# Enabling Intelligent 6G Communications: A Scalable Deep Learning Framework for MIMO Detection
## 5 MIMONet: A DL-Based MIMO Detector
### MIMONet: Training and Testing
#### 5.2.3 Testing
[PERSON] focused on software implementation and the preparation of figures to support the research findings. [PERSON] led the overall project conceptualisation, designed the methodology, supervision of software development, supervised the research process, and was involved in thorough revision, editing, data analysis, and validation to ensure the integrity and quality of the final manuscript. All authors have read and agreed to the published version of the manuscript. [PERSON] PhD funding is supported by the Department of Economy (DfE) at the School of Engineering, Ulster University, Belfast, BT15 1 ED, United Kingdom. Data Availability Statement: Data will be made available on request. Conflicts of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Figure 10: Computational complexity: Comparative analysis of MIMONet against the benchmark MIMO detector. ## References

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