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Abstract-In this paper, we study the sum degrees of freedom (DoF) of an uplink two-cell multiuser MIMO interference network with asymmetric number of users in the cells. The achievable DoF is devised based on a two-dimensional space-time spreading code framework with linear precoding/decoding design and finite channel extension. The derivation of the achievable DoF is shown related to a rank minimization problem, which corresponds to the minimization of the dimension of the interference subspace. The problem is solved by the proposed grouping algorithm (GA) based on aligning interfering signals into a low-dimensional subspace as a group and attaining the minimum number of groups. The achievable sum DoF derived based on the proposed GA is shown to be greater than prior arts and achieves the theoretic upper bound in several cases. We also give a closed-form expression of the maximum achievable sum DoF when there is the maximum number of admissible users in the considered finite diversity environment.Index Terms-Degrees of freedom, interference alignment, multiuser MIMO, cellular networks, grouping algorithm.

This paper studies the fairness optimization of dynamic multiuser multicarrier allocation in the cellular downlink of MIMO orthogonal frequency division multiple access (OFDMA) systems. The varying capacity demands of different users motivate the fairness problem. In the resource allocation approaches that maximizing the sum rate or minimizing the total power often leads to poor fairness among users. The allocation is prone to starvation situation for the users with deep fading subchannels. Hence, this work considers the fairness issue and proposes to maximize the minimum rate surplus, where the rate surplus is defined as the difference between the demand data rate and the resulting allocated data rate. The fairness is inverse proportional to the gap of the maximum rate surplus to the minimum rate surplus among all users. In this work, the design of the precoding and decoding matrices for the MIMO structure is also developed. To solve the optimization problem, an iterative algorithm is proposed to optimize the subcarrier assignment with low complexity. Simulation results on multiuser MIMO environment show that the proposed algorithm strikes the balance between sum rate and fairness. Comparing with the stateof-the-art works, the proposed algorithm shows an advantage in keeping the sum rate while the fairness is significantly improved.