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The Resource Evolution of Air Interface Towards 5G : Radio Access Technology and Performance Analysis

Evolution of Air Interface Towards 5G : Radio Access Technology and Performance Analysis

Label
Evolution of Air Interface Towards 5G : Radio Access Technology and Performance Analysis
Title
Evolution of Air Interface Towards 5G
Title remainder
Radio Access Technology and Performance Analysis
Creator
Contributor
Language
eng
Member of
Cataloging source
NhCcYBP
http://library.link/vocab/creatorName
Das, Suvra Sekhar
Dewey number
621.384
Index
no index present
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Prasad, Ramjee
  • ProQuest (Firm)
Series statement
River Publishers Series in Communications Ser
Label
Evolution of Air Interface Towards 5G : Radio Access Technology and Performance Analysis
Instantiates
Publication
Note
5.1.6.2 Spectral efficiency of a femtocell network
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Introduction
  • Radio and Propagation Channel Models
  • 4.1.2.
  • Large-Scale Channel Model
  • 4.1.3.
  • MIMO Spatial Channel Model
  • 4.2.
  • Millimeter-Wave Communications
  • 4.2.1.
  • Challenges
  • 4.2.2.
  • 2.2.
  • State-of-the-Art Technology and Standards
  • 4.2.3.
  • Millimeter-Wave Applications for 5G
  • 4.3.
  • Rician K-Factor for Indoor mmWave Channels
  • 4.3.1.
  • Rician K-Factor Calculation for the Multicluster With Directivity Saleh-Valenzuela Model
  • 4.3.2.
  • Rician K-Factor Calculation for the Modified SV Model for mmW
  • 4.3.3.
  • OFDM
  • Modified SV Model for mmW
  • 4.3.4.
  • IEEE 802.11ad Model
  • 4.3.5.
  • Variation of K-Factor With Respect to Link Orientations
  • 4.3.6.
  • Impact of Rician K-Factor on System BER
  • 4.4.
  • mmWave MIMO in Channels with Realistic Spatial Correlation
  • 4.4.1.
  • 2.2.1.
  • Analytical Modeling of the Composite PAS
  • 4.4.2.
  • Performance Analysis
  • 4.4.3.
  • Hybrid Beamforming
  • 5.1.
  • Femtocell-/Small Cell-based Heterogeneous Networks
  • 5.1.1.
  • Femtocells/Small cells
  • 5.1.2.
  • Channel
  • Deployment Modes
  • 5.1.3.
  • Access Mechanisms
  • 5.1.4.
  • Issues Related to Femtocell/Small cell Deployment
  • 5.1.5.
  • Control Mechanisms for Femto Base Stations
  • 5.1.6.
  • Area Spectral Efficiency Analysis of Co-Channel Heterogeneous network
  • 5.1.6.1.
  • 2.2.2.
  • Spectral efficiency of a macrocell network
  • 5.1.6.2.
  • Spectral efficiency of a femtocell network
  • 5.1.6.3.
  • Area spectral efficiency
  • 5.1.6.4.
  • Optimal femtocell radio parameters
  • 5.1.6.5.
  • Results and discussion
  • 5.1.6.6.
  • Receiver
  • ASE with QoS constraints
  • 5.2.
  • OFDMA-based Cellular Network and Underlaying D2Ds
  • 5.2.1.
  • D2D Deployment Modes
  • 5.2.2.
  • System Level Performance Evaluation
  • 5.2.3.
  • Stochastic Modeling and Analysis of D2D Enabled Heterogeneous Cellular Network
  • 5.2.3.1.
  • 2.3.
  • Distribution of eNBs
  • 5.2.3.2.
  • Distribution of UEs (D2D Tx and Rx) and femtos
  • 5.2.4.
  • Signal-to-interference Ratio with Activity
  • 5.2.5.
  • Sub-band Coverage Probability Under PPP
  • 5.2.6.
  • Coverage Probability Under GPP
  • 5.2.7.
  • 5G Numerology
  • User Association under Cellular Tier Being GPP and D2D and Femto Being PPP Distributed
  • 5.2.8.
  • Fractional Load and Link Throughput
  • 5.2.9.
  • Results and Their Analysis
  • 5.2.10.
  • Coverage Probability Analysis
  • 5.2.11.
  • Throughput Analysis
  • 6.1.
  • 2.3.1.
  • Multi-objective Optimization in for Energy Savings
  • 6.2.
  • System Model
  • 6.2.1.
  • SINR
  • 6.2.2.
  • Traffic
  • 6.3.
  • Network Coverage, Overlap, ASE, and APC
  • 6.3.1.
  • Machine generated contents note:
  • Genesis
  • Network Coverage
  • 6.3.2.
  • Overlap Probability
  • 6.3.3.
  • Area Spectral Efficiency
  • 6.3.4.
  • Blocking Probability
  • 6.3.5.
  • Area Power Consumption
  • 6.4.
  • 2.3.2.
  • Multi-objective Optimization Framework
  • 6.4.1.
  • Genetic Algorithm-based Multi-objective Optimization
  • 6.4.2.
  • Set of Active Sectors
  • 6.4.3.
  • RAN Parameters
  • 6.5.
  • Results
  • 7.1.
  • Implementation
  • System Model of the Dynamic Priority Scheduler
  • 7.1.1.
  • Modeling the Physical Layer (PHY) Layer
  • 7.1.2.
  • Modeling the Medium Access Control (MAC) Layer: DP Scheduler
  • 7.2.
  • Queueing Analysis
  • 7.2.1.
  • Arrival Statistics
  • 7.2.2.
  • 2.4.
  • Queue Service Process: DP Scheduler
  • 7.2.2.1.
  • Scheduler dynamics
  • 7.2.2.2.
  • Packet departure process
  • 7.2.3.
  • Synthesis of the Markov Chain
  • 7.3.
  • Evaluation of Performance Metrics
  • 7.3.1.
  • Windowed OFDM
  • Packet Drop Probability
  • 7.3.2.
  • Throughput
  • 7.3.3.
  • Average Delay
  • 7.4.
  • Results
  • 7.4.1.
  • Evaluation Framework
  • 7.4.2.
  • 2.4.1.
  • Verification of Performance Analysis
  • 7.5.
  • Call Admission Control Using the DP Scheduler Framework
  • 7.5.1.
  • Working of the CAC and Role of the Scheduler
  • 7.5.1.1.
  • Simulation setup
  • 7.5.1.2.
  • Results on CAC for the DP scheduler framework
  • 7.6.
  • Transmitter
  • Summary
  • 2.4.2.
  • Receiver
  • 2.5.
  • 1.1.
  • Filtered OFDM
  • 2.5.1.
  • Transmitter
  • 2.5.2.
  • Receiver Processing
  • 2.6.
  • GFDM
  • 2.6.1.
  • Transmitter
  • 2.6.2.
  • Introduction
  • Receiver
  • 2.7.
  • Precoded GFDM
  • 2.7.1.
  • Block IDFT Precoded GFDM
  • 2.7.1.1.
  • Joint processing
  • 2.7.1.2.
  • BIDFT-N precoding
  • 2.7.1.3.
  • 1.2.
  • Two-stage processing
  • 2.7.1.4.
  • BIDFT-N precoding
  • 2.7.1.5.
  • BIDFT-M precoding
  • 2.7.2.
  • DFT Precoded GFDM
  • 2.7.3.
  • SVD Precoded GFDM
  • 2.8.
  • Development of LTE toward 5G
  • FBMC
  • 2.8.1.
  • Cosine Modulated Tone
  • 2.8.2.
  • Filter Characteristics
  • 2.8.3.
  • Simplified Filter Characteristics
  • 2.8.4.
  • MMSE Equalizer for FBMC
  • 2.9.
  • 1.3.
  • UFMC
  • 2.9.1.
  • Structure of UFMC Transceiver
  • 2.9.2.
  • System Model for UFMC
  • 2.9.3.
  • Output of the Receiver for the UFMC Transceiver Block Diagram
  • 2.10.
  • Performance Comparison
  • 3.1.
  • Technologies Drivers for 5G
  • OFDM-based Non-orthogonal Multiple Access
  • 3.1.1.
  • Algorithms for User Multiplexing and Power Allocation
  • 3.1.2.
  • Performance Analysis
  • 3.2.
  • Coordinated OFDM - NOMA
  • 3.2.1.
  • System Model
  • 3.2.2.
  • 2.1.
  • Solution Methodology and Proposed Algorithms
  • 3.3.
  • User Selection and Optimal Power Allocation in NOMA
  • 3.3.1.
  • System Model
  • 3.3.2.
  • Performance Analysis
  • 4.1.
  • Millimeter-Wave Channel Modeling
  • 4.1.1.
Control code
MSTDDA5493974
Dimensions
unknown
Extent
1 online resource ( 298 pages.):
Form of item
online
Isbn
9788793609808
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Reproduction note
Electronic reproduction.
Specific material designation
remote
Label
Evolution of Air Interface Towards 5G : Radio Access Technology and Performance Analysis
Publication
Note
5.1.6.2 Spectral efficiency of a femtocell network
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Introduction
  • Radio and Propagation Channel Models
  • 4.1.2.
  • Large-Scale Channel Model
  • 4.1.3.
  • MIMO Spatial Channel Model
  • 4.2.
  • Millimeter-Wave Communications
  • 4.2.1.
  • Challenges
  • 4.2.2.
  • 2.2.
  • State-of-the-Art Technology and Standards
  • 4.2.3.
  • Millimeter-Wave Applications for 5G
  • 4.3.
  • Rician K-Factor for Indoor mmWave Channels
  • 4.3.1.
  • Rician K-Factor Calculation for the Multicluster With Directivity Saleh-Valenzuela Model
  • 4.3.2.
  • Rician K-Factor Calculation for the Modified SV Model for mmW
  • 4.3.3.
  • OFDM
  • Modified SV Model for mmW
  • 4.3.4.
  • IEEE 802.11ad Model
  • 4.3.5.
  • Variation of K-Factor With Respect to Link Orientations
  • 4.3.6.
  • Impact of Rician K-Factor on System BER
  • 4.4.
  • mmWave MIMO in Channels with Realistic Spatial Correlation
  • 4.4.1.
  • 2.2.1.
  • Analytical Modeling of the Composite PAS
  • 4.4.2.
  • Performance Analysis
  • 4.4.3.
  • Hybrid Beamforming
  • 5.1.
  • Femtocell-/Small Cell-based Heterogeneous Networks
  • 5.1.1.
  • Femtocells/Small cells
  • 5.1.2.
  • Channel
  • Deployment Modes
  • 5.1.3.
  • Access Mechanisms
  • 5.1.4.
  • Issues Related to Femtocell/Small cell Deployment
  • 5.1.5.
  • Control Mechanisms for Femto Base Stations
  • 5.1.6.
  • Area Spectral Efficiency Analysis of Co-Channel Heterogeneous network
  • 5.1.6.1.
  • 2.2.2.
  • Spectral efficiency of a macrocell network
  • 5.1.6.2.
  • Spectral efficiency of a femtocell network
  • 5.1.6.3.
  • Area spectral efficiency
  • 5.1.6.4.
  • Optimal femtocell radio parameters
  • 5.1.6.5.
  • Results and discussion
  • 5.1.6.6.
  • Receiver
  • ASE with QoS constraints
  • 5.2.
  • OFDMA-based Cellular Network and Underlaying D2Ds
  • 5.2.1.
  • D2D Deployment Modes
  • 5.2.2.
  • System Level Performance Evaluation
  • 5.2.3.
  • Stochastic Modeling and Analysis of D2D Enabled Heterogeneous Cellular Network
  • 5.2.3.1.
  • 2.3.
  • Distribution of eNBs
  • 5.2.3.2.
  • Distribution of UEs (D2D Tx and Rx) and femtos
  • 5.2.4.
  • Signal-to-interference Ratio with Activity
  • 5.2.5.
  • Sub-band Coverage Probability Under PPP
  • 5.2.6.
  • Coverage Probability Under GPP
  • 5.2.7.
  • 5G Numerology
  • User Association under Cellular Tier Being GPP and D2D and Femto Being PPP Distributed
  • 5.2.8.
  • Fractional Load and Link Throughput
  • 5.2.9.
  • Results and Their Analysis
  • 5.2.10.
  • Coverage Probability Analysis
  • 5.2.11.
  • Throughput Analysis
  • 6.1.
  • 2.3.1.
  • Multi-objective Optimization in for Energy Savings
  • 6.2.
  • System Model
  • 6.2.1.
  • SINR
  • 6.2.2.
  • Traffic
  • 6.3.
  • Network Coverage, Overlap, ASE, and APC
  • 6.3.1.
  • Machine generated contents note:
  • Genesis
  • Network Coverage
  • 6.3.2.
  • Overlap Probability
  • 6.3.3.
  • Area Spectral Efficiency
  • 6.3.4.
  • Blocking Probability
  • 6.3.5.
  • Area Power Consumption
  • 6.4.
  • 2.3.2.
  • Multi-objective Optimization Framework
  • 6.4.1.
  • Genetic Algorithm-based Multi-objective Optimization
  • 6.4.2.
  • Set of Active Sectors
  • 6.4.3.
  • RAN Parameters
  • 6.5.
  • Results
  • 7.1.
  • Implementation
  • System Model of the Dynamic Priority Scheduler
  • 7.1.1.
  • Modeling the Physical Layer (PHY) Layer
  • 7.1.2.
  • Modeling the Medium Access Control (MAC) Layer: DP Scheduler
  • 7.2.
  • Queueing Analysis
  • 7.2.1.
  • Arrival Statistics
  • 7.2.2.
  • 2.4.
  • Queue Service Process: DP Scheduler
  • 7.2.2.1.
  • Scheduler dynamics
  • 7.2.2.2.
  • Packet departure process
  • 7.2.3.
  • Synthesis of the Markov Chain
  • 7.3.
  • Evaluation of Performance Metrics
  • 7.3.1.
  • Windowed OFDM
  • Packet Drop Probability
  • 7.3.2.
  • Throughput
  • 7.3.3.
  • Average Delay
  • 7.4.
  • Results
  • 7.4.1.
  • Evaluation Framework
  • 7.4.2.
  • 2.4.1.
  • Verification of Performance Analysis
  • 7.5.
  • Call Admission Control Using the DP Scheduler Framework
  • 7.5.1.
  • Working of the CAC and Role of the Scheduler
  • 7.5.1.1.
  • Simulation setup
  • 7.5.1.2.
  • Results on CAC for the DP scheduler framework
  • 7.6.
  • Transmitter
  • Summary
  • 2.4.2.
  • Receiver
  • 2.5.
  • 1.1.
  • Filtered OFDM
  • 2.5.1.
  • Transmitter
  • 2.5.2.
  • Receiver Processing
  • 2.6.
  • GFDM
  • 2.6.1.
  • Transmitter
  • 2.6.2.
  • Introduction
  • Receiver
  • 2.7.
  • Precoded GFDM
  • 2.7.1.
  • Block IDFT Precoded GFDM
  • 2.7.1.1.
  • Joint processing
  • 2.7.1.2.
  • BIDFT-N precoding
  • 2.7.1.3.
  • 1.2.
  • Two-stage processing
  • 2.7.1.4.
  • BIDFT-N precoding
  • 2.7.1.5.
  • BIDFT-M precoding
  • 2.7.2.
  • DFT Precoded GFDM
  • 2.7.3.
  • SVD Precoded GFDM
  • 2.8.
  • Development of LTE toward 5G
  • FBMC
  • 2.8.1.
  • Cosine Modulated Tone
  • 2.8.2.
  • Filter Characteristics
  • 2.8.3.
  • Simplified Filter Characteristics
  • 2.8.4.
  • MMSE Equalizer for FBMC
  • 2.9.
  • 1.3.
  • UFMC
  • 2.9.1.
  • Structure of UFMC Transceiver
  • 2.9.2.
  • System Model for UFMC
  • 2.9.3.
  • Output of the Receiver for the UFMC Transceiver Block Diagram
  • 2.10.
  • Performance Comparison
  • 3.1.
  • Technologies Drivers for 5G
  • OFDM-based Non-orthogonal Multiple Access
  • 3.1.1.
  • Algorithms for User Multiplexing and Power Allocation
  • 3.1.2.
  • Performance Analysis
  • 3.2.
  • Coordinated OFDM - NOMA
  • 3.2.1.
  • System Model
  • 3.2.2.
  • 2.1.
  • Solution Methodology and Proposed Algorithms
  • 3.3.
  • User Selection and Optimal Power Allocation in NOMA
  • 3.3.1.
  • System Model
  • 3.3.2.
  • Performance Analysis
  • 4.1.
  • Millimeter-Wave Channel Modeling
  • 4.1.1.
Control code
MSTDDA5493974
Dimensions
unknown
Extent
1 online resource ( 298 pages.):
Form of item
online
Isbn
9788793609808
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Reproduction note
Electronic reproduction.
Specific material designation
remote

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