As a result of rapid progress in research and development, today's wireless world exhibits several heterogeneous communication networks, such as cellular networks, satellite networks, wireless local area networks (WLAN), mobile ad hoc networks (MANET), and sensor networks. These networks are complementary to each other. Hence, their integration can realize a unified wireless system that has the best features of the individual networks. This has spurred much research interest in designing integrated next-generation of wireless systems (NGWS). While existing wireless networks have been extensively studied individually, the integrated wireless system brings new challenges in architecture design, system management, and protocol design. The different wireless networks use different communication technologies and are based on different networking paradigms. Therefore, it is challenging to integrate these networks such that their heterogeneities are hidden from each other and a harmonious inter-operation among them is achieved. The objective of this research is to design a scalable, secure, and robust architecture and to develop seamless mobility management protocols for NGWS. More specifically, an architecture that integrates the heterogeneous wireless systems is first proposed for NGWS. Next, a cross-layer (Layer 2 + 3) handoff management protocol is developed for NGWS. Afterward, analytical modeling is developed to investigate the handoff performance of the existing mobility management protocols for different types of applications. Finally, a framework for multi-layer mobility management is developed to support the seamless handoff support to all types of applications in NGWS.

Orthogonal frequency division multiplexing (OFDM) in next generation wireless systems provides high downlink data rates by employing frequency-domain scheduling and rate adaptation at the base station (BS). However, in order to control the significant feedback overhead required by these techniques, feedback reduction schemes are essential. Best-m feedback is one such scheme that is implemented in OFDM standards such as Long Term Evolution. In it, the sub channel (SC) power gains of only the m strongest SCs and their corresponding indices are fed back to the BS. However, two assumptions pervade most of the literature that analyze best-m feedback in OFDM systems. The first one is that the SC gains are uncorrelated. In practice, however, the SC gains are highly correlated, even for dispersive multipath channels. The second assumption deals with the treatment of unreported SCs, which are not fed back by the best-m scheme. If no user reports an SC, then no data transmission is assumed to occur. In this thesis, we eschew these assumptions and investigate best-m feedback in OFDM systems with correlated SC gains. We, first, characterize the average throughput as a function of correlation and m. A uniform correlation model is assumed, i.e., the SC gains are correlated with each other by the same correlation coefficient. The system model incorporates greedy, modified proportional- fair, and round robin schedulers, discrete rate adaptation, and non-identically distributed SC gains of different users. We, then, generalize the model to account for feedback delay. We show in all these cases that correlation degrades the average throughput. We also show that this effect does not arise when users report all the SC power gains to the BS. In order to mitigate the reduction in the average throughput caused by unreported SCs, we derive a novel, constrained minimum mean square error channel estimator for the best-m scheme to estimate the gains of these unreported SCs. The estimator makes use of the additional information, which is unique to the best-m scheme, that the estimated SC power gains must be less than those that were reported. We, then, study its implications on the downlink average cell throughput, again for different schedulers. We show that our approach reduces the root mean square error and increases the average throughput compared to several approaches pursued in the literature. The more correlated the SC gains, greater is the improvement.

Motivated by the increasing demand for higher data rates, coverage, and spectral efficiency, current and next generation wireless systems adapt transmission parameters and even who is being transmitted to, based on the instantaneous channel states. For example, frequency-domain scheduling(FDS) is an instance of adaptation in orthogonal frequency division multiple access(OFDMA) systems in which the base station opportunistically assigns different subcarriers to their most appropriate user. Likewise ,transmit antenna selection(AS) is another form of adaptation in which the transmitter adapts which subset of antennas it transmits with. Cognitive radio(CR), which is a next generation technology, itself is a form of adaptation in which secondary users(SUs) adapt their transmissions to avoid interfering with the licensed primary users(PUs), who own the spectrum. However, adaptation requires channel state information(CSI), which might not be available apriori at the node or nodes that are adapting. Further, the CSI might not be perfect due to noise or feedback delays. This can result in suboptimal adaptation in OFDMA systems or excessive interference at the PUs due to transmissions by the SUs in CR. In this thesis, we focus on adaptation techniques in current and next generation wireless systems and evaluate the impact of CSI –both perfect and imperfect –on it. We first develop a novel model and analysis for characterizing the performance of AS in frequency-selective OFDMA systems. Our model is unique and comprehensive in that it incorporates key LTE features such as imperfect channel estimation based on dense, narrow band demodulation reference signal and coarse, broad band sounding reference signal. It incorporates the frequency-domain scheduler, the hardware constraint that the same antenna must be used to transmit over all the subcarriers that are allocated to a user, and the scheduling constraint that the allocated subcarriers must all be contiguous. Our results show the effectiveness of combined AS and FDS in frequency-selective OFDMA systems even at lower sounding reference signal powers. We then investigate power adaptation in underlay CR, in which the SU can transmit even when the primary is on but under stringent interference constraints. The nature of the interference constraint fundamentally decides how the SU adapts its transmit power. To this end, assuming perfect CSI, we propose optimal transmit power adaptation policies that minimize the symbol error probability of an SU when they are subject to different interference and transmit power constraints. We then study the robustness of these optimal policies to imperfections in CSI. An interesting observation that comes out of our study is that imperfect CSI can not only increase the interference at the PU but can also decrease it, and this depends on the choice of the system parameters, interference, and transmit power constraints. The regimes in which these occur are characterized.