# Intelligent Reflecting Surface Enhanced Wireless Network: Joint Active and Passive Beamforming Design

arXiv: https://arxiv.org/abs/1809.01423 · HTML: https://mlsanity.com/paper/1809.01423/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Sep 2018.

## Built on by (most cited first, 7 of 7)

- [Multi-hop RIS-Empowered Terahertz Communications: A DRL-based Hybrid Beamforming Design](https://mlsanity.com/paper/2101.09137/) (2021)
- [Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA](https://mlsanity.com/paper/2104.01414/) (2021)
- [Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems](https://mlsanity.com/paper/2506.22448/) (2025)
- [Energy Efficiency Maximization in IRS-Aided Cell-Free Massive MIMO System](https://mlsanity.com/paper/2212.12744/) (2022)
- [A Novel Deep Reinforcement Learning-based Approach for Enhancing Spectral Efficiency of IRS-assisted Wireless Systems](https://mlsanity.com/paper/2302.14706/) (2023)
- [Machine Learning-Based Channel Prediction for RIS-assisted MIMO Systems With Channel Aging](https://mlsanity.com/paper/2406.07387/) (2024)
- [Unsupervised Learning based Element Resource Allocation for Reconfigurable Intelligent Surfaces in mmWave Network](https://mlsanity.com/paper/2509.03241/) (2025)

## Abstract (arXiv)

Intelligent reflecting surface (IRS) is envisioned to have abundant applications in future wireless networks by smartly reconfiguring the signal propagation for performance enhancement. Specifically, an IRS consists of a large number of low-cost passive elements each reflecting the incident signal with a certain phase shift to collaboratively achieve beamforming and suppress interference at one or more designated receivers. In this paper, we study an IRS-enhanced point-to-point multiple-input single-output (MISO) wireless system where one IRS is deployed to assist in the communication from a multi-antenna access point (AP) to a single-antenna user. As a result, the user simultaneously receives the signal sent directly from the AP as well as that reflected by the IRS. We aim to maximize the total received signal power at the user by jointly optimizing the (active) transmit beamforming at the AP and (passive) reflect beamforming by the phase shifters at the IRS. We first propose a centralized algorithm based on the technique of semidefinite relaxation (SDR) by assuming the global channel state information (CSI) available at the IRS. Since the centralized implementation requires excessive channel estimation and signal exchange overheads, we further propose a low-complexity distributed algorithm where the AP and IRS independently adjust the transmit beamforming and the phase shifts in an alternating manner until the convergence is reached. Simulation results show that significant performance gains can be achieved by the proposed algorithms as compared to benchmark schemes. Moreover, it is verified that the IRS is able to drastically enhance the link quality and/or coverage over the conventional setup without the IRS.