A low complex joint optimization model for maximizing sum rate and energy efficiency in an IRS-assisted multi-user communication scenario

The sum-rate and energy efficiency of an Intelligent Reflective Surfaces (IRS)-assisted downlink multi-user communication scenario with a generalized fading channel model is improved by implementing joint optimization of the active precoding matrix at Base Station (BS) and phase optimization at IRS. To fulfil this objective, joint optimization is first obtained by incorporating the Semi Definite Relaxation (SDR) optimization algorithm in the κ−μ fading channel model to evaluate the considered system model’s sum rate and energy efficiency. Then, to improve the performance and reduce the complexity, the Manifold Optimization (MO) algorithm is deployed to tackle the unit modulus constraint in the phase optimization problem. In the end, simulation results present an improvement in the sum rate of almost 10% and 12% increased energy efficiency for the MO algorithm compared to the SDR optimization. Also, the convergence and computational time analysis of both algorithms are provided, which also steers towards the less complex nature of the MO algorithm. It is also been concluded with the simulation results that an increment in the number of reflecting elements has more effect on improving the efficient performance of the communication system rather than increasing the number of active antennas at the BS.