DC Field | Value | Language |
---|---|---|
dc.contributor.author | KIM, HWAN JIN | ko |
dc.contributor.author | Choi, Junil | ko |
dc.date.accessioned | 2019-09-10T01:20:09Z | - |
dc.date.available | 2019-09-10T01:20:09Z | - |
dc.date.created | 2019-09-09 | - |
dc.date.created | 2019-09-09 | - |
dc.date.created | 2019-09-09 | - |
dc.date.issued | 2018-12 | - |
dc.identifier.citation | 2018 IEEE Global Communications Conference, GLOBECOM 2018 | - |
dc.identifier.uri | http://hdl.handle.net/10203/267412 | - |
dc.description.abstract | Massive multiple-input multiple-output (MIMO) can improve the overall system performance significantly. Massive MIMO systems, however, may require a large number of radio frequency (RF) chains that could cause high cost and power consumption issues. One of promising approaches to resolve these issues is using low-resolution analog-to-digital converters (ADCs) at base stations. Channel estimation becomes a difficult task by using low-resolution ADCs though. This paper addresses the channel estimation problem for massive MIMO systems using one-bit ADCs when the channels are spatially and temporally correlated. Based on the Bussgang decomposition, which reformulates a non-linear one-bit quantization to a statistically equivalent linear operator, the Kalman filter is used to estimate the spatially and temporally correlated channel by assuming the quantized noise follows a Gaussian distribution. Numerical results show that the proposed technique can improve the channel estimation quality significantly by properly exploiting the spatial and temporal correlations of channels. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Channel Estimation for One-Bit Massive MIMO Systems Exploiting Spatio-Temporal Correlations | - |
dc.type | Conference | - |
dc.identifier.wosid | 000465774302111 | - |
dc.identifier.scopusid | 2-s2.0-85063456089 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 2018 IEEE Global Communications Conference, GLOBECOM 2018 | - |
dc.identifier.conferencecountry | AR | - |
dc.identifier.conferencelocation | Abu Dhabi | - |
dc.identifier.doi | 10.1109/GLOCOM.2018.8647574 | - |
dc.contributor.localauthor | Choi, Junil | - |
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