Resource Allocation for Broadband Wireless Access Networks with Imperfect CSI

The high deployment and maintenance costs of last mile wireline networks (i.e., DSL and cable networks) have urged service providers to search for new cost-effective solutions to provide broadband connectivity. Broadband wireless access (BWA) networks, which offer a wide coverage area and high transmission rates in addition to their fast and low-cost deployment, have emerged as an alternative to last mile wireline networks. Therefore, BWA networks are expected to be deployed in areas with different terrain profiles (e.g., urban, suburban, rural) where wireless communication faces different channel impairments. This fact necessitates the adoption of various transmission technologies that combat the channel impairments of each profile. Implementation scenarios of BWA networks considered in this thesis are multicarrier-based direct transmission and single carrier-based cooperative transmission scenarios. The performance of these transmission technologies highly depends on how resources are allocated. In this thesis, we focus on the development of practical resource allocation schemes for the mentioned BWA networks implementation scenarios. In order to develop practical schemes, the imperfection of channel state information (CSI) and computational power limitations are among considered practical implementation issues. The design of efficient resource allocation schemes at the MAC layer heavily relies on the CSI reported from the PHY layer as a measure of the wireless channel condition. The channel estimation error and feedback delay renders the reported CSI erroneous. The inaccuracy in CSI propagates to higher layers, resulting in performance degradation. Although this effect is intuitive, a quantitative measure of this degradation is necessary for the design of practical resource allocation schemes. An approach to the evaluation of the ergodic mutual information that reflects this degradation is developed for single carrier, multicarrier, direct, and cooperative scenarios with inaccurate CSI. Given the CSI estimates and estimation error statistics, the presented evaluation of ergodic mutual information can be used in resource allocation and in assessing the severity of estimation error on performance degradation. A point-to-multipoint (PMP) network that employs orthogonal frequency division multiple access (OFDMA) is considered as one of the most common implementation scenarios of BWA networks. Replacing wireline networks requires not only providing the last mile connectivity to subscribers but also supporting their diverse services with stringent quality of service (QoS) requirements. Therefore, the resource allocation problem (i.e., subcarriers, rate and power allocation) is modeled as a network utility maximization (NUM) one that captures the characteristics of this implementation scenario. A dual decomposition-based resource allocation scheme that takes into consideration the diversity of service requirements and inaccuracy of the CSI estimation is developed. Numerical evaluations and simulations are conducted to validate our theoretical claims that the scheme maximizes resource utilization, coordinates with the call admission controller to guarantee QoS, and accounts for CSI inaccuracy. Cooperation has recently received great attention from the research community and industry because of its low cost and fast deployment in addition to the performance improvement it brings to BWA networks. In cooperative scenarios, subscribers cooperate to relay each other's signals. For this implementation scenario of BWA networks, a robust and constrained Kalman filter-based power allocation scheme is proposed to minimize power consumption and guarantee bit error probability (BEP) requirements. The proposed scheme is robust to CSI inaccuracy, responsive to changes in BEP requirements, and optimal in allocating resources. In summary, research results presented in this thesis contribute to the development of practical resource allocation schemes for BWA networks

Power optimization, network coding and decision fusion in multi-access relay networks

Multi-access relay (MAR) assisted communication appears in various applications such as hierarchical wireless sensor networks (WSN), two-way relay channels (TWRC) etc. since it provides a high speed and reliable communication with considerably large coverage. In this thesis, we develop the optimal power allocation, network coding and information fusion techniques to improve the performance of MAR channel by considering certain criterion (e.g., minimizing the average symbol error rate (SER) or maximizing the average sum-rate. For this purpose, we first derive optimal information fusion rules for hierarchical WSNs with the use of complete channel state information (CSI) and the partial CSI using channel statistics (CS) with the exact phase information. Later, we investigate the optimization of the MAR channel that employs complex field network coding (CFNC), where we have used two different metrics during the optimization: achievable sum rate and SER bound of the network under the assumption of receiver CSI. After that, we formulate the optimal power allocation problem to maximize the achievable sum rate of the MAR with decode and forward relaying while considering fairness among users in terms of their average achievable information rates under the constraints on the total power and network geometry. We show that this problem is non-convex and nonlinear, and obtain an analytical solution by properly dividing parameter space into four regions. Then, we derive an average SER bound for the CFNC coded MAR channel and aim to jointly optimize the CFNC and the relay power by minimizing SER bound under the total power constraint, which we prove as a convex program that cannot be solved analytically since the Karush-Khun-Tucker (KKT) conditions result in highly nonlinearity equations. Following that, we devise an iterative method to obtain SER optimal solutions which uses the information theoretical rate optimal analytical solution during the initialization and we show that this speeds up the convergence of the iterative method as compared to equal power allocation scheme. Next, we integrate CFNC into WSNs that operate over non-orthogonal communication channel, and derive optimal fusion rule accordingly, combine the SER bound minimization and the average rate-fairness ideas to come up with an approximate analytical method to jointly optimize CFNC and the relay power. Simulation results show that the proposed methods outperform the conventional methods in terms of the detection probability, achievable average sum-rate or average SER