# Multi-stream Transmission for Directional Modulation Network via Distributed Multi-UAV-aided Multi-active-IRS

arXiv: https://arxiv.org/abs/2404.15297 · HTML: https://mlsanity.com/paper/2404.15297/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 19 of its 39 references that are in the map.
- First posted on arXiv 26 Mar 2024.

## Builds on (most cited first, 19 of 19)

- [Model-Driven Deep Learning for Physical Layer Communications](https://mlsanity.com/paper/1809.06059/) (2018)
- [Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming](https://mlsanity.com/paper/1810.03961/) (2018)
- [Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network](https://mlsanity.com/paper/1905.00152/) (2019)
- [Wireless Communications Through Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/1906.09490/) (2019)
- [Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead](https://mlsanity.com/paper/2004.09352/) (2020)
- [Multicell MIMO Communications Relying on Intelligent Reflecting Surface](https://mlsanity.com/paper/1907.10864/) (2019)
- [Intelligent Reflecting Surface-Assisted Millimeter Wave Communications: Joint Active and Passive Precoding Design](https://mlsanity.com/paper/1908.10734/) (2019)
- [Active RIS vs. Passive RIS: Which Will Prevail in 6G?](https://mlsanity.com/paper/2103.15154/) (2021)
- [Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison](https://mlsanity.com/paper/1908.08747/) (2019)
- [Enhanced Secrecy Rate Maximization for Directional Modulation Networks via IRS](https://mlsanity.com/paper/2008.05067/) (2020)
- [Active RIS Versus Passive RIS: Which Is Superior with the Same Power Budget?](https://mlsanity.com/paper/2112.07510/) (2021)
- [Low-complexity Joint Phase Adjustment and Receive Beamforming for Directional Modulation Networks via IRS](https://mlsanity.com/paper/2207.04829/) (2022)
- [Intelligent Surfaces for 6G Wireless Networks: A Survey of Optimization and Performance Analysis Techniques](https://mlsanity.com/paper/2006.06541/) (2020)
- [Enhanced Secure Wireless Transmission Using IRS-aided Directional Modulation](https://mlsanity.com/paper/2209.14721/) (2022)
- [Active-IRS Aided Wireless Network: System Modeling and Performance Analysis](https://mlsanity.com/paper/2211.04173/) (2022)
- [Three High-rate Beamforming Methods for Active IRS-aided Wireless Network](https://mlsanity.com/paper/2212.02186/) (2022)
- [Performance Analysis of Active RIS-aided Systems in the Face of Imperfect CSI and Phase Shift Noise](https://mlsanity.com/paper/2301.09716/) (2023)
- [Reconfigurable Intelligent Surface Aided Amplitude- and Phase-Modulated Downlink Transmission](https://mlsanity.com/paper/2301.09717/) (2023)
- [Asymptotic Performance Analysis of Large-Scale Active IRS-Aided Wireless Network](https://mlsanity.com/paper/2305.19931/) (2023)

## Abstract (arXiv)

Active intelligent reflecting surface (IRS) is a revolutionary technique for the future 6G networks. The conventional far-field single-IRS-aided directional modulation(DM) networks have only one (no direct path) or two (existing direct path) degrees of freedom (DoFs). This means that there are only one or two streams transmitted simultaneously from base station to user and will seriously limit its rate gain achieved by IRS. How to create multiple DoFs more than two for DM? In this paper, single large-scale IRS is divided to multiple small IRSs and a novel multi-IRS-aided multi-stream DM network is proposed to achieve a point-to-point multi-stream transmission by creating K (≥3) DoFs, where multiple small IRSs are placed distributively via multiple unmanned aerial vehicles (UAVs). The null-space projection, zero-forcing (ZF) and phase alignment are adopted to design the transmit beamforming vector, receive beamforming vector and phase shift matrix (PSM), respectively, called NSP-ZF-PA. Here, K PSMs and their corresponding beamforming vectors are independently optimized. The weighted minimum mean-square error (WMMSE) algorithm is involved in alternating iteration for the optimization variables by introducing the power constraint on IRS, named WMMSE-PC, where the majorization-minimization (MM) algorithm is used to solve the total PSM. To achieve a lower computational complexity, a maximum trace method, called Max-TR-SVD, is proposed by optimize the PSM of all IRSs. Numerical simulation results has shown that the proposed NSP-ZF-PA performs much better than Max-TR-SVD in terms of rate. In particular, the rate of NSP-ZF-PA with sixteen small IRSs is about five times that of NSP-ZF-PA with combining all small IRSs as a single large IRS. Thus, a dramatic rate enhancement may be achieved by multiple distributed IRSs.