Sampling-based tracking of time-varying channels for millimeter wave-band communications
| Autor: | Sun Hong Lim, Jin Hyeok Yoo, Byonghyo Shim, Jisu Bae, Jun Won Choi, Sunwoo Kim |
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| Rok vydání: | 2017 |
| Předmět: |
Signal processing
Mathematical optimization Markov chain Stochastic process Computer science Sampling (statistics) 020206 networking & telecommunications 010103 numerical & computational mathematics 02 engineering and technology Kalman filter 01 natural sciences Compressed sensing Angle of arrival 0202 electrical engineering electronic engineering information engineering 0101 mathematics Particle filter Algorithm Communication channel |
| Zdroj: | ICC |
| DOI: | 10.1109/icc.2017.7996518 |
| Popis: | In this paper, we propose a new recursive sparse channel recovery algorithm which can track time-varying support of angular domain channel response vector in mobility scenario for millimeter wave-band communications. We model the angle of departure (AoD) and the angle of arrival (AoA) using discrete state Markov random process and derive joint estimation of the time-varying support and amplitude of the angular domain channel vector. Using sequential Monte Carlo (SMC) method, the proposed channel estimation scheme tracks the support by drawing the samples from a posteriori distribution of the support indices while capturing the dynamics of time-varying amplitude using Kalman filter. Our simulation results show that the proposed algorithm yields significantly better tracking performance than the existing compressed sensing schemes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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