Radar and Communication Spectrum Sharing

Cover
Contents
About the editor
Preface
Part I The big picture
1 The case for spectrum access
1.1 Introduction
1.2 Why spectrum access is so vital
1.3 Tolerating versus cooperating
1.3.1 Achieving greater tolerance
1.3.2 Living in harmony
1.4 Scoping the spectrum-sharing problem space
1.4.1 Spectral perspective
1.4.2 Power perspective
1.4.3 Spatial perspective
1.4.4 Temporal perspective
1.4.5 Doppler perspective
1.4.6 Modulation and coding perspective
1.4.7 Polarization perspective
1.4.8 Separability
1.5 Conclusions
Acknowledgments
References
2 The spectrum crunch – a radar perspective
2.1 Introduction
2.2 The radar spectrum environment
2.3 Signal spectra
2.3.1 Spectra of practical emissions
2.3.2 Radar emissions
2.3.3 Radar transmitters
2.4 Spectrum allocation
2.4.1 Competition for spectrum
2.4.2 Spectrum regulation
2.5 Radar interference to other users
2.5.1 Radar interference to other radars
2.5.2 Radar interference to other systems
2.5.3 WiMAX and LTE communication systems
2.6 Interference to radar by other users
2.7 Technology developments
2.7.1 Passive bistatic radar
2.7.2 Waveform diversity
2.7.3 Bio-inspired approaches
2.7.4 Cognitive radar
2.8 Conclusions
Acknowledgements
References
3 Spectrum sharing between radar and small cells
3.1 Radar systems—the incumbents
3.1.1 Classification of radar systems
3.1.1.1 By operating principle
3.1.1.2 By application
3.1.1.3 By waveform
3.1.1.4 By beam and scanning pattern
3.1.2 Radar environmental factors
3.2 Current regulation on radar spectrum sharing
3.2.1 5150–5925 MHz band
3.2.1.1 Radio environment
3.2.1.2 Policy history and context
3.2.1.3 Incumbent protection
3.2.2 3550–3700 MHz band in the United States
3.2.2.1 Radio environment
3.2.2.2 Policy history and context
3.2.2.3 Spectrum access system
3.2.2.4 Incumbent protection
3.3 Spatial sharing techniques
3.3.1 Geolocation database (GL-DB)
3.3.2 Spectrum sensing and DFS
3.3.2.1 Beaconing
3.3.3 Cooperative spectrum sensing
3.3.4 Radio environment map (REM)
3.4 Beyond traditional sharing schemes
3.4.1 Temporal sharing
3.4.2 Cognitive beamforming
3.4.2.1 Offline beamforming
3.4.3 Coexistence through cooperation and codesign
3.4.4 Open challenges
3.5 Secondary radio access technologies
3.5.1 LTE in unlicensed spectrum
3.5.2 Licensed LTE
3.5.3 WLAN
3.6 Conclusions
3.7 Looking ahead
References
4 Radar spectrum sharing: history, lessons learned, and ways forward
4.1 Introduction
4.2 Early radar development
4.2.1 The reason behind higher radar frequencies
4.2.2 Radar spectrum band development
4.2.3 Radars need quiet spectrum to work well
4.2.4 Why frequency bands allocated to radars require large bandwidths
4.2.5 Why radars have tended to have their own spectrum allocations
4.3 Regulation of radar spectrum in the United States and worldwide
4.4 The advent of radar band sharing
4.5 Radar 101: essential knowledge for spectrum sharing
4.5.1 Specification of what the radar must do
4.5.2 Radar receiver inherent internal thermal noise and other losses
4.5.3 The radar antenna
4.5.4 Radar wave propagation to and from a target
4.5.5 Peak power the radar must transmit
4.5.6 Radar pulse repetition rate
4.5.7 Radar pulse echo integration for effective detection
4.5.8 Radar beam-scanning interval
4.6 Radar receiver susceptibility to interference in spectrum-sharing scenarios
4.7 Detecting our hypothetical radar for DFS purposes
4.7.1 The DFS spectrum-sharing concept
4.7.2 Uniqueness of DFS for real-world spectrum sharing
4.7.3 Timeline of international (ITU-R) and U. S. national development of DFS
4.7.4 DFS introductory efforts, 1996
4.7.5 Initial FCC R& O and MO& O policy statements, 1997–1998
4.7.6 WRC-03 and Recommendation M. 1652, Circa 2003
4.7.7 Determination of protection criteria, late 1990s through mid-2000s
4.7.8 First DFS implementation steps in the United States, 2003–2004
4.7.9 DFS certification testbed development, 2005–2006
4.7.10 DFS certification requirements developed, 2005–2006
4.7.11 DFS compliance testbed constructed and early testing, 2005–2006
4.7.12 Initial DFS deployment experience, 2006–2009
4.7.13 Ongoing DFS deployment experience, 2010–present
4.8 Technical assumptions of DFS
4.8.1 Assumption: radars can be detected while U-NII message traffic is occurring
4.8.2 Assumption: detection of radar signals by APs protects radars from all network transmissions
4.8.3 Assumption: radar-detection thresholds are adequate to protect radars from harmful interference
4.8.4 Assumption: radar waveform testing is sufficiently robust
4.8.5 Assumption: firmware updates installed in DFS units after initial certification will not cause DFS to be impaired or disabled
4.8.6 Assumption: DFS-equipped U-NIIs will be properly installed and operated
4.8.7 Ongoing need for enforcement in DFS bands
4.9 More lessons learned
4.10 Challenges for manufacturers and vendors
4.10.1 Challenges to the communications community in understanding radar systems
4.10.2 Difficulty of detecting general, not specific, radar waveforms
4.10.3 Lack of industry testbeds for DFS
4.10.4 Development of the NTIA testbed and its use by industry and FCC
4.11 Challenges for development of DFS test-and-certification protocols
4.11.1 Advantages: working from a blank slate
4.11.2 Disadvantages: areas of developmental doubt and uncertainty
4.12 Interference cases after initial DFS deployment
4.12.1 Identification of interfering DFS-equipped devices at San Juan
4.13 Ongoing DFS spectrum sharing maintenance
4.13.1 Continuing monitoring of DFS devices
4.13.2 Consideration of more complex future radar waveforms
4.14 Looking forward to future spectrum sharing
References
5 Spectrum use, congestion, issues, and research areas at radio-frequencies
5.1 Introduction
5.2 Impacts of EM spectral interactions between communication and radar systems
5.2.1 Impacts of radars on communication systems
5.2.2 Impacts of communication systems on radars
5.3 Radar spectrum-mitigation efforts
5.3.1 Selected efforts since 1998
5.3.2 Current efforts
5.4 Suggested research areas for radar–communications spectral harmony
5.4.1 Adjacent-band interference mitigation for radar emissions
5.4.1.1 Adaptive RF filter technology
5.4.1.2 Transmitter topology
5.4.1.3 Linearizing radar transmitters
5.4.2 Radar waveforms
5.4.3 Innovative antenna elements and arrays
5.4.4 Innovative radar receivers
5.4.4.1 Radar receiver design using digital beamforming
5.4.4.2 Receiver interference rejection
5.4.5 Propagation
5.4.6 Adaptive and cognitive emission control
5.4.7 Radar–communications co-design
5.4.7.1 Code-transmitted signal at RF
5.5 Some essential EM theory for communications and radar
5.5.1 Physically realizable waveforms
5.5.2 Notions of far field and antenna pattern for communication cell sizes
5.5.3 Maxwellian-based use of capacity
5.5.4 Antenna pattern and placement for communications
5.5.5 Essential antenna properties for system design
5.6 Closing observations
5.6.1 Radar–communications spectral harmony
References
Part II Systems engineering perspectives
6 Spectrally efficient communications and radar
6.1 Introduction
6.2 Communication spectral efficiency
6.2.1 Basic linear modulation schemes
6.2.2 Detection in additive white Gaussian noise
6.2.3 The waveform model for linear modulations
6.2.4 Orthogonal frequency division multiplexing
6.2.5 Continuous phase modulation
6.2.6 Channel capacity and the fundamental limits on spectrum efficiency
6.3 Radar spectral efficiency
6.3.1 Radar spectral content
6.3.2 Designing for radar spectral containment: holistic system perspective
6.3.3 Some practical aspects of sharing radar spectrum
6.3.3.1 Coherent rejection of shared-spectrum interference
6.3.3.2 Radar spectrum nulling on transmit
6.4 Conclusions and looking ahead
References
7 Passive bistatic radar for spectrum sharing
7.1 Introduction
7.2 Bistatic radar principles
7.2.1 Bistatic radar geometry
7.2.2 Bistatic radar equation
7.2.3 Target signatures
7.2.4 The ambiguity function in bistatic radar
7.3 Passive bistatic radar illuminators
7.3.1 Power density incident upon a target
7.3.2 Coverage
7.3.3 Waveforms
7.3.4 Orthogonal frequency division multiplexing
7.3.5 Long-term evolution
7.4 Passive bistatic radar techniques
7.4.1 Direct signal suppression
7.4.2 Processing gain and performance prediction
7.4.3 Target detection, localisation and tracking
7.5 Passive bistatic radar and the spectrum problem
7.5.1 PBR in air traffic management
7.6 Summary and conclusions
Acknowledgements
References
8 Symbiosis for communications, broadcasting and sensor systems in the white space TV band
8.1 Introduction
8.2 The white space standard and its evolution
8.2.1 A historical perspective
8.2.2 White space overview
8.2.3 Key WRAN radiator parameters
8.3 Networks of sensors and a taxonomy
8.3.1 Early networks of sensors: radar
8.3.2 A proposed taxonomy for networks of sensors
8.3.2.1 Commensal systems
8.3.2.2 Mutualistic systems
8.3.2.3 Parasitic systems
8.3.3 Parameter extraction with sensor networks
8.3.3.1 Monostatic sensing
8.3.3.2 Bistatic sensing
8.3.3.3 Multistatic sensing
8.3.3.4 Doppler-only sensing
8.3.3.5 Multilateration
8.3.4 Applications of EM sensor networks
8.3.4.1 Aircraft detection and tracking
8.3.4.2 Vehicle detection and tracking
8.3.4.3 Maritime/waterway traffic detection and tracking
8.3.4.4 Human detection and tracking
8.3.4.5 Earth observation applications
8.4 Commensal implementation of a WS sensor
8.4.1 FM band commensal aircraft sensing
8.5 Mutualistic implementation of a WS sensor
8.6 Time and frequency alignment
8.6.1 Necessity of time/frequency alignment
8.6.2 Hard wired timing
8.6.3 SONET and other network technologies
8.6.4 GPS disciplined oscillators
8.6.5 White Rabbit
8.6.5.1 Performance of White Rabbit in radar
8.7 Conclusions and looking ahead
8.7.1 Summary
8.7.2 Looking ahead
References
9 Fusion of radar sensing, data communications, and GPS interoperability via software-defined OFDM architecture
9.1 Overview of OFDM in radar and communications
9.2 Design of an UWB software-defined system based on OFDM
9.2.1 General considerations for an UWB SDRS design
9.2.2 Transmit power considerations for indoor UWB OFDM SDRS
9.3 Dual use of system bandwidth and transmit power via OFDM radar/communication signals
9.3.1 Radar-embedded communications and radar/communication signals
9.3.2 Example: OOK OFDM signal performance in radar and communications
9.3.2.1 AF and PSL of UWB OOK-like OFDM radar signals
9.3.2.2 BER of UWB OOK-like OFDM communication signals
9.4 Simultaneous sensing and covert, ad-hoc asynchronous communications with OFDM
9.4.1 Randomization of radar/communication signals for communications
9.4.2 Randomization of radar/communication signals using stochastic sequences
9.4.3 Cross-range compression for SAR with randomized OFDM signals
9.5 In-band co-existence of UWB OFDM radar signals and navigation satellite signals
9.5.1 System and simulation setup for UWB radar and GPS receiver co-design
9.5.2 GPS software receiver model
9.5.3 UWB OFDM and GPS coexistence modeling results
9.6 Looking ahead: conclusions and perspectives
References
10 Adaptive RF multi-interference suppression for wideband radar/communication receivers
10.1 Introduction
10.1.1 Wideband receiver architectures for radar and communication systems
10.1.2 Narrowband interference in wideband receivers
10.2 Case study: impact of narrowband interference on a wideband radar receiver
10.2.1 Coherent FMCW radar
10.2.2 Impact and mitigation of CW interference on FMCW radar
10.2.3 Integration of tunable notch filters in the receiver front-end
10.3 Spectrally agile RF/microwave multi-notch filters
10.3.1 Filter design for agile interference rejection
10.3.2 Filter design based on a coupled-resonator arrangement
10.3.3 Filter design based on hybrid acoustic-wave/lumped-element resonators
10.4 Looking ahead: future trends
10.5 Conclusions
References
11 Transmitter architectures for radar/communication spectral coexistence
11.1 Spectral, propagation, and regulatory environment for transmitters
11.2 Transmitter architectures: past, present, and future
11.2.1 Current transmitter design philosophy: radar vs. communication
11.2.2 Future transmitter architectures
11.2.2.1 Software-defined radio
11.2.2.2 Adaptive/Cognitive/Distributed transmitters
11.3 Transmitter components
11.3.1 Microwave tubes
11.3.1.1 Magnetron
11.3.1.2 Cross-field amplifier
11.3.1.3 Traveling wave tube
11.3.1.4 Klystron
11.3.1.5 Multiple beam klystron
11.3.2 Pulse modulators
11.3.3 Solid-state transmitter architectures
11.3.3.1 Solid-state devices
11.3.3.2 Combining solid-state power amplifiers
11.3.4 Microwave power module
11.3.5 Classes of power amplifiers
11.4 Radar transmitters and the future of radar
11.4.1 Legacy versus new radar developments
11.4.2 Transmit/Receive modules
11.4.3 Power amplifier linearization
11.5 Transmitter emission measurements
11.6 Future research
References
Further reading
12 Adaptively reconfigurable radar: real-time optimization of the transmitter amplifier and waveforms
12.1 Why an adaptive and reconfigurable radar transmitter?
12.1.1 Traditional radar spectrum regulations
12.1.2 Dynamic spectrum access
12.2 Algorithms for circuit optimization
12.2.1 Optimization of load impedance to maximize PAE under spectral constraints
12.2.2 The Smith tube
12.2.3 Simultaneous optimization of load impedance and input power using the power Smith tube
12.2.4 Simultaneous optimization of load impedance and bias voltage using the bias Smith tube
12.2.5 Optimization of PAE under multiple constraints based on output power and ACPR
12.3 Radar waveform optimization with spectral mask compliance
12.3.1 Woodward's ambiguity function
12.3.2 Alternating projections optimization
12.4 Adjusting the radar spectral mask based on surrounding wireless devices
12.4.1 Calculation of a dynamic radar spectral mask
12.4.2 Radar waveform optimization using a dynamic spectral mask
12.4.3 Joint transmitter and waveform optimization
12.5 Looking ahead
12.5.1 Creating a regulatory environment favoring adaptive radar transmission
12.5.2 Cooperation between radar and communication systems
12.5.3 Development of high-power-tunable components
12.6 Conclusions
Acknowledgments
References
Part III Addressing interference
13 Radar/Wi-Fi spectrum sharing: evaluation of radar protection regions
13.1 Background
13.2 Search radar: noise limited operation
13.2.1 Noise-limited radar operation: design equations
13.3 Cumulative interference to radar from randomly deployedWi-Fi APs
13.3.1 Average and variance of aggregate interference (μI, σI2 ): Campbell's theorem
13.3.1.1 Homogeneous Poisson point process (PPP)
13.3.1.2 Nonhomogeneous Poisson process
13.4 Simulation results for omni antenna gain pattern
13.4.1 Campbell's theorem verification
13.4.2 Optimizing the protection region for homogenous PPP
13.4.2.1 Numerical brute-force approach for omniprotection region
13.4.2.2 Iterative Monte-Carlo approach to determine dopt(θ)
13.4.2.3 Gaussian assumption for distribution of Iaggr
13.4.2.4 Comparison of the Gaussian assumption with Monte-Carlo simulation
13.4.3 Poisson cluster process
13.4.3.1 Campbell's theorem verification
13.4.4 Inhomogeneous PPP
13.5 Simulation results for typical radar gain pattern
13.5.1 Homogeneous PPP
13.5.2 Inhomogeneous PPP
13.6 Looking ahead: future work
Acknowledgment
Appendix A
References
14 Spectrum sharing via interference tolerant transform domain waveform design
14.1 Introduction
14.2 Foundations and framework
14.2.1 Transform domain communication system
14.2.1.1 Multiple access in TDCS
14.2.1.2 TDCS receiver
14.2.2 SMSE framework
14.3 SMSE-based overlay multicarrier communication waveforms
14.3.1 OFDM via SMSE
14.3.2 TDCS via SMSE
14.4 SMSE-based multicarrier radar waveforms
14.5 Coexistence of radar and communications
14.5.1 Scenario 1: Communication coexistence with narrowband emissions
14.5.2 Scenario 2: Radar coexistence with narrowband emissions
14.5.3 Scenario 3: Radar/Communication coexistence with narrowband emissions
14.6 Looking ahead
References
15 Radar bandwidth optimization for interference mitigation
15.1 Introduction
15.2 Spectrum sensing, multi-objective optimization for RFI avoidance
15.3 Computational cost and RF tuning considerations
15.3.1 Computational cost of WSMO
15.3.2 Considerations for RF tuning
15.4 Fast weighted sum multi-objective optimization for RFI avoidance
15.4.1 Generation of synthetic data for fWSMO training
15.4.2 Interference threshold and merge bandwidth parameter training for fWSMO
15.5 Evaluation ofWSMO and fWSMO
15.6 Conclusions, applications of RFI avoidance, and future work
References
16 Compressed sensing and interference occupancy monitoring for spectrum sharing in spectrally dense environments
16.1 Introduction
16.2 Cognitive spectrum sensing and sharing
16.2.1 Cognitive cycle
16.2.2 System architecture
16.3 Channel characterization
16.4 Compressed spectrum sensing
16.5 Spectrum sharing
16.6 Conclusions and looking ahead
References
17 Radar waveform design for spectral coexistence
17.1 Introduction
17.1.1 Waveform design for interference mitigation
17.1.2 The role of practical constraints
17.1.3 Performance prediction (empirical vs. analytic)
17.2 Representing interference and noise for waveform design algorithm development
17.2.1 Auto-regressive parametric models
17.2.2 Marčenko–Pastur generalized model
17.2.3 Empirical models
17.3 Modelling SINR loss for spectral coexistence (radar centric)
17.3.1 Cumulative modulus
17.3.1.1 Numerical results
17.3.1.2 Application to waveform design
17.3.2 Integrated sidelobe constraints
17.3.2.1 Expected ISL performance model
17.3.2.2 Expected SINR performance model
17.3.3 Simulation results and comparison to measured data
17.4 Alternative metrics for spectrally crowded engagements
17.4.1 Maximizing information
17.4.2 Mutual information for cognitive radar
17.4.3 Example with primary users
17.5 Summary
17.6 Looking ahead
References
18 Space–time transmit nulling for RF spectrum interoperability
18.1 Introduction
18.2 Overview of reiterative uniform weight optimization (RUWO) algorithm
18.2.1 General formulation
18.2.2 Spatial nulling
18.2.3 Frequency nulling
18.2.4 Space–frequency nulling
18.2.5 Deterministic and adaptive spatial interference covariance
18.3 Experimental MIMO radar test bed
18.4 Experimental demonstration of transmit nulling
18.4.1 Base-band loop-back demonstration
18.4.2 Open-air demonstration of space–frequency transmit nulling
18.5 Incorporation of RUWO within a wideband emission design problem
18.5.1 Wideband array analysis
18.5.1.1 Wideband beamforming
18.5.1.2 Wideband definition and the narrowband assumption
18.5.1.3 Physical considerations and the invisible space
18.5.2 RUWO within spectral shaping optimization
18.5.3 Wideband MIMO radar emission optimization with space–frequency nulling
18.5.3.1 Parameter initialization
18.5.3.2 Emission design via alternating projections
18.5.4 Emission optimization analysis
18.6 Summary
18.7 Looking ahead
Acknowledgments
References
Part IV Radar/communication co-design
19 Communication and radar co-design
19.1 Introduction
19.2 Background
19.2.1 Coexistence
19.2.2 Co-design of joint radar–communications
19.3 Performance metrics
19.3.1 Communication metrics
19.3.2 Radar estimation information rate
19.3.3 Detection performance
19.3.4 Practical limitations
19.4 Topologies
19.4.1 Multiaccess sensing and communications
19.4.2 Multiaccess receiver and relay
19.5 Operating-point optimization
19.6 Conclusions
19.7 Looking ahead
Acknowledgments
References
20 Real-time radar/communication spectrum sharing based on information exchange
20.1 Introduction, background, and the "Three A's"of radar–comms spectrum sharing
20.1.1 Avoid & mitigate interference
20.1.2 Accept interference
20.1.3 Amalgamate waveforms
20.2 Business cases for spectrum stakeholders
20.3 Maximizing the joint capacity of a radar–communication network
20.4 Theory of JDO SSPARC
20.5 JDO SSPARC channel estimation
20.6 High-fidelity JDO SSPARC design example
20.7 A new approach to radar/communication spectrum sharing
20.8 Architecture of the spectrum sharing system
20.8.1 Slow-time control loop via sharing policy composition
20.8.2 Fast-time control loop via sharing policy enforcement
20.9 Performance of the RCS3
20.9.1 Simulation results for radar/communication spectrum sharing
20.9.2 Temporally coordinated slow-frequency hopping between radar and communications via RAC
20.9.3 Temporally coordinated transmit muting for military MANETs via CAR
20.10 Summary
20.11 Looking ahead
Acknowledgments and disclaimer
References
21 Embedding communication symbols in radar clutter on an intrapulse basis
21.1 Introduction
21.1.1 Practical considerations
21.2 RCEC symbol design
21.2.1 Signal model
21.2.2 Direct-sequence spread-spectrum
21.2.3 Eigenvectors as waveforms
21.2.4 Dominant projection
21.2.5 Shaped dominant projection
21.2.6 Shaped waterfilling
21.3 Receiver design
21.3.1 Matched filter
21.3.2 Maximum likelihood (ML) decorrelating filter (DF)
21.3.3 Diagonally loaded decorrelating filter
21.3.4 Two-stage Neyman–Pearson detector
21.4 Performance evaluation
21.4.1 Spectral content
21.4.2 Processing gain
21.4.3 Probability of detection and symbol error rate
21.5 Conclusions
21.6 Looking ahead
References
22 Dual-function radar–communications using sidelobe control
22.1 Introduction
22.2 System configuration and signal model
22.3 Transmit beampattern synthesis for dual-function systems
22.3.1 Time-modulated array-based synthesis
22.3.2 Convex optimization based design
22.3.3 Beampattern synthesis with minimum disturbance to the radar
22.3.4 Beampattern synthesis with phase control
22.4 Transmit signaling strategies for embedding information
22.4.1 Sidelobe AM-based communications
22.4.2 Multi-waveform sidelobe ASK-based communications
22.4.3 Multi-waveform PSK-based communications
22.4.4 Embedding information into MIMO radar emissions
22.5 Performance analysis
22.5.1 Impact of dual-functionality on radar performance
22.5.2 Bit error rate performance analysis
22.5.3 Simulation results
22.6 Looking ahead: discussion and future directions
References
23 Embedding communications into radar emissions by transmit waveform diversity
23.1 Coding waveform diversity
23.1.1 PCFM-based radar-embedded communication (REC)
23.1.1.1 System model
23.1.1.2 Spectral content
23.1.2 Receive filter design to address RSM for coding diversity REC
23.1.2.1 Common filter response
23.1.2.2 Matched filter (MF) formulation
23.1.2.3 Mismatched filter (MMF) formulation
23.1.2.4 Cascaded filters formulation
23.1.3 Characterization of RSM
23.2 Spatial waveform diversity
23.2.1 Far-field radiated emission design
23.2.1.1 Signal model
23.2.1.2 Optimality of waveforms
23.2.1.3 Utilization of the null space and the total directed power
23.2.2 Realization of emission constraints using error reduction algorithm
23.2.2.1 FFRED implementation
23.2.3 Simulated characterization of FFRED emissions
23.3 Spectral waveform diversity
23.3.1 Designing an FM noise waveform with spectral notches
23.3.2 Embedding communications into radar spectral notches
23.3.3 Performance assessment of THoRaCs
23.3.3.1 Performance evaluation
23.3.4 Commensal radar with spectrally shaped OFDM
23.4 Conclusions
23.5 Looking ahead
References
Index
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