Page 33 - Kaleidoscope Academic Conference Proceedings 2024

APPENDIX

3GPP 3rd Generation Partnership Project

pi/2-BPSK pi/2-Binary Phase Shift Keying

ACLR Adjacent Channel Leakage Ratio
ARS Additional Reference Signals

BLER Block Error Rate

CCDF Complementary Cumulative Distribution
Function
Figure 14 – UL Link Budget for indoor UEs (RMa)
CP Cyclic Prefix

CS Cyclic Suffix

5. CONCLUSION AND FUTURE WORK CSI Channel State Information

This paper presents a comprehensive exploration of key DFT-s- Discrete Fourie Transform-spread-
candidate technologies for 6G systems, with a particular OFDM Orthogonal Frequenc Division
focus on Orthogonal Time Frequency Division Multiplexing Multiplexing
(OTFDM) and Structural MIMO (S-MIMO). OTFDM
addresses the limitations of traditional OFDM, offering DFT Discrete Fourier Transform
enhanced power efficiency, low PAPR, and improved
simultaneous transmission of reference signals and data. S- DL Downlink
MIMO, on the other hand, provides significant
advancements in network capacity through its innovative EVM Error Vector Magnitude
antenna arrangements, enabling comprehensive 360-degree
coverage. The significant improvements in the achievable FFT Fast Fourier Transform
capacity and coverage with both these technologies positions
them as critical enablers for meeting the stringent IFFT Inverse FFT
requirements of IMT-2030.
IMT International Mobile Telecommunications
Future directions:
ISI Inter Symbol interference
In OTFDM, the inherent support for multi-user MIMO (MU- ITU WP International Telecommunications Union
MIMO) is relatively constrained. However, there is potential 5D Working Party 5D
to optimize OTFDM, particularly in uplink transmissions, to
enhance its spatial multiplexing capability. By improving the MIMO Multiple Input Multiple Output
MU-MIMO capacity, OTFDM can become more efficient
and scalable in high-density network scenarios. In the case OTFDM Orthogonal Time Frequency Multiplexing
of S-MIMO, the large number of antennas leads to a
significant increase in computational complexity for PA Power Amplifier
baseband signal processing, which in turn raises hardware
costs and maintenance requirements. To mitigate this, low- PAPR Peak to Average Power Ratio
complexity baseband algorithms can be developed to
efficiently estimate channel characteristics and compute PRB Physical Resource Block
precoding weights.
QAM Quadrature Amplitude Modulation

QPSK Quadrature Phase Shift Keying

RS Reference Signals

S-MIMO Structural-Multiple Input Multiple Output

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