Resource allocation techniques in relay-aided multicell OFDMA-based wireless communication systems

This thesis studies resource allocation (RA) problems in multi-cell orthogonal frequency division multiple access (OFDMA) downlink systems with co-channel interference (CCI). This thesis contains four parts. In the first part, four signal models used for formulating RA problems in multi-cell OFDMA downlink systems are overviewed. For comparison, the classic sum rate maximized RA problem with per-station individual power constraints is considered. Applying the four signal models, exact formulations of the considered RA problem are proposed. Properties of the different formulations are unveiled and compared. Based on existing RA methods, suggestions about choosing a suitable signal model and problem formulation are given. Finally, an interesting property of the recommended formulations is unveiled. In the second part, the sum (over all cells and all destinations) rate maximized problem is considered in multi-cell decode-and-forward (DF) relay-aided OFDMA downlink systems. An iterative RA algorithm is proposed to optimize mode selection (decision whether the relay should help or not), subcarrier assignment and pairing (MSSAP) and power allocation (PA) in an alternate way. The proposed algorithm is coordinate ascent (CA) based and can reach a local optimum in polynomial time. In the third part, user fairness is further considered in multi-cell DF relay-aided OFDMA downlink systems. The problem of maximizing the weighted sum of per cell min-rate (WSMR) with per-cell total power constraints is formulated and its per-cell maximum fairness property is proven. An iterative RA algorithm is proposed to obtain a local optimum of the problem. The convergence and the per-cell user fairness of the proposed RA algorithm are proven. In the fourth part, multiple DF relay stations (RSs) are considered to assist data transmission in each cell. An iterative semi-distributed RA algorithm is firstly proposed to reach a local optimum with guaranteed convergence. Then a modified iterative waterfilling (IWF) algorithm is further proposed to solve the problem autonomously. An optimum algorithm is proposed to solve the local RA problem in each cell.