Joint activity detection and channel estimation via Bayesian orthogonal matching pursuit
| Autor: | Namik Kim, Kwang Bok Lee, Euitaek Lee, Jinyoup Ahn |
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| Rok vydání: | 2017 |
| Předmět: |
Channel (digital image)
Computer science Bayesian probability 020302 automobile design & engineering 020206 networking & telecommunications 02 engineering and technology Matching pursuit Signal-to-noise ratio Distribution (mathematics) 0203 mechanical engineering 0202 electrical engineering electronic engineering information engineering Maximum a posteriori estimation Greedy algorithm Algorithm Communication channel |
| Zdroj: | ICTC |
| Popis: | In this paper, we propose a novel method to jointly estimate the activities and channel coefficients of devices in massive machine-type communications (mMTC) systems. We formulate a maximum a posteriori probability (MAP) estimation problem by exploiting the statistical prior information including the channel distribution and device activity probability. The formulated MAP problem is solved by a greedy algorithm, named Bayesian orthogonal matching pursuit (BOMP). We observe that the proposed method improves the activity detection and channel estimation performance compared to the conventional methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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