa range 0.840–0.901). The interobserver agreement was lower as expected, and was substantial to excellent (kappa range 0.726–0.818). Overall complete agreement was obtained in 87.8% of all interspinous ligament levels. A difference of 1, 2, and 3 grades occurred in 8.1, 3.0, and 1.1% of readings, respectively. This proposed MRI classification of interspinous ligament degeneration was simple, reliable, and reproducible. Its use as a standardized nomenclature in clinical and radiographic research may be recommended.

Published
2010

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