# 3 GPP Evolution from 5G to 6G: A 10-Year Retrospective
## 7 3 GPP Release 20: Evolution to 6G
Seminal surveys and tutorials have articulated key use-case families--ranging from holographic communications and digital twins to pervasive sensing and AI-driven networks--and have identified spectrum, waveform, and architecture innovations needed to meet IMT-2030 targets [95; 96; 97; 98; 99; 100; 101; 102; 103; 104; 105; 106]. To meet 6G requirements with higher data rates, lower latencies, massive connectivity, and ultra-high reliability, 3 GPP may explore several advanced technologies for enhancing the radio interface in Release-20 6G studies:  
* **Advanced modulation schemes**: High-order QAM constellations increasingly suffer from hardware non-linearities that erode their spectral-efficiency gains. Alternative signal-shaping modulation techniques offer promising paths forward [107]. 6G studies should explore low peak-to-average-power-ratio schemes that deliver strong performance while remaining cost-effective. Moreover, because residual phase noise persists despite receiver compensation, developing modulation methods with robust phase-noise suppression is essential;
* **Advanced coding schemes**: 6G studies should explore further development of Polar, LDPC, and other coding schemes (e.g., space-frequency coding) that span a wide range of block lengths and code rates [108; 109]. Crucial goals include minimizing decodingcomplexity, maximizing parallelism, and reducing latency. Codes must combine high rate, strong error correction, and low error floor to reduce HARQ retransmissions. Additionally, novel coding schemes integrated with iterative retransmission/feedback mechanisms are needed for short-packet IoT, balancing block length, latency, and reliability;
* **Advanced waveforms**: OFDM has emerged as the dominant multicarrier waveform for mobile communications systems. While OFDM's practical advantages and ecosystem maturity argue for its continued baseline role, its limitations under non-ideal conditions motivate ongoing research into both modified multicarrier systems and new waveforms. Emerging techniques such as orthogonal time-frequency space (OTFS) exploit Doppler diversity by operating in the delay-Doppler domain, providing robustness in high-mobility environments [110];
* **Multiple access**: OFDMA has served 4G LTE and 5G, and will continue to be the baseline multiple access scheme in 6G. Nonetheless, it may fall short in scaling to scenarios with massive low-duty-cycle devices. 6G studies may explore non-orthogonal multiple access (NOMA), which overlays users in the same time-frequency resources, relying on advanced detection and decoding to resolve collisions [111]. It is also of interest to study rate-splitting multiple access (RSMA) that uses message splitting and linearly precoded multi-antenna transmission [112];
* **Advanced antenna technologies**: 6G studies should explore extreme MIMO that extends massive MIMO by deploying orders-of-magnitude larger arrays [113]. As array dimensions grow, physical effects, such as wavefront curvature, beam squint, and near-field shadowing, break plane-wave assumptions, requiring fresh beam-management and channel-estimation algorithms. Another promising direction is distributed MIMO (or cell-free MIMO) that coordinates many transmission/reception points for coherent joint processing, thereby reducing interference and eliminating cell boundaries [114];
* **AI-native air interface**: 6G studies will continue to explore the roles of AI/ML in wireless communications. AI/ML in 6G is expected to be embedded from inception across all layers, forming a core design paradigm rather than an optimization add-on. In the near term, targeted AI/ML models will not only incrementally optimize features but will also unlock new air-interface capabilities [115]. In the long term, semantic communications, where meanings, not bits, are transmitted, is an interesting direction for further exploration [116];
* **Full duplex**: 6G studies should explore in-band full-duplex transmission, which could theoretically double capacity compared to conventional FDD and TDD [117].