The emergence of millimeter-wave based technologies is pushing the deployment of the 5th generation of mobile communications (5G), on the potential to achieve multi-gigabit and low-latency wireless links. Part of this breakthrough was only possible with the introduction of small antenna arrays, capable to form highly directional and electronically steerable beams. This strategy allowed the overcoming of some drawbacks, but with a higher price: the re-design of the lower layers by introducing beamforming techniques. The impact of these changes is not well studied on the higher layers, in the most recent stacks (IEEE 802.11ad, 3GPP). Thus, the study of real deployments and the use of accurate network simulators play a key role, by enabling the test of complex large-scale scenarios. This article presents a key component missing in the simulation of mmWave networks, a blockage model. To the best of our knowledge, this is first blockage model that emulates the effects of obstacles in the mmWave links. Additionally, a codebook generation of a phased antenna array, with the Quasi-Deterministic (Q-D) channel model is also presented. All models are tested and compared with an outdoor mmWave network using the IEEE 802.11ad standard. The simulated and the real-life tests show similar results, with an average error for the worst case of 2.43% (index ranges) and 4.51% (distance), and to an average standard deviation of about 1.33 dBm and 2.26 dBm.
The wireless backhaul has become a key enabler for 5G technology by presenting a costeffective and scalable alternative to the typical fiber backhaul. WiGig protocols, such as IEEE 802.11ad and later IEEE 802.11ay, have been considered for backhaul connectivity of 5G mobile networks, thanks to the availability of high bandwidths capable of achieving fiber-like data rates. However, this band suffers from high propagation loss that can only be compensated using highly directional antennas, making mmWave links more susceptible to blockage and errors. Thus, to effectively evaluate the viability of WiGig-based technologies in wireless backhaul scenarios, it is crucial to characterize the impact of obstruction across the different network layers. This article presents an extensive measurement campaign and cross-layer analysis of physical (PHY), medium access control (MAC), and transport layers metrics measured for outdoor WiGig-based hardware submitted to short-term and long-term blockage. This study found that maintaining constant and higher modulation and coding schemes (MCSs) in long-term blocked channels may induce packet errors as high as 100%, round-trip-time (RTTs) that can be in the order of a few seconds, and packet losses as high as 90%. Even dynamically adjusting the MCS, the performance can be highly degraded. This effect was exacerbated in short-term links, as they suffered from more extreme MCS changes upon sudden obstructions. Temporary line of sight (LOS) obstruction was shown to cause maximum delays of half a second and a PER of around 20%; in more extreme cases, it has even led to temporary link failures.
LoRa is one of the most prominent LPWAN technologies due to its suitable characteristics for supporting large-scale IoT networks, as it offers long-range communications at low power consumption. The latter is granted mainly because end-nodes transmit directly to the gateways and no energy is spent in multi-hop transmissions. LoRaWAN gateways can successfully receive simultaneous transmissions on multiple channels. However, such gateways can be costly when compared to simpler single-channel LoRa transceivers, and at the same time they are configured to operate with pure-ALOHA, the well-known and fragile channel access scheme used in LoRaWAN. This work presents a fair, control-based channel hopping-based medium access scheme for LoRa networks with multiple single-channel gateways. Compared with the pure-ALOHA used in LoRaWAN, the protocol proposed here achieves higher goodput and fairness levels because each device can choose its most appropriate channel to transmit at a higher rate and spending less energy. Several simulation results considering different network densities and different numbers of single-channel LoRa gateways show that our proposal is able to achieve a packet delivery ratio (PDR) of around 18% for a network size of 2000 end-nodes and one gateway, and a PDR of almost 50% when four LoRa gateways are considered, compared to 2% and 6%, respectively, achieved by the pure-ALOHA approach.
LoRa is actually one of the most popular LPWAN technologies for IoT applications, due to its low‐power and long‐range transmissions. A single low‐cost, single‐channel LoRa Gateway is able to cover a large number of End‐Devices spread over a wide area. Gateway diversity is traditionally used to reduce the impact of packet losses: adding more Gateways can increase both delivery ratio and goodput, even when using a pure‐ALOHA access policy. However, such solution can be cost‐expensive and the adoption of control‐based medium access strategies, without violating the duty‐cycle constraints, can be, in some situations, a better option. In this letter, we compare the effectiveness of Gateway diversity against a medium access protocol with channel reservation. We evaluate if and in which scenarios, relatively to delivery ratio and goodput, in a single communication channel, it is better to add more Gateways to the system (hardware) or adopt a reservation protocol (software) for tackling the scaling‐up of the number of End‐Devices.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.