http://hdl.handle.net/123456789/10340 2026-07-16T22:03:29Z http://hdl.handle.net/123456789/19033 2-D Seismic Data Interpretation of Qadirpur Area, Pakistan Ammad Ali Tariq Aim of the study is to interpret 2D-Seismic Reflection time section of the Qadirpur Area (Sindh Province) Pakistan. This seismic section is a Pre-stacked time migrated section and was provided by the Department of Earth Sciences, Bahria University Islamabad and this line bears the title 985-QPR-03 It is about 40 Kms in length and is oriented in SW-NE direction. OGDC acquired data in October 1998 and processed it in January 1999. The velocity information is in the form of RMS. DIX interval and DIX average at different times is given, and is provided at selected S.P. RMS velocity varies from 1500 m/s to 5000 m/s Interpreted part of this line from S.P. # 460 to S.P # 720, with CDPs from 920 to 1440 Length of this part of seismic section is 13 Kms. For interpretation of this part of Seismic section, four reflectors and 2 faults are marked on the basis of prominent reflections from subsurface horizons due to changes in lithology and diffractions. Using the RMS velocity given in the velocity panels on seismic section for selected shot points, calculate the time on constant velocity interval of 100m/sec Then using these calculated time and velocity values prepare the Iso-velocity graph and Iso-time graph (for mean line method) by taking constant velocity and time respectively, In Mean line Method of velocity estimation, a velocity vs time graph is prepared. From this graph, a mean average velocity is determined. From Seismic Section, arrival times (two ways) of each marked reflector are determined, Using these arrival times, Time Section is prepared. Also using these arrival times, calculate the average velocity for these times on mean line graph and then the depth of each reflector has been calculated using s(vt)/2 and is represented in Depth Section. Depth Section provides a reliable picture of reflectors and structures present in the subsurface of the area. Well correlation is also done, which satisfy the calculated depths, so horizons have been marked Interpretation of the Project Area shows that, extensional regime and calm environment prevails in the area. Reflectors are almost flat-lying, whereas Horst and Graben structures have been found. Supervised by Mr. Rashid Jamil 2907-01-01T00:00:00Z http://hdl.handle.net/123456789/20904 RIS-Assisted UAV-Enabled Cell-Free MIMO Systems for 6G Communications Farhan Siddiqui, 09-244241-002 The exponential surge in global mobile data traffic and the stringent requirements of emerging applications such as extended reality, holographic telepresence, and advanced industrial automation expose fundamental limitations in 5G networks, particularly in achieving ultra-reliable low-latency communication (URLLC) and massive connectivity in challenging environments. This thesis investigates the performance enhancements provided by four pivotal 6G enabling technologies: conventional massive MIMO, cell-free massive MIMO, Reconfgurable Intelligent Surfaces (RIS), and UAV-assisted communication, with a focus on their ability to deliver superior coverage probability in high signal-to-interference-plus-noise ratio (SINR) regimes essential for future wireless systems, including Industry 4.0 deployments. Despite extensive theoretical and simulation-based research demonstrating individual benefits of these technologies, a notable research gap persists in the absence of unified, comparative evaluations conducted under consistent modelling assumptions and realistic propagation conditions. To address this gap, this study employs large-scale Monte Carlo simulations (10,000 independent drops per scenario) to systematically quantify coverage probability across SINR thresholds ranging from 0 to 20 dB. The primary objectives are to: (1) model and evaluate the SINR coverage performance of each technology against its respective baseline; (2) assess implications and limitations for 6G network design. Key findings indicate that cell-free massive MIMO achieves near-perfect coverage (100 %) even at 20 dB SINR, outperforming all others due to macro-diversity and cell-edge elimination. RIS delivers substantial passive gains, pushing coverage close to 100% in obstructed scenarios. Conventional massive MIMO provides reliable and consistent array gain improvements, while UAV-assisted communication offers modest but valuable line-of-sight enhancements under favourable conditions. Overall, the technologies rank as cell-free MIMO > RIS > conventional MIMO > UAV for high-reliability applications. These results highlight the critical role of technology integration in realising robust, energy-efficient 6G networks capable of supporting extreme reliability demands in industrial settings. Supervised by Dr. Adil Ali Raja 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/20905 6G-Enabled ISAC: AI-Based Sensing and Communication Convergence Saqib Islam, 09-244241-004 Integrated Sensing and Communications (ISAC) shares radio resources, evolving from existing to 6G cellular networks. However, due to the highly dynamic nature of 6G, traditional ISAC models fail. This thesis investigates whether an AI-based framework can help converge ISAC by using an experimental simulation-driven methodology. A synthetic dataset containing 10,000 6G ISAC scenarios has been created in various environments. A selection of 7 different machine learning techniques were used to assess their ability to determine an accurate prediction of the Sensing Range from the communication parameters (Sensing Accuracy/Sensing Range, Data Rate/Sensing Range and Spectral Effciency/Sensing Range). The outcome presents a fundamental trade-off between data rate and the Sensing Range through an inverse-read correlation coeffcient of 0.38. Based upon the use of more advanced set techniques (e.g. ensemble models), XGBoost (R² = 0.60, MAE = 4.24 m) outperformed all previous linear based established models (R² = 0.37, MAE = 5.25 m). Thus providing conclusive evidence for the complexity of non-linear characteristics in relation to ISAC systems. This research provides a single empirical framework driven by AI and demonstrates that XGBoost provides an accuracy and interpretability necessary to operate and manage intelligent 6G networks; thereby flling the gap between the theoretical building blocks of ISAC and the practical AI implementation required by ISAC for 6G. Supervised by Dr. Adil Ali Raja 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/20902 Communication Link Modelling of Vehicle-To-Everything (V2x) Networks Muhammad Sohail Sajid, 01-244232-006 A crucial enabling technology for intelligent transportation systems is vehicle-toeverything (V2X) communication, which provides dependable wireless connectivity to support applications related to traffc effciency and safety. Because of the high vehicle mobility, heavy traffc, and stringent latency and reliability requirements, accurate performance evaluation of V2X networks is critical. While existing analytical models frequently rely on simplifed assumptions like fxed communication ranges and ideal channel conditions, which limit their practical accuracy, simulation-based approaches offer detailed insights but are computationally costly. The analytical modeling of IEEE 802.11p-based V2X communication links with realistic wireless propagation and interference effects is the main focus of this thesis. The suggested framework takes into consideration changes in signal power, interference from nearby vehicles, hidden terminal effects, and packet reception failures due to channel impairments, in contrast to traditional models that assume error free communication within a predetermined range. Packet Delivery Ratio (PDR) and the likelihood of transmission failure due to propagation errors, packet collisions, receiver busy states, and sensing errors are among the important performance metrics that the model assesses. Extensive simulations with different vehicle densities, transmission ranges, and data rates are used to validate the analytical results. The accuracy of the suggested model is confrmed by the comparison, which shows strong agreement between analytical predictions and simulation results. The fndings also demonstrate how mobility and interference signifcantly affect the reliability of V2X communication, especially in situations with heavy traffc. All things considered, this work offers an analytical framework for assessing V2X communication performance that is more practical and scalable. In addition to supporting the creation and improvement of dependable V2X systems for upcoming intelligent transportation applications, the suggested model can help researchers and system designers better understand network behavior. Supervised by Dr. Junaid Imtiaz 2026-01-01T00:00:00Z