Base Station (BS) cooperation has been considered as a promising technology to mitigate co-channel interference (CCI), yielding great capacity improvement in cellular systems. In this paper, by combining frequency domain cooperation and space domain cooperation together, we design a new CCI mitigation scheme to maximize the total utility for a multi-cell OFDMA network. The scheme formulates the CCI mitigation problem as a mixture integer programming problem, which involves a joint user-set-oriented subcarrier assignment and power allocation. A computationally feasible algorithm based on Lagrange dual decomposition is derived to evaluate the optimal value of the problem. Moreover, a low-complexity suboptimal algorithm is also presented. Simulation results show that our scheme outperforms the counterparts incorporating BS cooperation in a single domain considerably, and the proposed low-complexity algorithm achieves near optimal performance.

Efficient resource allocation for delay-sensitive traffic, such as telephony and video streaming, in Orthogonal Frequency Division Multiple Access (OFDMA) networks is needed to increase system performance. In our system, users try to achieve a low queuing delay and buffer space usage by competing for transmission over the subchannels. We formulate this problem as a bargaining game and use the Nash Bargaining Solution (NBS) to realize a fair and efficient subchannel allocation for the users. Simulation results show performance improvements, with regard to packet dropping and delay distribution, over other algorithms.

In this letter, we propose a new modification to the belief propagation (BP) decoding algorithm for Finite-Geometry low-density parity-check (LDPC) codes. The modification is based on introducing feedback into the iterative process, which can break the oscillations of bit log-likelihood ratio (LLR) values. Simulations show that, with a given maximum iteration, the "feedback BP" (FBP) algorithm can achieve better performance than the conventional belief propagation algorithm.