A Framework for End-to-End Evaluation of 5G mmWave Cellular Networks in ns-3

Abstract

The growing demand for ubiquitous mobile data services along with the scarcity of spectrum in the sub-6 GHz bands has given rise to the recent interest in developing wireless systems that can exploit the large amount of spectrum available in the millimeter wave (mmWave) frequency range. Due to its potential for multi-gigabit and ultra-low latency links, mmWave technology is expected to play a central role in 5th Generation (5G) cellular networks. Overcoming the poor radio propagation and sensitivity to blockages at higher frequencies presents major challenges, which is why much of the current research is focused at the physical layer. However, innovations will be required at all layers of the protocol stack to effectively utilize the large air link capacity and provide the end-to-end performance required by future networks.Discrete-event network simulation will be an invaluable tool for researchers to evaluate novel 5G protocols and systems from an end-to-end perspective. In this work, we present the first-of-its-kind, open-source framework for modeling mmWave cellular networks in the ns-3 simulator. Channel models are provided along with a configurable physical and MAC-layer implementation, which can be interfaced with the higher-layer protocols and core network model from the ns-3 LTE module to simulate end-to-end connectivity. The framework is demonstrated through several example simulations showing the performance of our custom mmWave stack.

Stochastic Geometric Coverage Analysis in mmWave Cellular Networks With Realistic Channel and Antenna Radiation Models

“…3) Aligned/misaligned gain model: In order to solve the aforementioned issue brought by inaccurate channel gains, one can use measurement-based channel gain models, such as the models provided by the New York University (NYU) Wireless Group [13], which are operating at 28 GHz as described in [13], [20]- [22]. However, the NYU channel gain model requires a large number of parameters, and is thus applicable only to system-level simulators with high complexity, as done in our previous study [23].…”

Low‐complexity networking based on joint energy efficiency in ultradense mmWave backhaul networks

“…The abovementioned innovative technologies mainly focus on the AN; yet, the joint design integrating both the access layer and the transport layer remains an open issue . Conventionally, transport capability is mainly provided through wired links, from which an abundant spectrum and an extremely low delay can be guaranteed.…”

“…[8][9][10][11] The abovementioned innovative technologies mainly focus on the AN; yet, the joint design integrating both the access layer and the transport layer remains an open issue. 12 Conventionally, transport capability is mainly provided through wired links, 13 from which an abundant spectrum and an extremely low delay can be guaranteed. However, with drastically increasing cost 14 for densely deploying wired links and a separation trend between the remote radio unit and the baseband processing unit, 13,15 the backhaul (BH) network is becoming the new obstacle for infrastructure providers and mobile network operators to further lift their profits.…”

Understanding End-to-End Effects of Channel Dynamics in Millimeter Wave 5G New Radio

“…Importantly, our measurement system can measure the channel in multiple directions nearly simultaneously, thereby providing a complete spatial and temporal trace of the channel. • 3GPP NR beam search: The channel measurements are then incorporated into a detailed ns-3 based simulation [7], [8] along with the latest 3GPP New Radio (NR) standard [1]. The simulation accurately models the beam tracking procedure at both the base station (gNB in NR terminology) and mobile user equipment (UE).…”

“…The blockage traces we measure experimentally are then integrated into a detailed ns-3 simulation developed in our earlier work [7], [8]. The simulator accurately models all layers of the communication stack including MAC, RLC, and PDCP as well as the core network and transport layer protocols and can capture the effects of rate adaptation, hybrid ARQ and RLC retransmissions during the blockage events.…”