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Welcome to the Learning-based-Power-Allocation-Strategy-in-Small-Cell-Network wiki! This repository is for the UCD EEC289Q 2018 Spring Quarter final project. The content of our project includes:

• data pre-processing
• feature selection
• learning algorithms
• Gibbs based optimization
• conclusion

Data Pre-processing

In this part, the data sets we get are some log files from Huawei Inst. We formalized the data sets with the target be the throughput of a base station and the feature be pilot power, data power, load, number of users, and its neighbor base station featres. A typical data frame is as below: | Time | Cell ID | Throughput |Load | Power | User| Neighbor| | ------------- |:-------------:| -----:| | col 3 is | right-aligned | $1600 | | col 2 is | centered | $12 | | zebra stripes | are neat | $1 |

Feature Selection

Learning throughput of the base station

Optimization