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In-band multi-connectivity with local beamtraining for improving mmWave network resilience

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MSWiM_2023_Multi_Connectivity (2).pdf (3.476Mb)
Identificadores
URI: https://hdl.handle.net/20.500.12761/1749
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Autor(es)
Grosheva, Nina; Hersyandika, Rizqi; Widmer, Joerg; Pollin, Sofie
Fecha
2023-10-29
Resumen
Multi-connectivity is considered a key enabler for 5G networks and beyond, aiming to enhance capacity by combining multiple communication links in the same or different bands. Similarly, in cell-free networks all Access Points (APs) jointly serve users in the same band, boosting capacity through enhanced spectral efficiency. Both approaches can be very effective in Millimeter-Wave (mmWave) networks by addressing key issues of reliability and robustness due to the multiple simultaneous links. Furthermore, the use of narrow directional beams in mmWave spatially separates the signals, allowing for in-band multi-connectivity through local beamtraining. Such in-band multi-connectivity would be an alternative design to traditional cell-free networks that does not rely on phase-coherent processing or centralized methods for interference suppression. The physical layer processing and resource allocation problem then simplifies to a local beamtraining challenge, making these networks easier and simpler to implement and deploy, as any connection just has to train and maintain the local beam. We validate this approach by designing a multi-connectivity mmWave network with minimal network synchronization, relying solely on analog beamforming for spatial separation. Our evaluation results demonstrate that inband multi-connectivity with 4 asynchronous and independent links can provide uninterrupted service even in dense, high-traffic scenarios, compared to up to 20% of service loss in a standard singleconnectivity deployment. Distributing the traffic across multiple APs also had throughput gains of up to 30%, showing that multiconnectivity mmWave networks can provide a high-throughput, reliable and stable service for next-generation applications.
Compartir
Ficheros
MSWiM_2023_Multi_Connectivity (2).pdf (3.476Mb)
Identificadores
URI: https://hdl.handle.net/20.500.12761/1749
Metadatos
Mostrar el registro completo del ítem

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