READ ME File For 'Sixty Years of Coherent Versus Non-coherent Tradeoffs and the Road from 5G to Wireless Futures' IEEE Access (Accepted on 2 Dec 2019) Authors: Chao Xu, Naoki Ishikawa, Rakshith Rajashekar, Shinya Sugiura, Robert G. Maunder, Zhaocheng Wang, Lie-Liang Yang and Lajos Hanzo C. Xu, R. Rajashekar, R. G. Maunder, L. L. Yang and L. Hanzo are with the School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK (e-mail: \{cx1g08,rmr1u14,lh\}@soton.ac.uk). N. Ishikawa is with the Graduate School of Information Sciences, Hiroshima City University, Ohzuka-higashi 731-3194, Japan (e-mail: naoki@ishikawa.cc). S. Sugiura is with the Institute of Industrial Science, University of Tokyo, Meguro-ku, Tokyo 153-8505, Japan (e-mail: sugiura@ieee.org). Z. Wang is with Tsinghua University, Beijing, China (e-mail: zcwang@tsinghua.edu.cn). Acknowledgement: L. Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EP/N004558/1, EP034284/1, COALESCE, of the Royal Society's Global Challenges Research Fund Grant, of the Royal Society Grant IF170002 as well as of the European Research Council's Advanced Fellow Grant QuantCom. The work of N. Ishikawa was supported in part by the Japan Society for the Promotion of Science KAKENHI under Grant 17H07036. The work of S. Sugiura was supported in part by Japan Society for the Promotion of Science (JSPS) KAKENHI under Grant Numbers 16KK0120, 17H03259, and in part by Japan Science and Technology Agency (JST) PRESTO under Grant Number JPMJPR1933. Abstract: Sixty years of coherent versus non-coherent tradeoff as well as the twenty years of coherent versus non-coherent tradeoff in Multiple-Input Multiple-Output (MIMO) systems are surveyed. Furthermore, the advantages of adaptivity are discussed. More explicitly, in order to support the diverse communication requirements of different applications in a unified platform, the 5G New Radio (NR) offers unprecendented adaptivity, abeit at the cost of a substantial amount of signalling overhead that consumes both power and the valuable spectral resources. Striking a beneficial coherent versus non-coherent tradeoff is capable of reducing the pilot overheads of channel estimation, whilst relying on low-complexity detectors, especially in high-mobility scenarios. Furthermore, since energy-efficiency is of salient importance both in the operational and future networks, following the powerful Index Modulation (IM) pholosophy, we conceive a holistic adaptive pholosophy striking the most appropriate coherent/non-coherent, single-/multiple-antenna and diversity/multiplexing tradeoffs, where the number of RF chains, the Peak-to-Average Power Ratio (PAPR) of signal transmission and the maximum amount of interference tolerated by signal detection are all taken into account. We demonstrate that this intelligent tripple-fold adaptivity offers significant benefits in next-generation applications of mmWave and Terahertz solutions, in space-air-ground integrated networks, in full-duplex techniques and in other sophisticated channel coding assisted system designs, where powerful machine learning algorithms are expected to make autonomous decisions concerning the best mode of operation with minimal human intervention. NOTE: .fig files are edited by Xfig in Linus systems; .dat files are read by .gle file in the same folder by gle. Fig.~1: Schematic_6G.eps Fig.~2: Structure_Paper.eps Fig.~3: Schematic_5G.eps Fig.~4: Spectrum_LTE.eps Spectrum_NR_FR1.eps Spectrum_NR_FR2.eps Fig.~5: Numerology_SCS.eps Numerology_OFDM_Duration.eps Numerology_RB_BW.eps Numerology_Slot.eps Fig.~6: Numerology_CP_Duration.eps Numerology_CP_Overhead.eps Fig.~7: Schematic_CH.eps Schematic_RS.eps Fig.~8: Schematic_RACH.eps Schematic_SRS.eps Schematic_CSI_RS.eps Fig.~9: Channel_Estimation.eps Fig.~10: Schematic_DPSK_MSDD.eps Schematic_DPSK_DFDD.eps Fig.~11: EXAMPLE_MSDSD_DQPSK.eps EXAMPLE_TRELLIS_DQPSK.eps Fig.~12: Link_MIMO_Noncoherent.eps Fig.~13: Constellation_Diagram_16ADPSK_Data.eps Schematic_DAPSK.eps Fig.~14: MIMO_Schemes_Tradeoffs.eps Fig.~15: Schematic_SM_Transmitter_Chapter1.eps Schematic_STSK_Transmitter_Chapter1.eps Fig.~16: Schematic_RF_Tradeoff.eps Fig.~17: Example_DG2_PSK.eps Fig.~18: Constellation_Diagram_DAOSTBC_M_2_T_2_L1_8_L2_8_Data.eps Constellation_Diagram_DAOSTBC_M_2_T_2_L1_8_L2_8_Transmit.eps Fig.~19: Schematic_TAST_DSTSK_TAST_Layers.eps Fig.~20: Det_Prod_M_2_tall.eps Det_Prod_M_4_tall.eps Fig.~21: Complexity_CDD_M_2_N_1_BER_4_EbN0.eps Complexity_CDD_M_4_N_1_BER_4_EbN0.eps Fig.~22: Hard_CDD_M_2_R_20_Rx_4.eps Hard_CDD_M_2_R_50_Rx_4.eps Hard_CDD_M_4_R_200_Rx_4.eps Hard_CDD_M_4_R_500_Rx_4.eps Fig.~23: nonsquare-dstbc.eps Fig.~24: DCMC_Capacity_QPSK_DQPSK_Ricean_K_0_fd_001_tall.eps DCMC_Capacity_QPSK_DQPSK_Ricean_K_0_fd_03_tall.eps Fig.~25: DCMC_Capacity_DPSK_DSM_DSTBC_Ricean_K_0_fd_03_tall.eps DCMC_Capacity_DQPSK_DSM_DSTBC_Ricean_K_0_fd_03_tall.eps Fig.~26: Power_Efficiency_QPSK_DQPSK_fd.eps Power_Efficiency_QPSK_DQPSK_K.eps Fig.~27: Power_Efficiency_DQPSK_DSTM_Rc.eps Power_Efficiency_DQPSK_DSTM_Rm.eps Fig.~28: Coverage_Example.eps Coverage_Gain_Percentage_Example.eps Fig.~29: Schematic_Space_Air_Ground.eps Fig.~30: Schematic_Golden.eps Schematic_FC_GSTSK.eps Fig.~31: Schematic_TDD_FDD_IBFD_MDD.eps Fig.~32: Schematic_CC_MIMO.eps Fig.~33: Trajectory_IRCC_URC_DQPSK_Ricean_K_0_fd_03_MSDSD_4_NOL_3.eps Trajectory_DQPSK_Ricean_K_0_fd_03_MSDSD_4_NOL_3_EbN01.eps Trajectory_DQPSK_Ricean_K_0_fd_03_MSDSD_4_NOL_3_EbN02.eps Fig.~34: BER_IRCC_TC_RSC_DPSK_PSAM_fd_001.eps BER_IRCC_TC_RSC_DPSK_PSAM_fd_03.eps Fig.~35: LLR_DQPSK_Ricean_K_0_fd_001_MSDSD_4_NOL_3.eps LLR_DQPSK_Ricean_K_0_fd_03_MSDSD_4_NOL_3.eps Fig.~36: Schematic_ML_Categories_Trends.eps Schematic_ML_Categories_Examples.eps Fig.~37: Schematic_Objectives_Methods.eps Fig.~38: Schematic_Optimization_Pareto.eps Schematic_Optimization_Separate.eps Fig.~39: Hard_Metric_div_prod_div_sum.eps Hard_Metric_div_prod_div_sum_ave.eps