研究目的
To study the impact of intercore crosstalk (ICXT) in weakly-coupled multicore fibers (MCFs) on the transmission performance of 10 Gbps CPRI signals in 5G network fronthauls using numerical simulation.
研究成果
FEC-supported CPRI signals show higher tolerance to ICXT due to a higher target BER. Increasing MCF skew improves ICXT tolerance by about 1 dB for a 1 dB power penalty. However, crosstalk levels causing 1 dB penalty lead to high system unavailability, requiring about 10 dB lower crosstalk for acceptable outage probability. Outage probability is a critical metric, with higher skew MCFs being more resilient.
研究不足
The study is based on numerical simulation, not experimental validation. Assumptions include infinite extinction ratio for transmitters, neglect of fan-in/fan-out device crosstalk, and consideration of only single interfering core in some analyses. The model may not capture all real-world variations in MCF behavior.
1：Experimental Design and Method Selection:
Numerical simulation using Monte Carlo (MC) simulation combined with a semi-analytical method for noise evaluation to assess ICXT impact on performance metrics such as eye-pattern, bit error rate (BER), power penalty, and outage probability. The discrete changes model is used for ICXT modeling.
2：Sample Selection and Data Sources:
Simulated CPRI signals at bit rates of 9.8304 Gbps (without FEC) and 10.1376 Gbps (with FEC), with parameters including fiber length, dispersion, skew, and crosstalk levels.
3：8304 Gbps (without FEC) and 1376 Gbps (with FEC), with parameters including fiber length, dispersion, skew, and crosstalk levels.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Not applicable as it is a simulation study; no physical equipment used.
4：Experimental Procedures and Operational Workflow:
Generation of OOK signals, propagation through MCF cores with ICXT modeling, photodetection with PIN photodiode, electrical filtering, and BER calculation using MC iterations with different MCF realizations.
5：Data Analysis Methods:
Semi-analytical BER estimation using Q-function, optimization of decision thresholds, and statistical analysis of outage probability.
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