Low-Complexity Beam Training for Multi-RIS-Assisted Multi-User Communications

المفاهيم الأساسية

The author proposes a novel hashing multi-arm beam training scheme to reduce complexity and improve accuracy in multi-user millimeter wave communication systems.

الملخص

In the paper, the authors address the high complexity and low identification accuracy of existing beam training techniques in mmWave systems. They introduce a hashing multi-arm beam (HMB) training scheme that reduces complexity to logarithmic order while maintaining high accuracy. By utilizing independent hash functions, soft decision demultiplexing, and a multi-round voting mechanism, the proposed method enables simultaneous training for multiple RISs and users. Simulation results demonstrate significant improvements in identification accuracy compared to existing techniques.

الإحصائيات

Simulation results show that the proposed HMB training scheme enables simultaneous training for multiple RISs and multiple users.
The proposed scheme can significantly improve the identification accuracy by at least 20% compared to existing beam training techniques.
The training complexity of the proposed method is O(BlogN), offering significant advantages.

اقتباسات

"The proposed HMB training scheme enables simultaneous training for multiple RISs and multiple users."
"Our proposed scheme can significantly improve the identification accuracy by at least 20% compared to existing beam training techniques."
"The training complexity of the proposed method is O(BlogN), offering significant advantages."

الرؤى الأساسية المستخلصة من

Low-Complexity Beam Training for Multi-RIS-Assisted Multi-User Communications

by Yuan... في arxiv.org 03-14-2024

https://arxiv.org/pdf/2403.08339.pdf

استفسارات أعمق

How does the use of independent hash functions impact the correlation between different RIS reflection links

The use of independent hash functions plays a crucial role in minimizing the correlation between different reconfigurable intelligent surface (RIS) reflection links. By employing separate hash functions for each RIS to generate multi-arm beams, the resulting beams are distributed in a way that ensures minimal correlation between the reflective links of different RISs. This independence allows for a comprehensive exploration of potentially aligned beam directions without introducing unwanted correlations that could impact the accuracy of beam identification.

What are potential limitations or drawbacks of using a multi-round voting mechanism in beam identification

While a multi-round voting mechanism can be effective in determining the aligned direction during beam identification, there are potential limitations to consider. One drawback is the increased complexity introduced by conducting multiple rounds of voting, especially as the number of users and RISs grows. This complexity may lead to higher computational requirements and longer processing times, impacting real-time applications where efficiency is critical. Additionally, there is a risk of misalignment or errors if not enough votes are cast on accurate directions or if noise interferes with the voting process, potentially reducing overall identification accuracy.

How might advancements in reconfigurable intelligent surfaces impact future developments in communication systems

Advancements in reconfigurable intelligent surfaces (RISs) have significant implications for future developments in communication systems. These surfaces offer opportunities to enhance spectrum/energy efficiency, mitigate interference, and enable customized wireless environments manually. With their ability to manipulate radio propagation environments using metamaterial antenna arrays controlled dynamically, RISs pave the way for improved coverage and achievable rates in communication systems.
In practical terms, integrating RIS technology into existing infrastructure can lead to more efficient use of available spectrum resources by optimizing signal paths through reflection and manipulation techniques. This optimization can result in better signal quality over longer distances while reducing power consumption—a critical factor for sustainable communication networks.
Moreover, advancements in RIS technology may drive innovations such as smart radio environments empowered by these surfaces—opening up possibilities for enhanced connectivity solutions across various scenarios like indoor communications or outdoor deployments where traditional methods face challenges due to path loss at higher frequencies like millimeter waves.