This Thesis is an embodiment of some research work carried out towards achieving faster and more reliable handover techniques in a Mobile WiMAX (Worldwide Interoperability for Microwave Access) network. Handover, also called handoff, is the critical mechanism that allows an ongoing session in a cellular mobile network like WiMAX to be seamlessly maintained without any call drop as the Mobile Station (MS) moves out of the coverage area of one base station (BS) to that of another. Mobile WiMAX supports three different types of handover mechanisms, namely, the hard handover, the Fast Base Station Switching (FBSS) and the Micro-Diversity Handover (MDHO). Out of these, the hard handover is the default handover mechanism whereas the other two are the optional schemes. Also, FBSS and MDHO provide better performance in comparison to hard handover, when it comes to dealing with the high-speed multimedia applications. However, they require a complex architecture and are very expensive to implement. So, hard handover is the commonly used technique accepted by the mobile broadband wireless user community including Mobile WiMAX users. The existing Mobile WiMAX hard handover mechanism suffers from multiple shortcomings when it comes to providing fast and reliable handovers. These shortcomings include lengthy handover decision process, lengthy and unreliable procedure of selecting the next BS, i.e., the target BS (TBS) for handover, occurrence of frequent and unwanted handovers, long connection disruption times (CDT), wastage of channel resources, etc. Out of these, reducing the handover latency and improving the handover reliability are the two issues that our present work has focused on. While the process of selecting the TBS for handover adds to the overall delay in completing the process of handover, choosing a wrong TBS for handover increases the chance of further unwanted handovers to occur or even a call drop to occur. The latter greatly hampers the reliability of a handover. In order to contribute to the solution of the above two problems of slow handover and unreliable handover, this Thesis proposes and investigates three handover techniques, which have been called Handover Techniques 1, 2 and 3, respectively. Out of these three techniques, the first two are fully MS-controlled while the third one is a dominantly serving BS-controlled. In Handover Techniques 1 and 2, which share between them some amount of commonness of ideas, the MS not only itself determines the need for a handover but also self-tracks its own independent movement with respect to the location of the (static) neighboring BSs (NBS). N both these handover techniques, the MS performs distance estimation of the NBSs from the signal strength received from the NBSs. But they (the two handover techniques) employ different kinds of “lookahead” techniques to independently choose, as the TBS, that NBS to which the MS is most likely to come nearest in the future. Being MS-controlled, both Handover Technique 1 and Handover Technique 2 put minimal handover-related workload on their respective SBSs who thus remain free to offer services to many more MSs. This interesting capability of the two handover techniques can increase the scalability of the WiMAX network considerably. In Handover Technique 3, which is a BS-controlled one with some assistance received from the MS, the SBS employs three different criteria or parameters to select the TBS. The first criterion, a novel one, is the orientation matching between the MS’s direction of motion and the geolocation of each NBS. The other two criteria are the current load of each NBS (the load provides an indication of a BS’s current QoS capabilities) and the signal strength received by the MS from each NBS. The BS assigns scores to each NBS against each of the three independent parameters and selects the TBS, which obtains the highest weighted average score among the NBSs. All three handover techniques are validated using simulation methods. While Handover Techniques 1 and 2 are simulated using Qualnet network simulator, for Handover Technique 3, we had to design, with barest minimum capability, our own simulation environment, using Python. Results of simulation showed that for Handover Techniques 1 and 2, it is possible to achieve around 45% improvement (approx) in the overall handover time by using the two proposed handover techniques. The emphasis in the simulation of the Handover Technique 3 was on studying its reliability in producing correct handovers rather than how fast handovers are. Five different arbitrary pre-defined movement paths of the MS were studied. Results showed that with orientation matching or orientation matching together with signal strength, reliability was extremely good, provided the pre-defined paths were reasonably linear. But reliability fell considerably when relatively large loads were also considered along with orientation matching and signal strength. Finally, the comparison between the proposed handover techniques in this Thesis and few other similar techniques in Mobile WiMAX proposed by other researchers showed that our techniques are better in terms providing fast, reliable and intelligent handovers in Mobile WiMAX networks, with scalability being an added feature.