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Content for
TR 38.866
Word version: 16.1.0
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2
References
3
Definitions, symbols and abbreviations
4
Introduction on atmospheric ducting phenomenon and remote interference in TDD network
5
Deployment Scenarios for RIM
6
Study on framework and mechanisms for RIM
7
Evaluation of reference signals
8
Conclusions
$
Change History
2
References
p. 5
3
Definitions, symbols and abbreviations
p. 6
3.1
Definitions
p. 6
3.2
Symbols
p. 6
3.3
Abbreviations
p. 6
4
Introduction on atmospheric ducting phenomenon and remote interference in TDD network
p. 6
4.1
Atmospheric ducting phenomenon
p. 6
4.2
Characteristics of the remote interference
p. 7
4.2.1
Characteristics of the IoT increase caused by remote interference
p. 7
4.2.2
The distance that the remote interference impacts
p. 8
5
Deployment Scenarios for RIM
p. 8
6
Study on framework and mechanisms for RIM
p. 9
6.1
RIM framework in current TD-LTE systems
p. 9
6.2
Potential frameworks and workflows for NR RIM
p. 10
6.3
Potential Reference signal designs for NR RIM
p. 13
6.3.1
General requirement
p. 13
6.3.2
RS sequence type and structure
p. 14
6.3.3
RS resource pattern
p. 14
6.4
Potential mechanisms for improving network robustness
p. 15
6.4.1
Solutions by network implementation
p. 15
6.4.1.1
Time-domain based solutions
p. 15
6.4.1.2
Frequency-domain based solutions
p. 15
6.4.1.3
Spatial-domain based solutions
p. 16
6.4.1.4
Power-domain based solutions
p. 16
6.4.1.5
Random access procedure enhancement
p. 16
6.4.2
Solutions with specification impact
p. 17
6.4.2.1
Time-domain based solutions
p. 17
6.4.2.2
Frequency-domain based solutions
p. 17
6.4.2.3
Spatial-domain based solutions
p. 17
6.4.2.4
Power-domain based solutions
p. 17
6.5
Backhaul-based coordination mechanisms for remote interference mitigation
p. 17
6.5.1
gNB set configuration
p. 17
6.5.2
Intra-set coordination in RIM
p. 18
6.5.3
Inter-set coordination for RIM
p. 18
6.5.3.1
Solutions for inter-set coordination
p. 18
6.5.3.2
Conclusions for inter-set coordination
p. 19
7
Evaluation of reference signals
p. 19
7.1
Evaluation methodology
p. 19
7.1.1
Evaluation cases
p. 19
7.1.2
Detection algorithms
p. 21
7.2
Performance metric
p. 23
7.2.1
False alarm probability
p. 23
7.2.2
Detection probability
p. 23
7.2.3
Error detection probability
p. 23
7.2.4
Minimum SNR
p. 23
7.3
Evaluation results and observations
p. 24
7.3.1
Case 1: Single sequence and single RS
p. 24
7.3.2
Case 2-1: Single sequence and multiple RSs
p. 25
7.3.3
Case 2-2A: Multiple sequences and single RS
p. 26
7.3.4
Case 2-2B: Multiple sequences and multiple RSs
p. 27
7.4
Conclusions based on evaluations
p. 29
8
Conclusions
p. 30
$
Change History
p. 31