Supporting 5G Wireless Networks Through IEEE802.11ac Standard With New Massive MIMO Antenna System Module Design in Omnet++ Simulator

Inzillo, Vincenzo; Rango, Floriano De; Quintana, Alfonso Ariza

doi:10.5220/0006910800620072

Cited by 8 publications

(3 citation statements)

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“…Unfortunately, there is almost no support for antenna arrays components with beamforming in INET/INETMANET, with the notable exception of [38]. Furthermore, our interest was primarily in the behavior of the routing protocol, separated from the intricacies of the link layer and physical layer models.…”

Section: Methodsmentioning

confidence: 99%

Avoiding Detection by Hostile Nodes in Airborne Tactical Networks

et al. 2023

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Contemporary airborne radio networks are usually implemented using omnidirectional antennas. Unfortunately, such networks suffer from disadvantages such as easy detection by hostile aircraft and potential information leakage. In this paper, we present a novel mobile ad hoc network (MANET) routing protocol based on directional antennas and situation awareness data that utilizes adaptive multihop routing to avoid sending information in directions where hostile nodes are present. Our protocol is implemented in the OMNEST simulator and evaluated using two realistic flight scenarios involving 8 and 24 aircraft, respectively. The results show that our protocol has significantly fewer leaked packets than comparative protocols, but at a slightly higher cost in terms of longer packet lifetime.

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Section: Methodsmentioning

confidence: 99%

Avoiding Detection by Hostile Nodes in Airborne Tactical Networks

et al. 2023

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“…We simulated a MANET environment using OMNeT 6 preview 10 version. Note that the part related 802.11ay extends the code presented in [38] and is referred to a private github repository branch that is in progress and also contains support for 802.11ax standard (in case of interest for contribution in the development of the code please refer to one author of the present proposal). The network consists of a certain number of uniformly distributed mobile nodes that vary from 20 to 100 (according the simulation seed).…”

Section: Simulation Setupmentioning

confidence: 99%

A Deep Learning Clustering Beamforming Approach for Future 6G Mobile Ad Hoc Networks

Inzillo¹,

Garompolo²

2023

Preprint

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The rapid advancement of wireless technologies and the increasing demand for seamless, high-speed connectivity has spurred the need for efficient routing protocols in 6G Mobile Ad Hoc Networks (MANETs). This paper proposes a modern approach, the Deep Learning Clustering Beamforming Massive MIMO Routing Protocol (DLCB), that is designed to achieve high level throughput by exploiting beamforming advantages and for enhancing communication efficiency for future next generation 6G MANETs. The DLCB algorithm establishes robust and efficient routes for data transmission by adopting a clustering strategy based on deep learning allowing to select cluster heads by taking advantage of Graph Neural Networks (GNN) features and creating effective cluster paths. Furthermore, this approach integrates IEEE 802.11ay and Massive MIMO technologies to exploit their benefits in terms of high-speed data transmission, improved network capacity, and better signal quality. DLCB aims to facilitate seamless data transmission in dynamic network environments, paving the way for enhanced network performance in 6G MANETs. Experimental evaluations and simulations are conducted to validate the performance of the proposed approach through the use of Omnet++ Network Simulator.

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“…performs 802.11n with a configuration of 40 MHz and two SS in terms of maximum throughput by 28%. By using the OMNet++ network simulator, a new Massive MIMO module is designed by [10] for verifying the operation of an IEEE 802.11ac wireless network according to the theoretical expectations. Sharma [11] has investigated the capabilities of the IEEE 802.11e protocol to improve QoS support in WLAN for time critical applications.…”

Section: Related Workmentioning

confidence: 99%

On the evaluation of the IEEE 802.11ac WLAN performance with QoS deployment

Farej

Ali

2021

IJEECS

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The increase in the number of users on wireless local area networks (WLAN) and the development of large size applications have increased the demand for high-speed data rate and low latency. The IEEE 802.11ac was developed to provide very high throughput WLANs. Many enhancements are added to the medium access control (MAC) and physical (PHY) layers to increase data rate and improve network performance, these features enable the IEEE 802.11ac standard to provide quality of service (QoS) for multimedia applications. This paper concentrates on the impact of QoS on the system performance in term of delay and throughput. Four scenarios are proposed to investigate the network performance with different (from 1 up to 8) spatial stream (SS). The objective modular network testbed in C++ (OMNet++ modeler v5.5.1) is used to simulate and model these scenarios. For 8×8 SS, the results of simulation show the best throughput (maximum) and delay (minimum) values of (622, 484, 399.3, 382.96 Mbps) and (0.0211, 0.0589, 0.1037, 0.1202 sec) for 5, 15, 30 and 45 node number scenarios respectively. Although the number of nodes increases, the system performance decreases, however when QoS is deployed the performance is enhanced and its best improvement is obtained at the highest (45) node number scenario with values of 94.4% and 56.1% for throughput and delay respectively.

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Supporting 5G Wireless Networks Through IEEE802.11ac Standard With New Massive MIMO Antenna System Module Design in Omnet++ Simulator

Cited by 8 publications

References 0 publications

Avoiding Detection by Hostile Nodes in Airborne Tactical Networks

Avoiding Detection by Hostile Nodes in Airborne Tactical Networks

A Deep Learning Clustering Beamforming Approach for Future 6G Mobile Ad Hoc Networks

On the evaluation of the IEEE 802.11ac WLAN performance with QoS deployment

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