Enhancing Directional Modulation Networks through Distributed Multi-UAV-Aided Multi-IRS for Multi-Stream Transmission

Core Concepts

A novel multi-IRS-aided multi-stream directional modulation network is proposed to achieve significant rate enhancement by creating more degrees of freedom compared to traditional single-IRS directional modulation networks.

Abstract

The paper proposes a novel distributed multi-UAV-aided multi-IRS network for directional modulation (DM) to achieve multi-stream transmission. The key insights are:

A large-scale active IRS is divided into multiple smaller distributed IRSs, each mounted on a UAV, to create more degrees of freedom (DoF) than a single IRS. This enables multi-stream point-to-point transmission.

Three methods are proposed:

NSP-ZF-PA: Null-space projection, zero-forcing, and phase alignment are used to design the transmit beamforming, receive beamforming, and phase shift matrix, respectively. This achieves high rate performance.
WMMSE-PC: Weighted minimum mean-square error with power constraint is used to jointly optimize the transmit beamforming, phase shift, and receive beamforming. The Majorization-Minimization algorithm is used to solve the phase shift matrix.
Max-TR-SVD: A maximum trace method based on singular value decomposition is proposed to optimize the phase shift matrix with lower complexity.

Analytical and simulation results show that the proposed multi-IRS network can achieve significantly higher rates compared to a single-IRS DM network, with the NSP-ZF-PA method outperforming the other two. The rate can be up to 5 times higher with 16 small IRSs compared to a single large IRS.

The relationship between the average SINR at the IRS and the SINR at the user is analyzed, showing they are linearly proportional when the IRS noise is fixed.

Stats

The transmit power at the base station is PB = 30 dBm.
The total power budget at the IRS is PI = 0.04 W.
The noise power at the IRS is σ^2_k = -40 dBm.
The noise power at the user is σ^2_z = -40 dBm.

Quotes

"A novel multi-IRS-aided multi-stream directional modulation 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)."
"Simulation results have 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."

Key Insights Distilled From

Multi-stream Transmission for Directional Modulation Network via distributed Multi-UAV-aided Multi-IRS

by Ke Yang,Rong... at arxiv.org 04-25-2024

https://arxiv.org/pdf/2404.15297.pdf

Deeper Inquiries

How can the proposed multi-IRS network be extended to scenarios with a direct link between the base station and the user

The proposed multi-IRS network can be extended to scenarios with a direct link between the base station and the user by modifying the beamforming and phase alignment strategies. In the current setup, the focus is on creating multiple degrees of freedom (DoFs) by distributing the IRS elements and utilizing UAVs to hang them. To incorporate a direct link scenario, the beamforming vectors and phase shift matrices can be adjusted to account for the presence of a direct path. This would involve optimizing the beamforming to take advantage of the direct link while still leveraging the distributed IRS elements for additional DoFs. By adapting the beamforming and phase alignment techniques, the system can effectively handle scenarios with both direct and reflected paths, maximizing the benefits of the multi-IRS architecture.

What are the potential challenges and practical considerations in deploying a distributed multi-UAV-aided multi-IRS system in real-world environments

Deploying a distributed multi-UAV-aided multi-IRS system in real-world environments poses several challenges and practical considerations. Some of these include:

UAV Coordination: Coordinating multiple UAVs to distribute and hang the IRS elements can be complex. Ensuring proper spacing, alignment, and synchronization among the UAVs is crucial for the effective functioning of the system.

Power and Connectivity: UAVs require sufficient power and connectivity to operate and communicate with the base station and IRS elements. Managing power consumption and ensuring continuous connectivity are essential for seamless operation.

Regulatory Compliance: Adhering to aviation regulations and obtaining necessary permits for UAV operations is vital. Compliance with airspace restrictions and safety protocols is critical for deployment.

Interference and Signal Quality: Managing interference and ensuring high signal quality between the base station, UAVs, IRS elements, and the user is a key challenge. Optimizing signal strength and minimizing interference are essential for reliable communication.

Scalability and Maintenance: Scaling the system to accommodate a larger number of IRS elements and UAVs requires careful planning. Regular maintenance, monitoring, and upkeep of the UAVs and IRS elements are necessary for long-term functionality.

What other applications beyond directional modulation could benefit from the increased degrees of freedom enabled by the proposed multi-IRS architecture

The increased degrees of freedom enabled by the proposed multi-IRS architecture can benefit various applications beyond directional modulation. Some potential applications include:

Wireless Communication Networks: Enhancing the capacity and coverage of wireless networks by optimizing signal transmission and reception using multiple IRS elements for improved connectivity and data rates.

IoT and Smart Cities: Facilitating seamless connectivity for Internet of Things (IoT) devices and smart city infrastructure by enhancing communication reliability and efficiency through multi-IRS configurations.

5G and Beyond: Supporting the evolving requirements of 5G networks and future generations of wireless technology by leveraging multi-IRS setups to enhance network performance, reduce latency, and increase data throughput.

Satellite Communication: Improving satellite communication systems by integrating multi-IRS architectures to enhance signal strength, reduce signal loss, and optimize data transmission for satellite-based services.

Rural Connectivity: Extending connectivity to rural and remote areas by deploying multi-IRS systems to overcome geographical challenges and provide reliable communication links for underserved communities.