Analytical modeling of heterogeneous cellular networks: geometry, coverage, and capacity
"This self-contained introduction shows how stochastic geometry techniques can be used for studying the behaviour of heterogeneous cellular networks (HCNs). The unified treatment of analytic results and approaches, collected for the first time in a single volume, includes the mathematical tools...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge [u.a.]
Cambridge Univ. Press
2014
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | "This self-contained introduction shows how stochastic geometry techniques can be used for studying the behaviour of heterogeneous cellular networks (HCNs). The unified treatment of analytic results and approaches, collected for the first time in a single volume, includes the mathematical tools and techniques used to derive them. A single canonical problem formulation encompassing the analytic derivation of Signal to Interference plus Noise Ratio (SINR) distribution in the most widely-used deployment scenarios is presented, together with applications to systems based on the 3GPP-LTE standard, and with implications of these analyses on the design of HCNs. An outline of the different releases of the LTE standard and the features relevant to HCNs is also provided. A valuable reference for industry practitioners looking to improve the speed and efficiency of their network design and optimization workflow, and for graduate students and researchers seeking tractable analytical results for performance metrics in wireless HCNs"-- |
| Beschreibung: | XVII, 172 S. |
| ISBN: | 9781107050945 |
Internformat
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Datensatz im Suchindex
| _version_ | 1804152113883774976 |
|---|---|
| adam_text | Contents
Preface
page [x
Acknowledgements
xiii
List of notation xv
List of acronyms and abbreviations
xvi
Introduction l
1.1
Wireless-channel model
2
1.1.1
Path-loss model
2
1.1.2
Fading model
3
1.2
Distribution of the SINR at an arbitrary user
4
1.3
Why SINR distributions are usually found via simulation
6
1.4
The role of analytic modeling
7
Structure of the SINR calculation problem
8
2.1
Statement of the SINR calculation problem
8
2.1.1
Candidate serving BSs and the serving BS
8
■4
2.1.2
Basic definitions
9
2.2
SINR distributions
10
2.2.1
Joint CCDF of SINRs from candidate serving BSs
10
2.2.2
Joint CCDF of SINRs from BSs ordered by serving BS
selection criterion
11
2.2.3
Conventions and notation
12
2.3
The canonical SINR probability
12
2.3.1
Form of joint CCDF of SINRs from candidate serving BSs
13
2.3.2
Form of joint CCDF of SINRs from BSs ordered by serving
BS selection criterion
13
2.3.3
Joint CCDF of SINR in canonical probability form
14
2.4
Calculation of the canonical probability
15
2.4.1
Z-matrices and M-matrices
15
2.4.2
Expressions for P{AX>b}
16
2.4.3
Expressions for the canonical probability P{ AX
>
Wb)
18
2.4.4
Approximating arbitrary PDFs by mixtures of
Erlang
PDFs
19
vi
Contents
2.5
Full solution to the canonical probability problem
21
2.5.1
Determining when a Z-matrix is an M-matrix
21
2.5.2
Analytic form of Laplace transform of
W
-1
Poisson
point processes
23
3.1
Stochastic models for BS locations
23
3.2
Complete spatial randomness
24
3.3
The
Poisson
point process
25
3.4
Theorems about PPPs
26
3.4.1
Mapping theorem
26
3.4.2
Superposition theorem
28
3.4.3
Coloring theorem 2X
3.4.4
Marking theorem
31
3.5
Applicability of PPP to real-world deployments
32
3.6
Other models for BS locations
34
SINR analysis for a single tier with fixed power
35
4.1
Introduction
35
4.2
Distribution of total interference power in a single-tier BS deployment
35
4.2.1
PPP of received powers at user from BSs in a tier
35
4.2.2
Distribution of total received power from all BSs in a tier
37
4.3
Distribution of SINR in a single-tier BS deployment
4
1
4.3.1
Serving BS known and fixed
42
4.3.2
A note on serving BS selection criteria
45
4.3.3
Serving BS is the one nearest to the user
45
4.3.4
Serving BS is the one received most strongly at the user
55
SINR analysis for multiple tiers with fixed powers
71
5.1
Introduction
71
5.2
Joint CCDF of SINR from candidate serving BSs
72
5.2.1
Candidate serving BS in each tier is the one nearest to the user
72
5.2.2
Application: camping probability in a macro-femto network.
78
5.2.3
Candidate serving BS in each tier is the one received most
strongly at the user
83
5.2.4
Application: coverage probability in an HCN
92
5.3
Distributions of serving tier and SINR from serving BS
98
5.3.1
Serving BS is the nearest (after selection bias) candidate
serving BS
99
5.3.2
Serving BS is the strongest (after selection bias) candidate
serving
B S
102
5.3.3
Serving BS is the max-SINR (after selection bias) candidate
serving BS
116
5.4
Selection bias and the need for interference control
119
Contents
vii
6 SINR
analysis with power control
122
6.1
Introduction
122
6.2
Power control from the transmitter perspective
122
6.3
Types of power control
123
6.4
Distribution of SINR under power control
124
6.4.1
Distribution of received power with i.i.d. BS transmit powers
124
6.4.2
SINR distribution with non-adaptive power control
125
6.4.3
Application: elCIC and felCIC in LTE
126
6.4.4
Interference power at the receiver of a given link under OLPC
128
6.4.5
Distribution of distance from BS to served user
130
6.4.6
CCDFofSINR when all BSs use OLPC
135
6.4.7
SINR distribution under CLPC
139
7
Spectral and energy efficiency analysis
141
7.1
Introduction
141
7.2
Spectral efficiency
142
7.2.1
Spectral efficiency on the link to an arbitrarily located user
142
7.2.2
Spectral efficiency of an HCN
144
7.2.3
Application: spectral efficiency of a macro-pico LTE HCN
with elCIC
147
7.3
Energy efficiency
153
8
Closing thoughts: future heterogeneous networks
154
8.1
Introduction
154
8.2
Analysis of a network with D2D links
154
8.3
The role of WiFi in future HCNs
156
8.4
Evolution of the network infrastructure
157
8.5
New directions in analysis
157
Appendix A Some common probability distributions
159
A.I Discrete distributions
159
A.
1.1
Uniform distribution
159
A.
1.2
Bernoulli distribution
159
A.
1.3
Binomial distribution
159
A.
1.4
Poisson
distribution
160
A.
1.5
Negative binomial distribution
160
A.
1.6
Generalized negative binomial distribution
160
A.
2
Continuous distributions
160
A.
2.1
Uniform distribution
160
A.2.2 Normal or Gaussian distribution
161
A.
2.3
Circularly symmetric complex Gaussian distribution
161
A.2.4 Rayleigh distribution
161
A.
2.5
Exponential distribution
161
viii Contents
Α.
2.6 Erlang
distribution
162
A.2.7 Gamma distribution
162
A.
2.8
Nakagami distribution
162
A.2.9
Lognormal
distribution
162
Appendix
В
HCNs in LTE
163
B.I 3GPPandLTE
163
B.2 Support for HCNs in LTE 1
63
References
Author index
170
Subject index 1
7
1
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| id | DE-604.BV041795194 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:05:33Z |
| institution | BVB |
| isbn | 9781107050945 |
| language | English |
| lccn | 2013036071 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027240729 |
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| physical | XVII, 172 S. |
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| publisher | Cambridge Univ. Press |
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| spelling | Mukherjee, Sayandev 1970- Verfasser (DE-588)1051994454 aut Analytical modeling of heterogeneous cellular networks geometry, coverage, and capacity Sayandev Mukherjee 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2014 XVII, 172 S. txt rdacontent n rdamedia nc rdacarrier "This self-contained introduction shows how stochastic geometry techniques can be used for studying the behaviour of heterogeneous cellular networks (HCNs). The unified treatment of analytic results and approaches, collected for the first time in a single volume, includes the mathematical tools and techniques used to derive them. A single canonical problem formulation encompassing the analytic derivation of Signal to Interference plus Noise Ratio (SINR) distribution in the most widely-used deployment scenarios is presented, together with applications to systems based on the 3GPP-LTE standard, and with implications of these analyses on the design of HCNs. An outline of the different releases of the LTE standard and the features relevant to HCNs is also provided. A valuable reference for industry practitioners looking to improve the speed and efficiency of their network design and optimization workflow, and for graduate students and researchers seeking tractable analytical results for performance metrics in wireless HCNs"-- Heterogenität (DE-588)4201275-2 gnd rswk-swf Modell (DE-588)4039798-1 gnd rswk-swf Zellulares Mobilfunksystem (DE-588)4387563-4 gnd rswk-swf Zellulares Mobilfunksystem (DE-588)4387563-4 s Heterogenität (DE-588)4201275-2 s Modell (DE-588)4039798-1 s DE-604 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027240729&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Mukherjee, Sayandev 1970- Analytical modeling of heterogeneous cellular networks geometry, coverage, and capacity Heterogenität (DE-588)4201275-2 gnd Modell (DE-588)4039798-1 gnd Zellulares Mobilfunksystem (DE-588)4387563-4 gnd |
| subject_GND | (DE-588)4201275-2 (DE-588)4039798-1 (DE-588)4387563-4 |
| title | Analytical modeling of heterogeneous cellular networks geometry, coverage, and capacity |
| title_auth | Analytical modeling of heterogeneous cellular networks geometry, coverage, and capacity |
| title_exact_search | Analytical modeling of heterogeneous cellular networks geometry, coverage, and capacity |
| title_full | Analytical modeling of heterogeneous cellular networks geometry, coverage, and capacity Sayandev Mukherjee |
| title_fullStr | Analytical modeling of heterogeneous cellular networks geometry, coverage, and capacity Sayandev Mukherjee |
| title_full_unstemmed | Analytical modeling of heterogeneous cellular networks geometry, coverage, and capacity Sayandev Mukherjee |
| title_short | Analytical modeling of heterogeneous cellular networks |
| title_sort | analytical modeling of heterogeneous cellular networks geometry coverage and capacity |
| title_sub | geometry, coverage, and capacity |
| topic | Heterogenität (DE-588)4201275-2 gnd Modell (DE-588)4039798-1 gnd Zellulares Mobilfunksystem (DE-588)4387563-4 gnd |
| topic_facet | Heterogenität Modell Zellulares Mobilfunksystem |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027240729&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT mukherjeesayandev analyticalmodelingofheterogeneouscellularnetworksgeometrycoverageandcapacity |