High-performance Power Allocation Strategies for Active IRS-aided Wireless Network

Due to its intrinsic ability to combat the double-fading effect, the active intelligent reflective surface (IRS) be-comes popular. The main feature of active IRS must be supplied by power, and the problem of how to allocate the total power between base station (BS) and IRS to fully explore the rate gain achieved by power allocation (P A) to remove the rate gap between existing P A strategies and optimal exhaustive search (ES) arises naturally. First, the signal-to-noise ratio (SNR) expression is derived to be a function of P A factor ß E [0, 1]. Then, to improve the rate performance of the conventional gradient ascent (GA), an equal-spacing-multiple-point-initialization GA (ESMPI-GA) method is proposed. Due to its slow linear convergence from iterative GA, the proposed ESMPI-GA is high-complexity. Eventually, to reduce this high complexity, a low-complexity closed-form P A method with third-order Taylor expansion (TTE) centered at point ß0 = 0.5 is proposed. Simulation results show that the proposed ESMPI-GA and TTE obviously outperform existing methods like equal P A.