Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Low-overhead Communications in IoT N...
~
Shi, Yuanming.
Low-overhead Communications in IoT Networks = Structured Signal Processing Approaches /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Low-overhead Communications in IoT Networks/ by Yuanming Shi, Jialin Dong, Jun Zhang.
Reminder of title:
Structured Signal Processing Approaches /
Author:
Shi, Yuanming.
other author:
Dong, Jialin.
Description:
XIV, 152 p. 350 illus., 19 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Engineering. -
Online resource:
https://doi.org/10.1007/978-981-15-3870-4
ISBN:
9789811538704
Low-overhead Communications in IoT Networks = Structured Signal Processing Approaches /
Shi, Yuanming.
Low-overhead Communications in IoT Networks
Structured Signal Processing Approaches /[electronic resource] :by Yuanming Shi, Jialin Dong, Jun Zhang. - 1st ed. 2020. - XIV, 152 p. 350 illus., 19 illus. in color.online resource.
Chapter 1. Introduction -- Chapter 2. Sparse Linear Model -- Chapter 3. Blind Demixing -- Chapter 4. Sparse Blind Demixing -- Chapter 5. Shuffled Linear Regression -- Chapter 6. Learning Augmented Methods -- Chapter 7. Conclusions and Discussions -- Chapter 8. Appendix. .
The recent developments in wireless communications, networking, and embedded systems have driven various innovative Internet of Things (IoT) applications, e.g., smart cities, mobile healthcare, autonomous driving and drones. A common feature of these applications is the stringent requirements for low-latency communications. Considering the typical small payload size of IoT applications, it is of critical importance to reduce the size of the overhead message, e.g., identification information, pilot symbols for channel estimation, and control data. Such low-overhead communications also help to improve the energy efficiency of IoT devices. Recently, structured signal processing techniques have been introduced and developed to reduce the overheads for key design problems in IoT networks, such as channel estimation, device identification, and message decoding. By utilizing underlying system structures, including sparsity and low rank, these methods can achieve significant performance gains. This book provides an overview of four general structured signal processing models: a sparse linear model, a blind demixing model, a sparse blind demixing model, and a shuffled linear model, and discusses their applications in enabling low-overhead communications in IoT networks. Further, it presents practical algorithms based on both convex and nonconvex optimization approaches, as well as theoretical analyses that use various mathematical tools.
ISBN: 9789811538704
Standard No.: 10.1007/978-981-15-3870-4doiSubjects--Topical Terms:
561152
Engineering.
LC Class. No.: TA1-2040
Dewey Class. No.: 620
Low-overhead Communications in IoT Networks = Structured Signal Processing Approaches /
LDR
:03097nam a22003975i 4500
001
1027901
003
DE-He213
005
20200701055502.0
007
cr nn 008mamaa
008
210318s2020 si | s |||| 0|eng d
020
$a
9789811538704
$9
978-981-15-3870-4
024
7
$a
10.1007/978-981-15-3870-4
$2
doi
035
$a
978-981-15-3870-4
050
4
$a
TA1-2040
072
7
$a
TBC
$2
bicssc
072
7
$a
TEC000000
$2
bisacsh
072
7
$a
TBC
$2
thema
082
0 4
$a
620
$2
23
100
1
$a
Shi, Yuanming.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1324382
245
1 0
$a
Low-overhead Communications in IoT Networks
$h
[electronic resource] :
$b
Structured Signal Processing Approaches /
$c
by Yuanming Shi, Jialin Dong, Jun Zhang.
250
$a
1st ed. 2020.
264
1
$a
Singapore :
$b
Springer Singapore :
$b
Imprint: Springer,
$c
2020.
300
$a
XIV, 152 p. 350 illus., 19 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
Chapter 1. Introduction -- Chapter 2. Sparse Linear Model -- Chapter 3. Blind Demixing -- Chapter 4. Sparse Blind Demixing -- Chapter 5. Shuffled Linear Regression -- Chapter 6. Learning Augmented Methods -- Chapter 7. Conclusions and Discussions -- Chapter 8. Appendix. .
520
$a
The recent developments in wireless communications, networking, and embedded systems have driven various innovative Internet of Things (IoT) applications, e.g., smart cities, mobile healthcare, autonomous driving and drones. A common feature of these applications is the stringent requirements for low-latency communications. Considering the typical small payload size of IoT applications, it is of critical importance to reduce the size of the overhead message, e.g., identification information, pilot symbols for channel estimation, and control data. Such low-overhead communications also help to improve the energy efficiency of IoT devices. Recently, structured signal processing techniques have been introduced and developed to reduce the overheads for key design problems in IoT networks, such as channel estimation, device identification, and message decoding. By utilizing underlying system structures, including sparsity and low rank, these methods can achieve significant performance gains. This book provides an overview of four general structured signal processing models: a sparse linear model, a blind demixing model, a sparse blind demixing model, and a shuffled linear model, and discusses their applications in enabling low-overhead communications in IoT networks. Further, it presents practical algorithms based on both convex and nonconvex optimization approaches, as well as theoretical analyses that use various mathematical tools.
650
0
$a
Engineering.
$3
561152
650
0
$a
Computer organization.
$3
596298
650
0
$a
Machine learning.
$3
561253
650
1 4
$a
Engineering, general.
$3
669723
650
2 4
$a
Computer Systems Organization and Communication Networks.
$3
669309
650
2 4
$a
Machine Learning.
$3
1137723
700
1
$a
Dong, Jialin.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1324383
700
1
$a
Zhang, Jun.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
796123
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9789811538698
776
0 8
$i
Printed edition:
$z
9789811538711
776
0 8
$i
Printed edition:
$z
9789811538728
856
4 0
$u
https://doi.org/10.1007/978-981-15-3870-4
912
$a
ZDB-2-ENG
912
$a
ZDB-2-SXE
950
$a
Engineering (SpringerNature-11647)
950
$a
Engineering (R0) (SpringerNature-43712)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login