The work presented in this paper addresses the sum rate maximization problem for the downlink of a wireless network where multiple transmitter-receiver links share the same medium and thus potentially interfere with each other. The solution of this problem requires the optimization of two aspects: the first one is the set of links that can be jointly scheduled, and the second is the set modulation and coding schemes (MCSs) that maximize the sum rate. A feasible link achieves a certain MCS if its signal-to-interference-plus-noise ratio (SINR) is above a threshold or target SINR associated with the MCS and the SINR of each link is coupled with the other links’ powers that are required to achieve their respective MCSs. Since the available MCSs form a finite set, the rate maximization problem has a combinatorial nature. We present iterative algorithms that find a suboptimal solution to the combinatorial problem by operating in two phases. Phase one verifies the feasibility of the MCS assignment by performing either eigenvalue analysis or power consumption analysis, and phase two uses the feasibility information delivered by phase one to modify either the set of links (user removal) or the MCS assignment if feasibility conditions are not fulfilled. Our approach extends the concept of user removal to the case of adaptive modulation, and this generalization allows us to schedule users more efficiently, improving outage probability figures. Numerical results show that the proposed algorithms achieved a good tradeoff between sum rate performance and complexity. Moreover, our algorithms are a low complex alternative to the state-of-the-art user-removal algorithms with minimum gap in outage performance.
['Eduardo D. Castañeda', 'Ramiro Samano-Robles', 'Atílio Gameiro']
Sum rate maximization via joint scheduling and link adaptation for interference-coupled wireless systems