Active-Passive IRS Aided Wireless Communication: New Hybrid Architecture and Elements Allocation Optimization

Intelligent reflecting surface (IRS) has emerged as a promising technology to enhance the wireless communication network coverage and capacity by dynamically controlling the radio signal propagation environment. In contrast to the existing works that considered active or passive IRS only, we propose in this paper a new hybrid active-passive IRS architecture that consists of both active and passive reflecting elements, thus achieving their combined advantages flexibly. Under a practical channel setup with Rician fading where only the statistical channel state information (CSI) is available, we study the hybrid IRS design in a multi-user communication system. Specifically, we formulate an optimization problem to maximize the achievable ergodic capacity of the worst-case user by designing the hybrid IRS beamforming and active/passive elements allocation based on the statistical CSI, subject to various practical constraints on the active-element amplification factor and amplification power consumption, as well as the total active and passive elements deployment budget. To solve this challenging problem, we first approximate the ergodic capacity in a simpler form and then propose an efficient algorithm to solve the problem optimally. Moreover, we show that for the special case with all channels to be line-of-sight (LoS), only active elements need to be deployed when the total deployment budget is sufficiently small, while both active and passive elements should be deployed with a decreasing number ratio when the budget increases and exceeds a certain threshold. Finally, numerical results are presented which demonstrate the performance gains of the proposed hybrid IRS architecture and its optimal design over the conventional schemes with active/passive IRS only under various practical system setups.

I. Introduction

Although the fifth-generation (5G) wireless network is still under deployment, researchers have moved forward to define the next-generation or sixth-generation (6G) wireless network, with the aim for achieving more stringent performance, such as unprecedentedly high throughput, super-high reliability, ultra-low latency, extremely low power consumption, etc [1], [2]. However, these targets may not be fully achieved by only relying on the existing technologies, such as massive multi-input multi-output (MIMO) and millimeter wave (mmWave) communications, which can attain enhanced performance but generally incur more substantial energy consumption and hardware cost. On the other hand, wireless communication performance is fundamentally constrained by the wireless channel impairments such as path-loss, shadowing, and small-scale fading, which can be partially mitigated by conventional wireless communication techniques such as power control, adaptive modulation, diversity, dynamic beamforming, etc., but still remain random and uncontrolled at large. Recently, intelligent reflecting surface (IRS) has emerged as a promising technology to address the above issues by leveraging massive low-cost reflecting elements to flexibly and dynamically control the radio signal propagation environment in favor of wireless communications/sensing, thus achieving substantially improved communication spectral/energy efficiency and sensing accuracy cost-effectively [3], [4], [5], [6], [7].