Wireless localization for mmWave networks in urban environments
Abstract Millimeter wave (mmWave) technology is expected to be a major component of 5G wireless networks. Ultra-wide bandwidths of mmWave signals and the possibility of utilizing large number of antennas at the transmitter and the receiver allow accurate identification of multipath components in tem...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2018-06-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13634-018-0556-6 |
| _version_ | 1819132700314828800 |
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| author | Macey Ruble İsmail Güvenç |
| author_facet | Macey Ruble İsmail Güvenç |
| author_sort | Macey Ruble |
| collection | DOAJ |
| description | Abstract Millimeter wave (mmWave) technology is expected to be a major component of 5G wireless networks. Ultra-wide bandwidths of mmWave signals and the possibility of utilizing large number of antennas at the transmitter and the receiver allow accurate identification of multipath components in temporal and angular domains, making mmWave systems advantageous for localization applications. In this paper, we analyze the performance of a two-step mmWave localization approach that can utilize time-of-arrival, angle-of-arrival, and angle-of-departure from multiple nodes in an urban environment with both line-of-sight (LOS) and non-LOS (NLOS) links. Networks with/without radio-environmental mapping (REM) are considered, where a network with REM is able to localize nearby scatterers. Estimation of a UE location is challenging due to large numbers of local optima in the likelihood function. To address this problem, a gradient-assisted particle filter (GAPF) estimator is proposed to accurately estimate a user equipment (UE) location as well as the locations of nearby scatterers. Monte-Carlo simulations show that the GAPF estimator performance matches the Cramer-Rao bound (CRB). The estimator is also used to create a REM. It is seen that significant localization gains can be achieved by increasing beam directionality or by utilizing REM. |
| first_indexed | 2024-12-22T09:35:34Z |
| format | Article |
| id | doaj.art-5ea9be01b79647d1a3ed6647d780e7d9 |
| institution | Directory Open Access Journal |
| issn | 1687-6180 |
| language | English |
| last_indexed | 2024-12-22T09:35:34Z |
| publishDate | 2018-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-5ea9be01b79647d1a3ed6647d780e7d92022-12-21T18:30:50ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802018-06-012018111910.1186/s13634-018-0556-6Wireless localization for mmWave networks in urban environmentsMacey Ruble0İsmail Güvenç1Department of Electrical and Computer Engineering, North Carolina State UniversityDepartment of Electrical and Computer Engineering, North Carolina State UniversityAbstract Millimeter wave (mmWave) technology is expected to be a major component of 5G wireless networks. Ultra-wide bandwidths of mmWave signals and the possibility of utilizing large number of antennas at the transmitter and the receiver allow accurate identification of multipath components in temporal and angular domains, making mmWave systems advantageous for localization applications. In this paper, we analyze the performance of a two-step mmWave localization approach that can utilize time-of-arrival, angle-of-arrival, and angle-of-departure from multiple nodes in an urban environment with both line-of-sight (LOS) and non-LOS (NLOS) links. Networks with/without radio-environmental mapping (REM) are considered, where a network with REM is able to localize nearby scatterers. Estimation of a UE location is challenging due to large numbers of local optima in the likelihood function. To address this problem, a gradient-assisted particle filter (GAPF) estimator is proposed to accurately estimate a user equipment (UE) location as well as the locations of nearby scatterers. Monte-Carlo simulations show that the GAPF estimator performance matches the Cramer-Rao bound (CRB). The estimator is also used to create a REM. It is seen that significant localization gains can be achieved by increasing beam directionality or by utilizing REM.http://link.springer.com/article/10.1186/s13634-018-0556-65GAOAAODTOACRLBLocalization |
| spellingShingle | Macey Ruble İsmail Güvenç Wireless localization for mmWave networks in urban environments EURASIP Journal on Advances in Signal Processing 5G AOA AOD TOA CRLB Localization |
| title | Wireless localization for mmWave networks in urban environments |
| title_full | Wireless localization for mmWave networks in urban environments |
| title_fullStr | Wireless localization for mmWave networks in urban environments |
| title_full_unstemmed | Wireless localization for mmWave networks in urban environments |
| title_short | Wireless localization for mmWave networks in urban environments |
| title_sort | wireless localization for mmwave networks in urban environments |
| topic | 5G AOA AOD TOA CRLB Localization |
| url | http://link.springer.com/article/10.1186/s13634-018-0556-6 |
| work_keys_str_mv | AT maceyruble wirelesslocalizationformmwavenetworksinurbanenvironments AT ismailguvenc wirelesslocalizationformmwavenetworksinurbanenvironments |