  Reducing computational complexity is crucial in optimizing the phase shifts
of Intelligent Reflecting Surface (IRS) systems since IRS-assisted
communication systems are generally deployed with a large number of reflecting
elements (REs). This letter proposes a low-complexity algorithm, designated as
Dimension-wise Sinusoidal Maximization (DSM), to obtain the optimal IRS phase
shifts that maximize the sum capacity of a MIMO network. The algorithm exploits
the fact that the objective function for the optimization problem is sinusoidal
w.r.t. the phase shift of each RE. The numerical results show that DSM achieves
a near-maximal sum rate and faster convergence speed than two other benchmark
methods.
