Low Electromagnetic Emission Wireless Network Technologies: 5G and beyond

Cover
Contents
About the editors
Preface
Part I. EMF evaluation and characterisation
1 EMF exposure definition, metrics, effects and regulations
1.1 Scope
1.2 Factors contributing to EM exposure in mobile communications
1.2.1 Communication network topology
1.2.1.1 Cell deployment
1.2.1.2 Distributed antenna topology
1.2.1.3 Heterogeneous networks
1.2.2 Location of the user relative to the BS
1.2.3 Duration of exposure
1.3 EM radiation and RF communication spectrum range
1.4 EM radiation metrics
1.4.1 Near field and SAR
1.4.1.1 Whole-body averaged SAR
1.4.1.2 Organ-specific averaged SAR
1.4.1.3 Peak-spatial averaged SAR
1.4.2 Far field and power density
1.5 EM exposure index
1.6 Perception and physiological impact of EMF exposure in mobile communication
1.6.1 Risk assessment and public perception of exposure
1.6.2 Physiological impact
1.6.2.1 Exposure and brain tumour
1.6.2.2 Other exposure effects on different age groups
1.6.2.3 Exposure effects of mmWave transmissions
1.7 EM exposure guidelines and limits
1.7.1 EM exposure limits
1.7.2 Precautionary principle
1.7.3 EM radiation exclusion zones
1.8 Conclusion
References
2 Electromagnetic field (EMF) monitoring tools
List of acronyms and symbols
2.1 Introduction
2.1.1 EMF exposure metrics
2.1.2 Typical EMF measurement sensor
2.2 State of the art for EMF monitoring tools
2.2.1 SAR measurement systems
2.2.2 Power density/E-field measurement systems
2.2.2.1 Wide-band exposimeters
2.2.2.2 Frequency-selective exposimeters
2.2.3 Simulation tools for EMF monitoring
2.2.4 Other measurement tools
2.3 EMF monitoring of a smart city
2.4 Conclusions and perspectives
References
3 Large-scale EMF characterization considering real network deployments
3.1 Test bed description
3.1.1 Low-complexity dosimeter
3.1.2 SmartSantander
3.1.3 Dosimeter integration
3.2 Scenario characterization
3.2.1 Deployment dimensioning
3.2.2 Network usage
3.2.3 Uplink–downlink correlation
3.3 Calibration of the measurements
3.3.1 Monaxial to isotropic
3.3.2 Location extrapolation factor
3.3.3 Indoor–outdoor extrapolation factor
3.4 Exposure calculation methodology
3.5 Exposure analysis
3.5.1 Frequency selectivity
3.5.2 Geographical and temporal variation
3.5.3 EI evaluation
3.6 Conclusion
References
4 EMF exposure in heterogeneous networks environments
4.1 Introduction
4.2 EMF exposure evaluation and assessment
4.2.1 Dosimetric/epidemiologic use of metrics
4.2.2 Methods for EMF exposure assessment
4.3 On-body measurements
4.3.1 Estimation of EMF from personal and fixed-point exposimeters
4.3.2 Simulation results
4.3.3 EMF exposure in BANs
4.4 EMF exposure in heterogeneous networks
4.4.1 Exposure assessment in heterogeneous networks accounting for UL and DL
4.4.2 Exposure model
4.4.3 Simulation scenario
4.4.4 Simulation results
4.5 Conclusions
References
5 Architecture of public mobile networks and its impact on EMF exposure
5.1 Introduction
5.2 Network architecture layers: macro, micro, pico, femto
5.2.1 Wi-Fi coverage
5.2.2 Relation to EMF
5.3 Measurements of incident EMF in DL
5.4 Measurements of Tx power in UL
5.5 Case studies: macro/micro, macro/femto
5.5.1 The addition of the microcell and indoor DAS system
5.5.2 Femtocell vs. macrocell
5.6 Impact of specific user services to EMF exposure
5.7 Conclusion
References
Part II. EMF reduction techniques
6 EMF emission-aware resource allocation for uplink OFDM systems
6.1 Introduction
6.2 System model
6.3 EMF emission reduction schemes
6.3.1 Offline EMF emission reduction scheme
6.3.1.1 Subcarrier allocation
6.3.1.2 Power allocation
6.3.2 Online EMF emission reduction scheme
6.3.2.1 Subcarrier allocation
6.3.2.2 Power allocation
6.3.2.3 Transmit power and target data constraints
6.3.3 Complexity analysis
6.4 Numerical results
6.5 Conclusion
References
7 Multicell uplink scheduling for EMF emission minimization in OFDMA systems
7.1 Introduction
7.2 System model
7.3 MC EMF emission-aware scheduling scheme
7.3.1 Subcarrier allocation
7.3.2 Power allocation
7.3.2.1 Power allocation algorithm 1
7.3.2.2 Power allocation algorithm 2
7.3.3 Scheduler algorithm
7.4 Complexity analysis
7.5 Numerical results and discussions
7.6 Conclusion
References
8 EMF: RF device end of things – low-exposure user terminal radio design concepts
8.1 Historical context: design of low SAR antennas for voice mobile
8.2 Emergence of ubiquitous computing and the changed shape of wireless device usage
8.3 Low-exposure antenna technologies in advanced mobile terminals
8.3.1 Context-aware multiple antennas
8.3.2 Proximity slave device for mobile terminals
8.4 Societal changes in mobile terminal usage
8.5 Low-exposure transmission techniques for advanced mobile terminals
8.6 Conclusions and evaluation of candidate low-exposure technologies for the mobile terminal
References
9 Millimetre-wave flexible wearable antenna design and challenges for 5G and beyond
9.1 Millimetre-wave spectrum for 5G networks
9.2 High-frequency spectrum challenges for 5G
9.3 Antennas for 5G cellular networks
9.4 5G antennas interaction with human body
9.5 Flexible antennas for 5G wearable applications
9.6 Fabrication processes for flexible antennas
9.6.1 Laser milling and PCB prototyping
9.6.2 Inkjet printing
9.6.3 Photolithography
9.6.4 Screen printing
9.7 Design and implementation of flexible 5G antenna
9.7.1 Antenna design and fabrication
9.7.2 Numerical and experimental analysis
9.7.2.1 Radiation pattern
9.7.2.2 Impedance bandwidth
9.7.2.3 Realized gain
9.8 Conclusion
References
10 Reducing EMF emissions in ultra-reliable low-latency communications with HARQ
10.1 Hybrid automatic repeat request
10.2 Reducing EMF emission
10.2.1 Health concerns from EMF exposure
10.2.2 Reducing EMF radiation in URLLC applications
10.2.2.1 Early feedback
10.2.2.2 Code design
10.2.2.3 Optimizing the number of transmission attempts
10.3 Conclusion
References
11 Reducing EMF via energy-efficient inter-frequency small cell discovery
11.1 Introduction
11.2 Energy-efficient ISCD mechanisms
11.2.1 Relaxed inter-frequency measurement gap
11.2.2 UE speed-based inter-frequency measurement gap triggering
11.2.3 Use of RSS or RSRP radio fingerprint for ISCD
11.3 Inter-frequency small cell discovery
11.3.1 ISCD periodicity and small cell offloading opportunity
11.3.2 Approximation of the percentage of time a typical UE missed small cell offloading opportunity
11.4 Energy efficiency evaluation
11.4.1 Probability of UE association to a tier
11.4.1.1 Idealistic probability of UE association to a tier
11.4.1.2 Realistic UE association
11.4.1.3 UE power consumption model
11.4.1.4 Average UE transmit power in a tier
11.4.1.5 Average ergodic rate of a typical UE in a tier
11.4.2 Ideal average energy efficiency
11.4.3 Realistic average energy efficiency
11.5 Optimal ISCD periodicity
11.5.1 Optimal ISCD based on average energy consumption
11.5.2 Optimal ISCD based on UE's average energy efficiency
11.6 Conclusion
References
12 Conclusion and future perspectives
Index
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