國立虎尾科技大學 |

AI-enabled spectrum sharing = recent advances in wireless edge networks /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	AI-enabled spectrum sharing/ by Lin Zhang ... [et al.].
其他題名:	recent advances in wireless edge networks /
其他作者:	Zhang, Lin.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	x, 84 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Internet of Things. -
電子資源:	https://doi.org/10.1007/978-981-97-7644-3
ISBN:	9789819776443

AI-enabled spectrum sharing = recent advances in wireless edge networks /
AI-enabled spectrum sharingrecent advances in wireless edge networks /[electronic resource] :by Lin Zhang ... [et al.]. - Singapore :Springer Nature Singapore :2024. - x, 84 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5776. - SpringerBriefs in computer science..

Chapter 1 Introductions and Preliminaries -- Chapter 2 AI-Enabled opportunistic Spectrum Sharing -- Chapter 3 AI-Enabled Centralized Spectrum Sharing -- Chapter 4 AI-Enabled Distributed Spectrum Sharing -- Chapter 5: Conclusions.

Wireless edge networks aim to provide last-mile wireless connections between access points and diversified wireless end devices. Recent years witness the rapid development of wireless communication ecosystems including fundamental theory breakthroughs, manufacture capability improvements, as well as the explosively increasing wireless end devices and service demands. It is known that spectrum is the irreplaceable resource for wireless transmissions in edge networks. Nevertheless, it is quite challenging and inefficient to allocate dedicated spectrum for each single transmission link due to the severe shortage of spectrum resource. Alternatively, by enabling different links to use the same spectrum, spectrum sharing is envisioned to be a promising paradigm to properly accommodate the conflict between the scarce spectrum resource and substantial spectrum demands. Conventionally, model-driven optimization methods are widely adopted to optimize the spectrum sharing policy in the edge network and achieve friendly coexistence among different transmission links. However, future wireless edge network is predicted to be large-scale and heterogeneous, model-driven optimization methods will be problematic such as imperfect modelling and unacceptable overheads. Different from the existing related books on spectrum sharing or spectrum management for wireless edge networks, our book leverages the artificial intelligence (AI) to achieve smart spectrum sharing for wireless edge networks and elaborates AI-enabled spectrum sharing technique in typical scenarios, which can guide the development of next-generation spectrum sharing standards, as well as provide innovative spectrum sharing methods for related practitioners, including research fellow, lecturers, and students.

ISBN: 9789819776443

Standard No.: 10.1007/978-981-97-7644-3doiSubjects--Topical Terms:

1048478
Internet of Things.

LC Class. No.: TK5103.2

Dewey Class. No.: 621.382

AI-enabled spectrum sharing = recent advances in wireless edge networks /
LDR:03086nam a2200337 a 4500 001 1138613
003 DE-He213
005 20241008130240.0
006 m d
007 cr nn 008maaau
008 250117s2024 si s 0 eng d
020 $a 9789819776443 $q (electronic bk.)
020 $a 9789819776436 $q (paper)
024 7 $a 10.1007/978-981-97-7644-3 $2 doi
035 $a 978-981-97-7644-3
040 $a GP $c GP
041 0 $a eng
050 4 $a TK5103.2
072 7 $a UKN $2 bicssc
072 7 $a COM043000 $2 bisacsh
072 7 $a UKN $2 thema
082 0 4 $a 621.382 $2 23
090 $a TK5103.2 $b .A288 2024
245 0 0 $a AI-enabled spectrum sharing $h [electronic resource] : $b recent advances in wireless edge networks / $c by Lin Zhang ... [et al.].
260 $a Singapore : $c 2024. $b Springer Nature Singapore : $b Imprint: Springer,
300 $a x, 84 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in computer science, $x 2191-5776
505 0 $a Chapter 1 Introductions and Preliminaries -- Chapter 2 AI-Enabled opportunistic Spectrum Sharing -- Chapter 3 AI-Enabled Centralized Spectrum Sharing -- Chapter 4 AI-Enabled Distributed Spectrum Sharing -- Chapter 5: Conclusions.
520 $a Wireless edge networks aim to provide last-mile wireless connections between access points and diversified wireless end devices. Recent years witness the rapid development of wireless communication ecosystems including fundamental theory breakthroughs, manufacture capability improvements, as well as the explosively increasing wireless end devices and service demands. It is known that spectrum is the irreplaceable resource for wireless transmissions in edge networks. Nevertheless, it is quite challenging and inefficient to allocate dedicated spectrum for each single transmission link due to the severe shortage of spectrum resource. Alternatively, by enabling different links to use the same spectrum, spectrum sharing is envisioned to be a promising paradigm to properly accommodate the conflict between the scarce spectrum resource and substantial spectrum demands. Conventionally, model-driven optimization methods are widely adopted to optimize the spectrum sharing policy in the edge network and achieve friendly coexistence among different transmission links. However, future wireless edge network is predicted to be large-scale and heterogeneous, model-driven optimization methods will be problematic such as imperfect modelling and unacceptable overheads. Different from the existing related books on spectrum sharing or spectrum management for wireless edge networks, our book leverages the artificial intelligence (AI) to achieve smart spectrum sharing for wireless edge networks and elaborates AI-enabled spectrum sharing technique in typical scenarios, which can guide the development of next-generation spectrum sharing standards, as well as provide innovative spectrum sharing methods for related practitioners, including research fellow, lecturers, and students.
650 2 4 $a Internet of Things. $3 1048478
650 2 4 $a Multiagent Systems. $3 1228090
650 2 4 $a Wireless and Mobile Communication. $3 1207058
650 1 4 $a Computer Communication Networks. $3 669310
650 0 $a Artificial intelligence. $3 559380
650 0 $a Wireless communication systems. $3 562740
700 1 $a Zhang, Lin. $3 888093
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
830 0 $a SpringerBriefs in computer science. $3 883114
856 4 0 $u https://doi.org/10.1007/978-981-97-7644-3
950 $a Professional and Applied Computing (SpringerNature-12059)