Packet-level network simulators such as ns-3 require accurate physical (PHY) layer models for packet error rate (PER) for wideband transmission over fading wireless channels. To manage complexity and achieve practical runtimes, suitable link-to-system mappings can convert high fidelity PHY layer models for use by packet-level simulators. This work reports on two new contributions to the ns-3 Wi-Fi module, which presently only contains error models for Single Input Single Output (SISO), additive white Gaussian noise (AWGN) channels. To improve this, a complete implementation of a link-to-system mapping technique for IEEE 802.11 TGn fading channels is presented that involves a method for efficient generation of channel realizations within ns-3. The runtimes for the prior method suffers from scalability issues with increasing dimensionality of Multiple Input Multiple Output (MIMO) systems. We next propose a novel method to directly characterize the probability distribution of the"effective SNR" in link-to-system mapping. This approach is shown to require modest storage and not only reduces ns-3 runtime, it is also insensitive to growth of MIMO dimensionality. We describe the principles of this new method and provide details about its implementation, performance, and validation in ns-3.
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This content will become publicly available on June 28, 2024
Efficient PHY Layer Abstraction for 5G NR Sidelink in ns-3
Physical (PHY) layer abstraction is an effective method to reduce the runtimes compared with link simulations but still accurately characterize the link performance. As a result, PHY layer abstraction for IEEE 802.11 WLAN and 3GPP LTE/5G has been widely configured in the network simulators such as ns-3, which achieve faster system-level simulations quantifying the network performance. Since the first publicly accessible 5G NR Sidelink (SL) link simulator has been recently developed, it provides a possibility of implementing the first PHY layer abstraction on 5G NR SL. This work deploys an efficient PHY layer abstraction method (i.e., EESM-log-SGN) for 5G NR SL based on the offline NR SL link simulation. The obtained layer abstraction which is further stored in ns-3 for use aims at the common 5G NR SL scenario of OFDM unicast single layer mapping in the context of Independent and Identically Distributed (i.i.d.) frequency-selective channels. We provide details about implementation, performance, and validation.
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- Award ID(s):
- 2016379
- NSF-PAR ID:
- 10466309
- Editor(s):
- Henderson, Thomas; Imputato, Pasquale; Liu, Yuchen; Gamess, Eric
- Date Published:
- Journal Name:
- WNS3 '23: Proceedings of the 2023 Workshop on ns-3
- Page Range / eLocation ID:
- 115 to 120
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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