LAUSR

The aspects of sum rate and fairness for dirty paper coding (DPC) based MIMO downlink communications are investigated in this paper. We first apply the $\ell _{1}$-norm fairness measure to formulate the problem of fairness maximization for a given sum rate as an optimization problem. The problem is unfortunately nonconvex and cannot be efficiently solved. To overcome the difficulty, we invoke the uplink-downlink duality to transform the problem back and forth between uplink and downlink communications. An efficient, iterative waterfilling based algorithm is then proposed to yield achievable rates with the best possible fairness values. Simulation results show that the proposed approach offers an enormous gain in the achievable sum rates for a wide range of fairness values, when compared to the popular successive zero-forcing DPC-based and block diagonalization based coding schemes.