Directional Training for FDD Massive MIMO
| dc.contributor.advisor | Sabharwal, Ashutosh | en_US |
| dc.creator | Zhang, Xing | en_US |
| dc.date.accessioned | 2017-08-01T15:32:26Z | en_US |
| dc.date.available | 2017-12-01T06:01:05Z | en_US |
| dc.date.created | 2016-12 | en_US |
| dc.date.issued | 2016-12-05 | en_US |
| dc.date.submitted | December 2016 | en_US |
| dc.date.updated | 2017-08-01T15:32:26Z | en_US |
| dc.description.abstract | To achieve the full array gain of massive MIMO in downlink trans- mission, the base station requires the knowledge of full downlink channel state information (CSI). In frequency-division duplexing (FDD) mode, full channel training in antenna space with feedback is required to obtain full downlink CSI and the overhead scales with the number of antennas at the base station. As a result, for large-antenna MIMO, the downlink CSI acquisition overhead will consume a large amount of coherence time and lead to much spectral efficiency loss. In this thesis, to reduce the large downlink CSI acquisition overhead and to let FDD still benefit from the array gain of massive MIMO, we propose directional training for FDD massive MIMO systems. Directional training exploits the fact that the number of angle-of-arrival/angle-of- departure (AoA/AoD) is much smaller than the number of antennas at the base station. Also, based on our measured channel data, we note that the number of AoD is nearly independent of the number of antennas at the base station. Directional training first leverages the possible AoA/AoD reciprocity between uplink and downlink to locate the AoD set of downlink channel utilizing uplink CSI only and then trains the downlink channel using the AoD set only. Therefore, the overhead of directional training will not scale with the number of antennas at the base station and will be much smaller than the overhead of full training. We conduct extensive channel measurement employing a 64-antenna base station at two different bands in the indoor environment to evaluate the downlink beamforming performance of directional training using zero-forcing beamforming. The results show that in the perfect CSI case, directional training performs close to full training in the line-of-sight scenarios and leads to about 17% achievable rate loss in the non-line-of-sight scenarios when serving two mobiles. In contrast, for the imperfect CSI case, directional training outperforms full training by 155% in the line-of-sight scenarios and 100% in the non-line-of-sight scenarios in terms of spectral efficiency when channel coherence symbols length is 200. Hence, directional training is a promising scheme for FDD massive MIMO to obtain downlink CSI. | en_US |
| dc.embargo.terms | 2017-12-01 | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.citation | Zhang, Xing. "Directional Training for FDD Massive MIMO." (2016) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/95973">https://hdl.handle.net/1911/95973</a>. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/95973 | en_US |
| dc.language.iso | eng | en_US |
| dc.rights | Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder. | en_US |
| dc.subject | FDD | en_US |
| dc.subject | massive MIMO | en_US |
| dc.subject | angle-of-arrival | en_US |
| dc.title | Directional Training for FDD Massive MIMO | en_US |
| dc.type | Thesis | en_US |
| dc.type.material | Text | en_US |
| thesis.degree.department | Electrical and Computer Engineering | en_US |
| thesis.degree.discipline | Engineering | en_US |
| thesis.degree.grantor | Rice University | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Science | en_US |
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