000			03742nam a22004575i 4500
999			_c361663 _d361663 _x1
001			361663
003			ES-MaUEC
005			20230102121417.0
006			a||||fo|||| 00| 0
007			cr nn nnnaamaa
008			211027s2021 sz | s |||| 0|eng d
020			_a9783030886301
024	7		_a10.1007/978-3-030-88630-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5103.4835 _b2021 EB
100	1		_aYang, Peng
245	1	0	_aMillimeter-Wave Networks _bBeamforming Design and Performance Analysis _cby Peng Yang, Wen Wu, Ning Zhang, Xuemin Shen.
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Publising _c2021
300			_a1 recurso en línea (XII, 160 páginas) _b67 ilustraciones, 54 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aWireless Networks _x2366-1445
490	0		_aComputer Science (SpringerNature-11645)
490	0		_aComputer Science (R0) (SpringerNature-43710)
505	0		_aIntroduction -- Literature Review of mmWave Networks -- Machine Learning Based Beam Alignment in mmWave Networks -- Beamforming Training Protocol Design and Analysis -- Beamforming-Aided Cooperative Edge Caching in mmWave Dense Networks -- Summary and Future Directions.
520	3		_aThis book provides a comprehensive review and in-depth study on efficient beamforming design and rigorous performance analysis in mmWave networks, covering beam alignment, beamforming training and beamforming-aided caching. Due to significant beam alignment latency between the transmitter and the receiver in existing mmWave systems, this book proposes a machine learning based beam alignment algorithm for mmWave networks to determine the optimal beam pair with a low latency. Then, to analyze and enhance the performance of beamforming training (BFT) protocol in 802.11ad mmWave networks, an analytical model is presented to evaluate the performance of BFT protocol and an enhancement scheme is proposed to improve its performance in high user density scenarios. Furthermore, it investigates the beamforming-aided caching problem in mmWave networks, and proposes a device-to-device assisted cooperative edge caching to alleviate backhaul congestion and reduce content retrieval delay. This book concludes with future research directions in the related fields of study. The presented beamforming designs and the corresponding research results covered in this book, provides valuable insights for practical mmWave network deployment and motivate new ideas for future mmWave networking. This book targets researchers working in the fields of mmWave networks, beamforming design, and resource management as well as graduate students studying the areas of electrical engineering, computing engineering and computer science. Professionals in industry who work in this field will find this book useful as a reference.
988			_aSpringer_Computer_2021
650		7	_2embne _9138448 _aTelecomunicaciones
700	1		_aWu, Wen _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aZhang, Ning _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aShen, Xuemin _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783030886295
776	0	8	_iPrinted edition: _z9783030886318
776	0	8	_iPrinted edition: _z9783030886325
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-88630-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2022 _dz _eh _zSI