Prototyping and Experimental Results for Environment-Aware Millimeter Wave Beam Alignment via Channel Knowledge Map

Kernekoncepter

The author presents a novel technique, CKM, for environment-aware communication using beam alignment strategies in millimeter wave systems.

Resumé

The content discusses the construction of a CKM to optimize beam alignment in dynamic environments, showcasing experimental results and comparisons with location-based strategies.
The CKM approach offers training-free beam alignment with improved communication performance in various scenarios.
Experiments demonstrate the effectiveness of CKM in achieving high received power and reducing training overhead compared to traditional methods.
The study highlights the potential of CKM for practical implementation in mmWave communication systems.

Statistik

The mmWave band ranges from 26.5-300 GHz.
The UWB positioning system has an update rate of 200Hz and an accuracy of 10cm.
The NI USRP-2974 device operates with a real-time bandwidth of up to 160MHz.
The mmPSA TR16-1909 supports time division duplex communication at 27-29 GHz.

Citater

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Prototyping and Experimental Results for Environment-Aware Millimeter Wave Beam Alignment via Channel Knowledge Map

by Zhuoyin Dai,... kl. arxiv.org 03-14-2024

https://arxiv.org/pdf/2403.08200.pdf

Dybere Forespørgsler

How can the CKM approach be adapted for other wireless communication technologies

The CKM approach can be adapted for other wireless communication technologies by customizing the construction and utilization of the channel knowledge map to suit the specific requirements of different systems. For instance, in cellular networks, CKM can be used to store information about cell coverage areas, signal strengths, interference levels, and handover parameters. In IoT applications, CKM can contain data on device locations, connectivity patterns, and network congestion points. By tailoring the CKM construction process to capture relevant channel characteristics unique to each technology, such as frequency bands, modulation schemes, antenna configurations, and propagation environments.

What challenges may arise when implementing CKM in real-world applications

Implementing CKM in real-world applications may present several challenges. One challenge is ensuring the accuracy and reliability of the channel knowledge stored in the map. This requires robust algorithms for offline construction based on accurate measurements or simulations. Another challenge is maintaining synchronization between the dynamic wireless environment and the static CKM during real-time operation. Changes in environmental conditions like obstacles or interference sources may impact beam alignment performance if not promptly reflected in the CKM.
Additionally,
ensuring seamless integration with existing communication protocols and hardware components poses a compatibility challenge.
Furthermore,
the scalability of CKM across large geographical areas or complex indoor environments could require significant computational resources for efficient mapping.
Moreover,
privacy concerns related to storing location-specific channel information must be addressed through secure data handling practices.

How does the use of dynamic obstacles impact the reliability of the CKM-based beam alignment strategy

The use of dynamic obstacles impacts
the reliability of
the CKM-based beam alignment strategy by introducing potential disruptions in communication links.
When a dynamic obstacle obstructs an existing LoS link between transmitter and receiver,
it can lead to signal blockage or degradation if not accounted for promptly.
In such cases,
the ability of
CKM-based strategy to switch seamlessly between LoS and NLoS links becomes crucial for maintaining reliable communication channels.
However,
if there are delays or inaccuracies in detecting these changes due to limitations in positioning systems or processing speeds,
there is a risk of temporary loss of connectivity until alternative paths are established using reflective NLoS links stored within
the Channel Knowledge Map (CKMs).