READ ME File For 'Dataset' Dataset DOI: 10.5258/SOTON/D2392 ReadMe Author: Bohan Li, University of Southampton This dataset supports the publication: AUTHORS: Bohan Li THESIS TITLE: Optimization of Multicarrier-Division Duplex Wireless Systems This dataset contains: Figure 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10, 2.11, 2.12, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, 4.3, 4.4, 4.5, 4.7, 4.8, 4.9, 4.11, 5.6, 5.7, 5.8, 5.9, 5.10, 5.11, 5.12, 5.13, 5.14, 6.4, 6.5, 6.7 and 6.8 of the aforementioned thesis. Each folder is named according to its content, where the curves of each figure are stored in mat files. To regenerate the results, please use the Matlab. The figures are as follows: - Figure 2.2: Contains the dataset of Figure 2.2. SI reduction versus number of iterations. - Figure 2.3: Contains the dataset of Figure 2.3. SIC versus number of iterations performance with respect to different angles between the transmit and receive antenna arrays, as well as to different Rician factors of SI channel. - Figure 2.4: Contains the dataset of Figure 2.4. SIC performance comparison of the proposed methods with Option 1 and Option 2 and the method presented in [108]. - Figure 2.5: Contains the dataset of Figure 2.5. Average sum-rate of the MDD MIMO systems with different beamforming/initialization schemes. - Figure 2.6: Contains the dataset of Figure 2.6. Average sum-rate versus the number of iterations of the analog precoder operated during the SIC process. - Figure 2.7: Contains the dataset of Figure 2.7. Average sum-rate versus BS's transmit power for the MDD MIMO systems employing different numbers of DL transmit antennas and RF chains. - Figure 2.8: Contains the dataset of Figure 2.8. Average sum-rate versus BS's transmit power for the MDD MIMO systems employing different numbers of DL/UL subcarriers. - Figure 2.9: Contains the dataset of Figure 2.9. Average sum-rate versus BS's transmit power for the MDD MIMO systems employing different numbers of DL/UL users. - Figure 2.10: Contains the dataset of Figure 2.10. Average sum-rate performance of MDD MIMO systems experiencing the frequency-selective fading channels with different taps. - Figure 2.11: Contains the dataset of Figure 2.11. Mean-square error (MSE) performance of channel estimation in MDD MIMO systems. - Figure 2.12: Contains the dataset of Figure 2.12. Average sum-rate versus SNR performance of MDD MIMO systems with channel knowledge provided by different methods. - Figure 3.3: Contains the dataset of Figure 3.3. Sum rate achieved by the MDD-, FDD- and TDD-based MU-SISO systems. - Figure 3.4: Contains the dataset of Figure 3.4. Performance comparison of the MUG algorithm and the proposed algorithm with different fairness constraints。 - Figure 3.5: Contains the dataset of Figure 3.5. Fairness comparison of MUG algorithm and proposed RA algorithm. - Figure 3.6: Contains the dataset of Figure 3.6. Sum rate versus transmit power of BS when different hybrid precoders are employed. - Figure 3.7: Contains the dataset of Figure 3.7. Sum rate versus the number of RF chains at BS transmitter, when different hybrid precoder designs are employed. - Figure 3.8: Contains the dataset of Figure 3.8. Rates of individual DL MSs achieved for one channel realization, when different hybrid precoders are employed. - Figure 3.9: Contains the dataset of Figure 3.9. SIC performance with respect to different number of antenna elements at receiver. - Figure 3.10: Contains the dataset of Figure 3.10. Uplink performance with ideal SIC and the SIC provided by our proposed algorithm. - Figure 4.3: Contains the dataset of Figure 4.3. Sum rate versus OFDM symbol index of the TDD systems with the different assumptions about channel acquisition and relative velocity. - Figure 4.4: Contains the dataset of Figure 4.4. Performance comparison of the MDD and TDD systems, when Type I frame structure and 7-th order WP are employed.. - Figure 4.5: Contains the dataset of Figure 4.5. Performance comparison of the MDD systems with Type I frame structure and different orders of WPs. - Figure 4.7: Contains the dataset of Figure 4.7. Average sum rate versus relative velocity, when the Type I frame structure is used. - Figure 4.8: Contains the dataset of Figure 4.8. Performance comparison of the MDD and TDD systems, when Type II frame structure is applied. - Figure 4.9: Contains the dataset of Figure 4.9. Average sum rate versus the relative velocity, when the Type II frame structure is used. - Figure 4.11: Contains the dataset of Figure 4.11. Sum rate comparison of MDD, IBFD and TDD with respect to OFDM symbol index, when Type I frame structure and the relative velocity of 150 km/h are assumed. - Figure 5.6: Contains the dataset of Figure 5.6. Power- and subcarrier-allocation results of AP 11 to MS 3 achieved by Algorithm 1. - Figure 5.7: Contains the dataset of Figure 5.7. Cumulative distribution of per-MS SE in different CF schemes. - Figure 5.8: Contains the dataset of Figure 5.8. Cumulative distribution versus per-MS SE in MDD- and IBFD-CF schemes with different SIC. - Figure 5.9: Contains the dataset of Figure 5.9. Cumulative distribution versus per-MS SE in MDD- and IBFD-CF schemes with different cell size. - Figure 5.10: Contains the dataset of Figure 5.10. SE convergence behavior of Algorithm 1 in MDD-CF scheme. - Figure 5.11: Contains the dataset of Figure 5.11. Average per-MS SE of one radio frame versus the relative speed. - Figure 5.12: Contains the dataset of Figure 5.12. Cumulative distribution versus per-MS SE in Phase I. - Figure 5.13: Contains the dataset of Figure 5.13. Cumulative distribution versus per-MS SE in the case of combined Phase I and Phase II. - Figure 5.14: Contains the dataset of Figure 5.14. SE convergence behavior of Algorithm 3 in MDD-CF scheme. - Figure 6.4: Contains the dataset of Figure 6.4. Cumulative distribution of SE, when the MDD-CF network has L = 24 APs and D = 6 MSs. - Figure 6.5: Contains the dataset of Figure 6.5. SE performance gap between QT-SCA and CF-HGNN, when the MDD-CF network uses L = 24 APs to support D = 6 MSs. - Figure 6.7: Contains the dataset of Figure 6.7. SE convergence behavior and operation time of different methods, where L = 24,D = 6. - Figure 6.8: Contains the dataset of Figure 6.8. Comparison of operation time between the QT-SCA and CF-HGNN methods. Date of data collection: 09, 2018 ~ 03, 2022 Information about geographic location of data collection: University of Southampton Licence: CC BY Related projects: The financial support of the Engineering and Physical Sciences Research Council (EPSRC) under the project EP/P034284/1, the Innovate UK under the Knowledge Transfer Partnership project KTP011036 and the China Scholarship Council (CSC). Date that the file was created: 09, 2022