Abstract
The upcoming 6G networks require digital signal processing (DSP) systems which need to adapt their operations for unanticipated changes in communication channel conditions and system environmental factors because the demand for high-speed communication demands both quick response times and dependable service. The fixed processing chains of traditional DSP systems which engineers built for 5G networks together with their requirement for specific hardware usage create limits that prevent effective operation under changing environmental conditions. The paper presents ADaPT-6 (Adaptive DSP for Progressive Transceivers in 6G) as a solution to these obstacles through its entire software-based AI-powered digital signal processing system which enables real-time transceiver operation changes through intelligent learning. The ADaPT-6 system operates through two fundamental components which use FlexiTune Modulation Adaptation to enable systems to select their best modulation methods based on current channel conditions while the Signal State Evolution Engine predicts system behavior to modify system operations of filtering and equalization and synchronization. The framework achieves better spectral efficiency through its implementation of adaptive modulation together with its ability to predict signal states which improves system reliability and operational efficiency. The research shows through extensive testing in practical 6G fronthauling situations that both traditional fixed DSP systems and DSP systems with limited adaptation capabilities face performance difficulties across multiple performance metrics including bit error rate and statistical reliability and throughput and energy efficiency and latency and outage probability. The evaluation process used SNR values ranging from 0 to 20 dB while measuring EVM in percentage terms and ACLR in decibels and average throughput in Mbps and latency in milliseconds and energy efficiency in bits per Joule. Quantitative evaluation demonstrates that ADaPT-6 achieves significant performance improvements over conventional DSP frameworks, including a ~ 20.8% increase in throughput (57.37 Mbps vs. 47.47 Mbps), ~ 23.7% reduction in latency (20.52 ms vs. 26.88 ms), and ~ 44.5% improvement in energy efficiency (0.678 vs. 0.469 bits/Joule). Additionally, the framework consistently achieves lower BER and EVM across the entire SNR range (0-20 dB), confirming its robustness under dynamic channel conditions. The results confirm that ADaPT-6 operates as an effective digital signal processing solution which works on any hardware platform and can be implemented at any scale. The system functions as the best solution for future AI-native 6G transceiver systems.