Joint optimization in multi-user MIMO-OFDMA relay-enhanced cellular networks

MIMO, OFDMA and cooperative relaying are the key technologies in future wireless communication systems. However, under the usage of these technologies, resource allocation becomes a more crucial and challenging task. In multi-user MIMO-OFDMA relay-enhanced cellular networks, we formulate the optimal instantaneous resource allocation problem including user group selection, path selection, power allocation, and subchannel scheduling to maximize system capacity. We first propose a low-complex resource allocation algorithm named `CP-CP' under constant uniform power allocation and then use a water-filling method named `CP-AP' to allocate power among transmitting antennas. Moreover, we solve the original optimization problem efficiently by using the Jensen's inequality and propose a modified iterative water-filling algorithm named `AP-CP'. Based on `AP-CP', the `AP-AP' algorithm is proposed to allocate power adaptively not only among subchannels but also among multiple transmitting. Finally, we compare the performance of the four schemes. Our results show that allocating power among subchannels is more effective than among transmitting antennas if the average signal-to-noise radio of users is low, and vice versa. Furthermore, the `AP-AP' algorithm achieves the highest throughout especially for users near the cell edge.