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

Official URL: http://risc01.sabanciuniv.edu/record=b1589543 (Table of Contents)

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.