Optimising Wi-Fi HaLow Connectivity: A Framework for Variable Environmental and Application Demands

Abstract

As the number of IoT (Internet of Things) devices continues to grow at an exceptional rate, so does the variety of use cases and operating environments. IoT now plays a crucial role in areas including smart cities, medicine and smart agriculture, where environments vary to include built environments, forest, paddocks and many more. This research examines how Wi-Fi HaLow can be optimised to support the varying environments and a wide variety of applications. Through examining data from performance evaluation testing conducted in varying environments, a framework has been developed. The framework takes inputs relating to the operating environment and application to produce configuration recommendations relating to ideal channel width, MCS (Modulation and Coding Scheme), GI (Guard Interval), antenna selection and distance between communicating devices to provide the optimal performance to support the given use case. The application of the framework is then demonstrated when applied to three various scenarios. This research demonstrates that through the configuration of a number of parameters, Wi-Fi HaLow is a versatile network technology able to support a broad range of IoT use cases.

1. Introduction

It has been established that the growth in IoT devices is happening at an exceptional rate [1,2,3] across a wide array of device types and environments. Devices range from low-data, single-measurement sensors to high-definition video streaming, whereby each use case has its own unique requirements relating to data delivery and reliability. These devices operate in environments such as home/office locations, factories, bush environments and paddocks, with each presenting varying degrees of challenges. Such requirements and challenges can present substantial difficulty when developing robust wireless networks for device communication [4].

Using Wi-Fi HaLow devices, this research study conducted real-world performance evaluation testing in a number of varying environments, including a laboratory, a forested environment, a built CBD and a clear line-of-sight environment. The results from this testing were then used to build an understanding relating to the degree of impact experienced by wireless communication within each environment. This information then informed the development of a framework that provides targeted recommendations relating to establishing an optimal Wi-Fi HaLow network for a given use case. Wi-Fi HaLow, or IEEE802.11ah, was selected for this project as it was developed specifically to address the requirements of IoT devices in that it is a low-power, high-throughput and long-range protocol [5].

Wi-Fi HaLow makes use of a number of technologies to improve its performance and capability. Restricted Access Window (RAW) improves the ability to manage a large number of devices, giving a Wi-Fi HaLow access point (AP) the ability to support over 8000 station (STA) devices [6,7]. Target Wait Time (TWT) allows the AP to specify set times for STA devices to communicate. This improves the energy performance of the STA [8] as it is able to reduce the power given to the communication hardware outside of these times. Modulation and Coding Scheme (MCS) relates to the modulation type and coding rate of the data being transferred [9]. The Guard Interval (GI) refers to the length of the time interval between blocks of data. The MCS and GI both directly impact the throughput rates and the MCS is also impacted by signal strength.

1.1. Research Scope

This research aims to present a framework for establishing optimal Wi-Fi HaLow networks for IoT devices. While there exists a number of wireless network technologies that have been developed specifically for different IoT use cases, Wi-Fi HaLow was selected for this project. The reasons for this relate to its newness, its various capabilities in terms of throughput and range, and the lack of real-world performance evaluation testing available.

The primary concern of this project relates to developing optimal connections in terms of throughput and available range. To support this, this project is only focusing on changes to MCS and GI values as well as antenna selection.

1.2. Research Questions and Objectives

1.2.1. Research Question

How can Wi-Fi HaLow be optimised to support various applications in varying environments?

1.2.2. Objectives

• To develop a sound methodology to collect Wi-Fi HaLow technology performance data in varying real-world environments.
• To analyse collected data to identify the primary factors that could impact the performance, such as
  • Device parameters (BW, MCS, GI, Antenna type);
  • Environmental factors (LoS obstructions, land topology, AP elevation);
  • Application requirements (real-time, not real-time, payload size, transmission frequency, transmission priority).
• To understand how the identified factors positively and negatively impact the performance and to determine strategies and recommendations to ensure that the network can perform in various applications and environments.

1.3. Our Contribution

A framework to optimise Wi-Fi HaLow network performance, supporting the needs of a diverse range of IoT applications across multiple physical environments. The framework provides

• Specific parameter configurations;
• Expected distance;
• Expected throughput;
• Application suitability with the constraints of a given environment;
• Recommendations on optimisations that can be made to improve the network performance.

This study utilised authentic data collected across a range of environments to provide Wi-Fi HaLow users with confidence in the framework. This work has applications across a range of fields such as industrial IoT, smart cities and smart agriculture. This framework also informs whether Wi-Fi HaLow is a suitable form of communication technology prior to deployment, potentially saving time and money.

1.4. Paper Structure

The remainder of this paper is structured as follows:

• Section 2 provides background knowledge and explores related work on the topics of Wi-Fi HaLow, performance evaluation and the impact that environmental factors have on wireless communication.
• Section 3 identifies the hardware and software used to gather the data required for the development of the framework. It also outlines the various processes that were undertaken and the locations selected for gathering the data.
• Section 4 presents the results of the performance evaluation work. The results are presented and discussed in terms of the environment type of the location. Additionally, data from differing locations with similar environment qualities are also used for comparison.
• Section 5 introduces the framework that is the subject of this article. Step-by-step instructions are provided to develop recommendations.
• Section 6 demonstrates the application of the framework in three unique use case scenarios.
• Section 8 is a summary of key findings and results. It also includes a discussion on imitations experienced and areas for future work.

2. Related Work

This article presents a framework that has been developed for formulating configuration recommendations specifically for IoT networks using Wi-Fi HaLow technology. To better understand the context of this work, this section presents relevant background knowledge and related works into the development of Wi-Fi HaLow, Wi-Fi HaLow performance evaluation and optimisation, and some of the factors that have the ability to positively or negatively impact wireless communication.

2.1. Wi-Fi HaLow Technology Overview

Wi-Fi HaLow, or IEEE802.11ah, was developed by the IEEE802.11ah working group and was standardised in 2016 [10]. The purpose of Wi-Fi HaLow was to provide an IP-based wireless network technology that could address the ever increasing and varied demands of IoT. According to the standard documentation [11], Wi-Fi HaLow could theoretically achieve communication beyond a distance of 1 km, a throughput of up to 78 Mbps and an access point (AP) that can support over 8000 station devices. This is achieved by combining technologies such as RAW, TWT, MCS and GI, and by operating in the unlicensed sub-GHz bandwidth range.

Operating in the unlicensed sub-GHz bandwidth range, Wi-Fi HaLow has the capacity to utilise channel widths of 1, 2, 4, 8 or 16 MHz [12] (region dependent) providing throughput capability up to 78 Mbps at 16 MHz. When operating at the lower channel widths, Wi-Fi HaLow is able to achieve distances over 1 km due to its ability to maintain signal strength [13]. This allows Wi-Fi HaLow to be suitable for both short- and long-range communications, supporting a greater range of environments and use cases [14] such as industrial, agriculture and medical, in both indoor and outdoor environs [4].

Early research of IEEE802.11ah by researchers such as Stefan Aust [15,16,17] and Kohei Ogawa [18,19,20] in 2011 and 2012 presented the benefits, implications and application of IEEE802.11ah, primarily in conference papers. Once developed and standardised, research focus has largely shifted to the manipulation of RAW and TWT in an effort to improve energy efficiency and scalability. Experimentation for this research has relied on theoretical modelling and simulation.

Additional technologies within Wi-Fi HaLow are Modulation and Coding Scheme (MCS) and Guard Interval (GI). These parameters can either be automatically selected by the device’s programming or manually set when configuring the connection, impacting the throughput that can be achieved. For MCS values ranging from 1 to 9, the higher the value, the greater the data rate. As with the channel widths, this value is also reduced as signal strength falls in order to maintain a resilient connection [21].

The GI is another configurable technology that impacts throughput [21]. When data are transmitted via wireless communication, pauses between pulses of data are needed to ensure that the data are received correctly. The gap between these pulses is dictated by the GI. With strong communication channels, a short GI can be utilised, which then increases the rate the data are sent and received. In the event of the communication channel being weak or prone to interference, a long GI is used to ensure clear separation and identification of data [22].

2.2. Analysis of Performance Evaluation Literature

When working with a new and/or constantly developing and evolving technology, performance evaluation is an important step to ensure that results are provided based on the most up-to-date version of a technology. Wi-Fi HaLow is still relatively new in terms of its technological development and, as a result, there has been limited opportunity for researchers to conduct independent performance evaluation. Prior to 2023, research such as [22,23,24] was reliant on theoretical and simulated results for Wi-Fi HaLow performance evaluation. More recently, since the release of manufactured evaluation kits, works such as [25,26,27] from 2023 have begun to provide metrics from actual device testing.

This is further observed when a search of the SCOPUS literary database conducted in March 2024 with the search phrase “SEARCH WITHIN Article Title, Abstract, Keywords FOR halow or 802.11ah or ‘802.11 and ah’ YEARS 2012–2024” returned 210 results, of which 79 included some form of performance evaluation. These search results also indicated that only 5% of the 79 studies conducted real-world performance evaluations, with the remainder using simulated results. Wi-Fi HaLow devices and chips have continued to be developed beyond the technology used in earlier performance evaluation work. Despite this, in the 12 months following the initial search, subsequent search results across a range of databases have demonstrated a lack of substantial further research in this field.

Of the research where any form of performance evaluation work was undertaken with WI-Fi HaLow devices, all the studies used stock evaluation kits provided by the manufacturer. This includes the use of a supplied di-pole omni-directional antenna. When exploring research regarding antennas in the greater topic of IoT, articles such as [28,29] provide a current and comprehensive review of the many types of antennas for IoT devices and the circumstances where they would be applicable. Refs. [30,31] extend this further by examining alternate designs for miniature IoT devices with a focus on sub-GHz frequencies. Considering this interest and understanding of alternative antenna types, this appears to be largely unexplored in the literature in relation to performance evaluation.

2.3. Environmental Factors That Impact Wireless Communication

Environmental factors such as line-of-sight (LoS) and non-line-of-sight (NLoS), as well as the elevation of either the access point or station devices, radio interference, density of obstructions and climate-related factors, can significantly affect performance. Within the limited amount of “actual device” testing that has been published, refs. [25,32] both explore the differences that built environments such as walls and floors within a building have in signalling strength and reliability. Conversely, recent findings by the authors of [33] show the results of testing conducted in a desert-type, LoS environment. In such an environment, performance metrics are improved, as signal degradation caused by humidity and related factors are minimised extensively.

3. Materials and Methods

To obtain the data required to develop informed recommendations, we conducted real-world performance evaluation tests in a range of environments. This section will present the materials used (both hardware and software), the performance evaluation processes that were undertaken as well as the locations and the rationale for why they were selected.

3.1. Materials Utilised

The experimental setup consists of two identical nodes. Each node contains a Wi-Fi HaLow device, antenna, a laptop and other associated equipment. The software and hardware requirements for each node is shown in

Table 1. Hardware and software requirements list for each node.

Hardware	Software
Wi-Fi HaLow device consisting of - Silex Wi-Fi HaLow Evaluation Kit SX-SDMAH-EVK; - Raspberry Pi 4B; - SD card. Di-pole antenna; Yagi antenna; Rj-45 USB-C adapter; Ethernet Cat5e cable; USB-C cable for power supply; Power bank; Aluminium pole (1.5 m); Tripod (extended to 1.5 m); Laptops.	Raspberry Pi OS (Bullseye); Drivers and Utilities from Silex; Windows; Notepad; Microsoft Excel; Putty; PSFTP.

.

The Wi-Fi HaLow devices used consist of Silex EVK boards mounted on Raspberry Pi 4B microcomputers. The Silex board was selected as it utilises the Morse Micro MM6108 HaLow chip, which is capable of 8 MHz bandwidth selection, providing a greater array of capability and flexibility options. The Raspberry Pi 4B was selected as it provides compatibility with the drivers and software for the Wi-Fi HaLow board. The inclusion of the Yagi antenna in addition to the supplied Di-pole antenna allows for gathering a broader range of data in varying circumstances and environments.

3.2. Method Applied

Figure 1 shows a setup that was used during the performance evaluation experiments. It shows two nodes, the AP (access point) and STA (station) nodes. The physical connection of the devices and the logical configuration are displayed. Laptops are used to control and monitor Wi-Fi HaLow devices and capture data for analysis.

A range of data were gathered, including throughput, signal strength and packet loss. Various utilities and scripts were used to collect data and control and manage the devices, including the following:

• iw: Used to collect the signal strength (dB);
• iperf3: Used to measure the throughput (Kbps);
• Ping:Used to test connectivity and to measure packet loss (%);
• Bash scripts: Used to change configuration and to automate the experiments.

The experiments were repeated with different MCS and GI values and antennas at each of the selected locations:

• MCS: Manually set 0–7 (and 10 for 1 MHz testing) and automatic selection;
• GI: Long and short;
• Antennas: Di-pole and Yagi.

3.3. Testing Locations

The experiments were conducted at various types of locations. Table 2 provides a description of each location, what type of environment it is, and a brief rationale for why it was selected.

Table 2. The summary of the various testing location used as they represent different environment types.

Site Type	Location	Description and Rationale
Controlled Environment	Laboratory	A laboratory shielded from external radio frequency ($RF$) was selected to provide real authentic performance data from an environment with no external interference. This location represents ideal and optimal conditions and demonstrates the device’s full capabilities.
Clear Line-of-sight (LoS)	Woody Point, QLD	The location of Woody Point, Queensland, was selected to gather a broad range of data. A key reason for this selection was because the location has clear LoS visibility up to 7 km. This enabled both antennas (the omni-directional and directional) to be used in the same location to almost reach the maximum of their capabilities. Figure 2 shows the map locations and related distance markers used for gathering data with the omni-directional and directional antennas.
Built Environment	Queensland University of Technology Gardens Point Campus	Only omni-directional antennas were used at this location. The AP was located on the roof of the 12-story building while the STA was at ground level. This location represents the challenges that built environments present to wireless communication. Figure 3 shows the map locations and related distance markers used for gathering data.
Forest (Limited LoS)	Samford Ecological Research Facility, Samford, QLD	This is an area of native forest where line-of-sight visibility to the access point was lost at approximately 20 m. Performance evaluation data at this location included both the directional and omni-directional antenna types. This location represents the challenges facing IoT deployments in the natural environment, particularly in areas of dense vegetation. Figure 4 shows the map locations and related distance markers used for gathering data with the omni-directional and directional antennas.

Table 2. The summary of the various testing location used as they represent different environment types.

Site Type	Location	Description and Rationale
Controlled Environment	Laboratory	A laboratory shielded from external radio frequency ($RF$) was selected to provide real authentic performance data from an environment with no external interference. This location represents ideal and optimal conditions and demonstrates the device’s full capabilities.
Clear Line-of-sight (LoS)	Woody Point, QLD	The location of Woody Point, Queensland, was selected to gather a broad range of data. A key reason for this selection was because the location has clear LoS visibility up to 7 km. This enabled both antennas (the omni-directional and directional) to be used in the same location to almost reach the maximum of their capabilities. Figure 2 shows the map locations and related distance markers used for gathering data with the omni-directional and directional antennas.
Built Environment	Queensland University of Technology Gardens Point Campus	Only omni-directional antennas were used at this location. The AP was located on the roof of the 12-story building while the STA was at ground level. This location represents the challenges that built environments present to wireless communication. Figure 3 shows the map locations and related distance markers used for gathering data.
Forest (Limited LoS)	Samford Ecological Research Facility, Samford, QLD	This is an area of native forest where line-of-sight visibility to the access point was lost at approximately 20 m. Performance evaluation data at this location included both the directional and omni-directional antenna types. This location represents the challenges facing IoT deployments in the natural environment, particularly in areas of dense vegetation. Figure 4 shows the map locations and related distance markers used for gathering data with the omni-directional and directional antennas.

4. Performance Results and Analysis

This section presents the results from the performance evaluation testing as well as a comparative analysis of the data based on individual locations against the other locations.

4.1. Controlled Environment: Laboratory

In establishing the baseline data for throughput, two sets of data were collected in a controlled environment. To provide a pure environment without signal loss, the first setup is based on wired connection using a coaxial cable with a 20 dB, 500 ohm attenuator. The second setup utilises an omni-directional antenna for establishing a wireless connection.

Figure 5 represents the signal strength (a) and throughput (b) obtained using both connection methods. When examining the signal strength, it is noted that while the cable connection maintained a signal strength of 0 dB, the signal strength varied when using the omni-directional antenna. In relation to the throughput obtained, it is to be noted that there is no significant variation in results. These data provide an understanding of the maximum throughput capabilities of the evaluated devices. It also demonstrates the impact of distance on signal capabilities throughout further experiments.

4.2. Clear Line-of-Sight: Woody Point, QLD

The Woody Point location provided the opportunity to gather data for a single environment over a range of distances. Due to the range of distances, the capabilities of both the omni-directional and Yagi antenna were explored. Comprehensive testing was conducted using the omni-directional antenna; this includes data from both the automatically selected settings as well as manually selecting the MCS and GI values. A reduced dataset was obtained using the Yagi antenna with the testing relying on the automatic setting selection of the devices.

Figure 6 and

Table 3. Summary of data gathered from Woody Point using an omni-directional antenna.

	1 MHz					2 MHz					4 MHz					8 MHz
Distance (m)	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate
100	7	S	−57	0	2640	7	S	−51	0	5551	5	S	−55	0	7030	3	S	−55	0	10,702
500	6	S	−65	0	2265	4	S	−61	0	3352	2	S	−60	0	3072	1	S	−62	0	2178
900	4	S	−76	0	1448	3	S	−66	0	1952
1500	2	S	−73	0	732	2	L	−75	10	1178
2500	2	S	−86	0	756	1	S	−74	0	978
3000	1	L	−79	0	331	2	L	−80	0	628

and

Table 4. Summary of data gathered from Woody Point using a Yagi antenna.

	1 MHz					2 MHz					4 MHz					8 MHz
Distance (m)	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate
100						7	S	−33	0	6026	2	S	−35	0	12,183	7	S	−40	0	22,981
500						5	S	−48	0	6073	2	S	−47	0	12,008	2	S	−53	0	22,497
900						5	S	−57	0	5294	3	L	−55	0	9706	4	S	−62	0	18,941
1500						4	S	−62	0	4420	6	L	−60	0	6872	4	S	−65	0	16,432
1900						6	L	−67	0	3026	4	S	−70	0	3732	3	S	−72	0	9696
3000						6	L	−62	0	4058	3	S	−63	0	5945	3	L	−71	0	10,151
4000	7	S	−70	0	1559	5	S	−68	0	3074	4	S	−69	0	3502	4	S	−79	0	2544
4500	5	S	−80	0	1267	4	S	−78	0	1621	2	L	−78	0	1777
5000	4	S	−81	0	1128	3	L	−78	0	1631	2	S	−80	10	1358
5500	5	L	−85	10	739	3	L	−80	10	1134
6000	3	S	−86	0	629	3	S	−82	0	488
6500	3	L	−92	0	343	2	S	−85	0	259
7000	2	S	−92	0	522	2	S	−86	0

present the data that were obtained during these experiments. A key observation from Figure 6 is the noticeable difference in range and throughput provided by the Yagi antenna over the omni-directional antenna. This is related to the approximately 20 dB improvement in signal strength. When comparing the trends of the two antennas, while the Yagi antenna provides a more protracted angle of throughput degradation, the relationship between throughput change and distance is similar.

Another observable trend relates to the curve on the throughput change for the 2, 4 and 8 MHz bandwidths. Shown at 500 m for the omni-directional antenna and 4 km for the Yagi antenna, there are distances at which a stronger and more stable connection is available using the 2 MHz bandwidth. This may be the case even if a connection is achievable using the 4 or 8 MHz bandwidths. As shown in both graphs, the throughput capability of the 4 and 8 MHz connections demonstrates a rapid decline, regardless of the antenna selected. Conversely, while the 1 and 2 MHz connections have an initial decline due to lower connection requirements, they are able to maintain a connection at lower signal strengths and at greater distances.

4.3. BuiltEnvironment: Brisbane, QLD

This location presented additional challenges compared with the previous clear line-of-site location. While there are still areas with direct line-of-sight, large urban environments present several uncontrolled sources of noise and interference. There are also many areas where line-of-sight is not available due to large obstructions in the form of multi-story buildings, with several of these structures constructed from dense materials such as solid brick, steel, and concrete. The results of these experiments are presented in Figure 7 and

Table 5. Summary of data gathered from CBD location using an omni-directional antenna.

	1 MHz					2 MHz					4 MHz					8 MHz
Distance (m)	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate
150	2	L	−81	0	453	2	S	−75	10	1111
400	7	S	−60	0	2217	5	L	−61	0	3686	3	S	−62	0	4318	2	S	−62	0	7483

.

Figure 7 presents how the varying types of environments within a city can impact wireless transmissions. In this experiment, the AP is situated on the roof of a 12 story building. At the 150 m NLoS location, experiments at the 4 MHz and 8 MHz could not be completed as the STA was unable to associate with the AP. This was due to the various obstructions and noisy environment. In contrast, when the STA was moved to the 400 m LoS experiment location across the river from the AP, the results saw significant improvement.

4.4. Forest Environment: Samford Ecological Research Facility

This location presented several challenges that were not present in any of the other selected locations. Line-of-sight after approximately 20 m was extremely limited. Signal interference in terms of additional radio noise was low in comparison to both the Woody Point and Brisbane CBD locations. The results of these experiments are presented in Figure 8, and in

Table 6. Summary of data gathered from SERF using both an omni-directional and Yagi antenna.

	1 MHz					2 MHz					4 MHz					8 MHz
Distance (m)	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate	MCS	GI	RSSI	Loss %	Bitrate
Omni-Directional Antenna
50	7	S	−59	0	1902	7	S	−47	0	4437	5	S	−58	0	5519	4	S	−56	0	10,867
100	4	S	−74	0	672	5	L	−69	0	1590	3	S	−75	30	1000
150	2	S	−88	0		1	S	−77	10	785
200	3	L	−85	0	136	3	S	−83	10	281
250	1	S	−95	50	183	1	S	−86	80
Yagi Antenna
50	7	S	−51	0	2636	7	S	−44	0	5793	6	L	−46	0	12,230	7	S	−67	0
100	7	S	−68	0	2288	7	S	−60	0	6045	7	S	−63	0	7495	7	S	−74	0
150	7	S	−79	10	788	4	L	−68	0	4152	5	S	−73	0	5345	5	S	−74	0
200	4	S	−78	0	809	7	L	−77	0	2491	5	S	−79	0	3206	0	L	−83	20
250	7	L	−89	0	924	6	L	−81	0		5	L	−85	0	2466	2	L	−87	10	24.1
300	0	S	−90	0	387	1	S	−87	0	342

.

When examining the data from this location, it is noted that there is a similar trend in the data for the omni-directional antenna when compared to the data obtained at Woody Point. The data from the omni-directional antenna show that, while the 8 MHz bandwidth connected and functioned at 50 m, it could not connect beyond that. Similarly, in relation to the 4 MHz bandwidth connection, connections could be established and utilised at 50 and 100 m. It can be observed that there is minimal difference between the 4 and 2 MHz connections in relation to throughput.

Unlike the previous experiments conducted at Woody Point, there was no significant improvement in the achievable distance through the use of the Yagi antenna. Rather, the throughput achieved using the various bandwidths was more sustained over a very similar distance with a maximum capability of 300 m. This makes antenna selection more critical for this type of environment to achieve a stable connection with higher available throughput.

It is to be noted that in this environment, while at 50 m there was some benefit from using the 4 and 8 MHz, beyond that, there was no notable throughput advantage when using either style of antenna. This finding demonstrates the presence of some application restrictions in this type of environment for Wi-Fi HaLow technology.

Due to technical limitations, it was not possible to obtain results for 8 MHz with the Yagi antenna at this location. The STA and AP were unable to maintain a link that was sufficient for iPerf to return usable results. This could potentially be attributed to antenna alignment due to a slight changes in elevation. Based on the performance of the 4 MHz and the observed trends, it could be predicted that the 8 MHz would follow a similar trend as a maximum capability.

4.5. Comparative Analysis

When comparing data gathered in the field, it was not always possible to test at exactly comparable distances due to the presence of obstructions or the topography of the environment. This section further examines the data obtained at the CBD location for comparison against environmental-related values from Woody Point and SERF. For LoS values, Figure 9a shows the CBD 400 m values compared with the 100–500 m graph lines of the Woody Point data. This graph shows that the 1, 2 and 4 MHz values are on trend, while the 8 MHz value is significantly improved at the CBD location. It is suspected that the elevation of the AP improved throughput with line-of-sight, with the elevation cancelling out the impact of the extra noise in the environment.

Figure 9b represents the NLoS environment where the CBD 150 m values are compared with values from SERF. At this distance, only the 1 and 2 MHz bandwidths could establish a connection at both locations. The obtained throughput values for the CBD closely matches values from SERF. This indicates that although one location has natural obstructions and the other is man-made, both are obstruction-rich environments. These environments yield similar results that allow them to be considered to have a similar degree of impact to signal.

5. Framework

Wi-Fi HaLow is seen as a versatile communication technology. As a member of the IEEE 802.11 standard [11], it is IP-based and capable of the same security features as the other members of the IEEE 802.11 technology family, which have been subjected to rigorous development processes. Performance evaluation testing conducted in this study demonstrated that Wi-Fi HaLow is capable of providing data throughput rates over 20 Mbps or a connection range of over 7 km, depending on the configuration.

Suitable for such a wide range of environments and applications, Wi-Fi HaLow is highly configurable with options such as MCS and GI within the software configuration options and then distance and antenna selection as part of the physical setup. This framework introduces a four-step process whereby environmental and usage factors are identified and then combined with gathered and interpreted data to generate informed recommendations for creating optimal Wi-Fi HaLow networks. The four-step process, further detailed in the remainder of this section, initially identifies various features of the operating environment along with usage requirements. The second step makes use of the environmental information to determine the degree of impact the environment will have to Wi-Fi HaLow communication. This is then matched with the appropriate capability table, which is combined with the usage application requirements to develop the final recommendations.

5.1. Framework Implementation Walkthrough

This section introduces a four-step framework for selecting the most appropriate settings and parameters to provide optimal communications for the desired use case.

5.1.1. Step 1: Identification of Operational Environment and Usage Requirement Variables

This framework makes use of input data relating to the operational environment and application requirements to develop recommendations.

Table 7. Sample environments and associated values.

Environmental Attribute	LoS			AP Elevation			Land Topography			Obstructions			Radio Interference
Degree of Impact	Good	Limited	No	Yes	Possible	No	Flat	Severe	Undulating	Natural	Man-Made	Limited	None	Limited	High
CBD		x	x	x	x		x				x				x
Bush			x			x		x	x	x			x	x
Paddock	x	x			x	x	x		x	x		x	x

‘x’ indicate the environmental properties. Colours relate to lines on Figure 10.

lists five key environmental factors that have been observed to impact Wi-Fi HaLow communication both positively and negatively. These factors are line-of-sight, access point elevation, land topography, obstructions, and radio interference. To demonstrate how this table is used, the environmental attributes of three varying environments—CBD, bush, and paddock—are provided as examples with their characteristics identified. For example, CBD locations are often characterised as having limited to no line-of-sight, with readily available access to elevated locations to mount an access point device. The topography is generally flat with a large number of man-made obstructions of varying size and shape. The increased volume of people and technology generates a high volume of radio interference.

Table 8. Sample usage types and associated values.

	Data Volume				Transmission Interval					Mobility	Urgency
	Micro	Small	Medium	High	<Hourly or on Demand	Hourly	Daily	Weekly	Monthly +
Environmental monitoring	x				x					x	x
Low resolution photos		x			x	x
Sensor reading digests (basic)		x					x	x
High resolution photos			x
Sensor reading digest (complex)			x	x			x	x	x
High resolution video streaming				x							x

‘x’ indicate the application requirements.

lists four application features that must be considered when developing a Wi-Fi HaLow topology. These features are volume, frequency, mobility of the device, and urgency.

In addition to identifying the various environmental factors that can impact communication, a number of usage or application requirements need to be considered when developing recommendations. These requirements include the volume of the data to be transmitted, along with how often it is transmitted, the priority or urgency of the data, as well as if the device is in a fixed location or if mobility is required. Table 8 lists these four requirements along with a number of options where appropriate. The table also includes a selection of possible applications as examples and their possible options. For example, when looking at the first example of environmental monitoring, this may refer to a handheld sensor that may be used on a farm. Being handheld, it will be mobile, and since the device may be switched off between uses, there is a high priority on ensuring the data are sent without need for re-transmission.

5.1.2. Step 2: Evaluation of the Degree of Impact Caused by the Operational Environment

Following the identification of the various environmental factors, it is then possible to plot this information onto a radar graph. Shown in Figure 10, the points closest to the center have the lowest degree of impact while the most outer points have the greatest impact. Figure 10 presents the environments that were presented in the previous example, with the blue line indicating that the paddock experiences the least amount of impact. The figure also shows both the CBD and bush environments, represented by the red and green lines, respectively, experiencing a high level of impact although from differing causes.

5.1.3. Step 3: Evaluation of Network Capability

This step in the framework uses the findings from the radar graph to determine how Wi-Fi HaLow will perform in the environment, as previously described. Figure 10 shows that while the bush and CBD environments differ in terms of the type of obstructions and the presence of radio interference, they both present a reasonable amount of impact to the quality of the communication available. Based on this information and that from the results of the evaluation testing, Figure 11 and Figure 12 have been developed to show the availability and likely quality of the connection available using both omni-directional and Yagi antennas in no-interference and high-interference environments, respectively. While these tables primarily represent the connection capability using the different antennas, they also show, particularly for the omni-directional antenna, that as the distance approaches the maximum limit, the MCS required rapidly decreases to values of 1 and 2. Similar to the observed difference whereby the Yagi antenna is able to maintain a stronger connection over a greater distance, the MCS value remains consistently high over most distances.

5.1.4. Step 4: Recommendation Development

When applying this information to various application requirements, as identified in Table 8, there is a direct correlation between throughput and volume. The mobility of the STA device may lead to the selection of the omni-directional antenna to allow for lateral direction movement. Frequency and urgency are values that must be considered when examining the quality of the connection. For instance, data that are not urgent and transmitted daily may connect at the maximum reach. If, however, there is an urgency value for the data, then adjusting the setup to provide a buffer would ensure a stronger connection. This adjustment may either reduce the distance or the required throughput.

6. Applied Use Cases

The objective of this paper has been to present a framework that has been developed to provide configuration recommendations for establishing optimal Wi-Fi HaLow networks. With Section 5 presenting the frame work, this section then applies the framework to three distinctly different use case scenarios. The environments include a CBD building site, a forest and the agricultural setting of a paddock. The applications are high-resolution photography, high-resolution video streaming and environmental sensor data, respectively. The remainder of this section will introduce the use case in a use case statement and then proceed to work through the steps of the framework to produce the configuration recommendations.

6.1. Use Case 1

6.1.1. Use Case Statement

Use case 1 is a situation where high-resolution photos are taken on an hourly basis for a time lapse archive of a construction site. With the AP located at the building site, it is preferred to be able to locate the camera at a minimum of 500 m from the site. This range allows for a wider view from the camera, thus providing greater context and enabling the use of a single camera. The environment is of flat ground with clear LoS between the AP and STA devices. The STA device is mounted at approximately 3 m with the opportunity to have the AP at a similar or greater height. The size of the image files is approximately 6 MB with an ideal transmission speed of 3 Mbps preferred.

6.1.2. Framework Application

1.

The various requirements are classified into their respective environmental impact and application requirement elements, as shown in

Table 9. Use case 1: Identified environmental variables.

Environmental Attribute	LoS			AP Elevation			Land Topography			Obstructions			Radio Interference
Degree of Impact	Good	Limited	No	Yes	Possible	No	Flat	Severe	Undulating	Natural	Man-Made	Limited	None	Limited	High
CBD	x			x	x		x							x

and

Table 10. Use case 1: Application requirements.

	Data Volume				Transmission Interval					Mobility	Urgency
	Micro	Small	Medium	High	<Hourly or on Demand	Hourly	Daily	Weekly	Monthly +
High-res photos			x	x		x

.

2.

Environmental elements are then transferred to a radar graph to determine the overall degree of impact for this use case. Figure 13 shows a low degree of environmental impact.

3.

Based on the degree of impact established in the previous step, it is possible to identify the connection capability based on the environment type. As the graph for this use case indicates a low degree of impact, then the ‘no interference’ capability chart (Figure 11) can be applied to this use case. This chart demonstrates good capability with the omni-directional antenna and excellent capability with the Yagi antenna.

4.

This final step in the framework is to develop and present the recommendations. In this step, the application requirements are applied to the application capability chart and the recommendations are formulated as follows.

Based on the requirements specified, Wi-Fi HaLow is able to support this application. Using an omni-directional antenna, the required throughput is able to be met at the minimum distance. Providing additional height to the AP will likely enhance the available throughput. Based on the likely connection quality, an MCS value of 5 to 3 will provide the most stable connection. An additional range between the AP and STA can be achieved through the use of a directional, i.e., Yagi, antenna as they provide a more focused, higher gain signal. The use of a Yagi antenna will provide a range of up to 4 km with an MCS value of 7 while supporting the required throughput.

6.2. Use Case 2

Use case 2 presents a scenario with challenging requirements, where application requirements are close to or exceed the capability of Wi-Fi HaLow. In such a situation, it may be possible to provide alternative options in terms of reducing requirements such as distance or throughput requirements.

6.2.1. Use Case Statement

Use case 2 represents the application of streaming high-resolution video. This activity is to be conducted in a forested environment for the purpose of observing and recording the activity of local fauna. As it is in a forest, there is minimal to no LoS availability with a range of natural obstructions. The topography is flat with the possibility of mounting the STA device and/or antenna to a tree to provide elevation. According to a range of sources including [34] to provide adequate bandwidth to transmit 1080p video, using a standard H. 264 compression with a frame rate of 30 frames per second, the connection needs to be approximately 4 or 5 Mbps (megabits per second).

6.2.2. Framework Application

1.

The various requirements are classified into their respective environmental impact and application requirement elements, as shown in

Table 11. Use case 2: Identified environmental variables.

Environmental Attribute	LoS			AP Elevation			Land Topography			Obstructions			Radio Interference
Degree of Impact	Good	Limited	No	Yes	Possible	No	Flat	Severe	Undulating	Natural	Man-Made	Limited	None	Limited	High
Forest		x	x		x		x			x			x

and

Table 12. Use case 2: Application requirements.

	Data Volume				Transmission Interval					Mobility	Urgency
	Micro	Small	Medium	High	<Hourly or on Demand	Hourly	Daily	Weekly	Monthly +
High-res video				x	x						x

.

2.

Environmental elements are then transferred to a radar graph to determine the overall degree of impact for this use case, as shown in Figure 14. This graph shows a high degree of environmental impact.

3.

As the previous step indicated a high degree of interference, the high interference capability chart shown in Figure 12 provides the appropriate capability data. This capability chart demonstrates the connection capability for both the omni-directional and Yagi antennas. As well as showing where connection is available, it also shows the strength of the connection.

4.

The application requirements as well as the initial use case statement is applied to this information to derive setup recommendations.

This application provides a number of challenges for Wi-Fi HaLow. In a forested environment with limited to no LoS, the capability of radio transmissions is greatly reduced. To meet the specified transmission requirements, the connection range is restricted to 50 m with the use of an omni-directional antenna and up to 150 with the use of a Yagi antenna and 200 m if the video resolution is reduced. Within the range of 50 m for the omni-directional antenna and 150 m for the Yagi antenna, an MCS value of 7 would be supported. Beyond that range for the Yagi antenna, the MCS value drops rapidly.

6.3. Use Case 3

6.3.1. Use Case Statement

IoT is increasingly being adopted into the agricultural sphere with the development of smart agricultural systems. Use case 3 represents one such application, which is the deployment of environmental sensors into a paddock. These sensors generate approximately 300 bytes of data to be transmitted half hourly. As these are deployed in a paddock, there is clear LoS between the STA and AP with flat land. While reliability and integrity of the data being transmitted is of high importance, the priority is on maximising the distance between the sensor and the access point. Additionally, the deployment of a mobile sensor is to be investigated to enable mobile testing with the results being immediately transmitted.

6.3.2. Framework Application

1.

The various requirements are identified into their respective environmental impact and application requirement elements as shown in

Table 13. Use case 3: Identified environmental variables.

Environmental Attribute	LoS			AP Elevation			Land Topography			Obstructions			Radio Interference
Degree of Impact	Good	Limited	No	Yes	Possible	No	Flat	Severe	Undulating	Natural	Man-Made	Limited	None	Limited	High
Paddock	x				x		x			x		x	x

and

Table 14. Use case 3: Application requirements.

	Data Volume				Transmission Interval					Mobility	Urgency
	Micro	Small	Medium	High	<Hourly or on Demand	Hourly	Daily	Weekly	Monthly +
Sensor data	x				x						x
Mobile Sensor	x				x					x	x

.

2.

Environmental elements are then transferred to a radar graph to determine the overall degree of impact for this use case as shown in Figure 15. This graph shows a low degree of environmental impact.

3.

As the degree of impact graph from the previous step indicates a low level of environmental interference, the capability table shown in Figure 11 is the appropriate option for this use case scenario.

4.

The application requirements as well as the initial use case statement is applied to this information to derive setup recommendations.

Wi-Fi HaLow is extremely well suited to this style of application. Using the lowest bandwidth option of 1 MHz, the data will be successfully transmitted up to 2 km using the omni-directional antenna and up to 5 km using the Yagi antenna. When applied to the use case, the fixed sensor location will be able to communicate effectively up to 5 km when using a Yagi antenna and the mobile sensor will be able to communicate effectively up to 2 km from the access point.

7. Discussion

This research has produced two areas of findings to be discussed: first, the results of the initial performance evaluation, and second, the findings from the application of the developed framework.

7.1. Performance Results

Performance evaluation testing was conducted as part of this study to gather data from actual devices in real-world environments. The testing was conducted in a range of locations, including an open area with long-range LoS, a forested environment with very limited LoS, and a built environment which provided a combination of both LoS and NLoS. The testing also occurred at a range of distances at each location, utilised two antenna types and explored the impact of manually adjusting the MCS and GI values.

Initial testing within the laboratory environment (Section 4.1) achieved throughput values of 2.7 Mbps, 6 Mbps, 12 Mbps and 22 Mbps for 1, 2, 4 and 8 MHz channel width connections, respectively. These values were almost identical when using both a cable connecting the antenna points as well as the standard omni-directional antenna. This test provides a pure value of the device capability. These values also provide important reference points when examining the impact that distance alone or distance with obstructions and other environmental factors has on the transmission capability.

The examination of the data presented in Section 4.2, which were gathered at the long-range LoS location, showed a clear distinction in the throughput trends for the 4 and 8 MHz channels with connections. In this instance, the throughput deteriorates rapidly as distance increases. This contrasts with the 2 MHz and more, as the 1 MHz channel width connections show a significantly more sustained throughput capability, up to a distance of 3 km. This 3 km range is a vast improvement over the standard requirements and generally accepted range of 1 km.

While the data presented in Section 4.2 were obtained from a clear LoS location, Section 4.4 presents the results of data gathered in a forested location with a maximum LoS of approximately 20 m. As expected, in a location heavy with obstructions, the maximum connection distance was significantly reduced at 300 m. This distance was only available using the narrow channel widths of 1 and 2 MHz.

QUT’s Gardens Point campus was then selected as a location that represents a CBD environment. This location provided LoS and NLoS testing capacity with the ability to mount the AP on the roof of a 13-storey building. This provided significant elevation that is available in many CBD-type environments. The elevation provided some improvement with the 1 and 2 MHz channel width connections a little higher than the trend observed at both the LoS and NLoS locations. Using the 4 and 8 MHz channel widths only provided a connection at the LoS test location. At this location, the 8 MHz connection saw significant improvement over the expected value. This provides some insight into the benefit of elevation for the AP.

These performance testing results have provided real-world data into how various aspects such as environment, distance, obstructions and elevation can have on the capability of Wi-Fi HaLow.

7.2. Framework Application Results

Following the development of the framework for recommendations, it was then applied to three unique use cases. These use cases explored a range of environments and applications. As seen both in the literature and in the examination of the testing results, Wi-Fi HaLow is a highly versatile wireless network protocol. This statement is strengthened when examining the application of Wi-Fi HaLow over the use cases.

Use cases 1 and 2, while vastly different in terms of requirements, both align well with Wi-Fi HaLow’s capabilities of supporting high throughput over a medium range, or lower throughput over a longer range. Use case 2 was specifically designed to present requirements that were outside of the capabilities of Wi-Fi HaLow. In this instance, the application requirements included a higher throughput capability than that which is available at the distance specified. To address this, the recommendations provided options to either modify the data load through a reduction in image quality or to reduce the transmission distance to support the throughput.

8. Conclusions

This research study addressed the question of “How can Wi-Fi HaLow be optimised to support various applications in varying environments?” The answer to this question was formulated through a multistep process that culminated in the development of a framework for developing configuration recommendations for Wi-Fi HaLow networks.

The initial step saw a wide range of performance testing carried out in a variety of locations. This evaluation testing demonstrated that Wi-Fi HaLow was able to establish a low data rate connection at 3.5 and 7 km using the omni-directional and directional antennas, respectively. The data gathered were then able to demonstrate the capabilities of Wi-Fi HaLow and also many of the environmental factors that impact the connection quality and throughput capabilities.

An analysis of the data informed the development of the framework for formulating optimisation recommendations. The framework takes in a number of variables that relate to the operating environment as well as application requirements, providing recommendations for setup and configuration values to ensure optimal connections.

Following the development of the framework, it was then applied to three unique use case examples. These use cases provided strong examples of Wi-Fi HaLow’s versatility in being able to provide a strong throughput rate over a short distance or support a longer distance with a lower throughput rate. This framework is also able to highlight alternative options if the required application is not available in the specified operating environment.

This work strengthens Wi-Fi HaLow’s position within the group of low-power, long-range connection technologies for IoT.

8.1. Limitations

Due to the nature of conducting real-world data gathering activities, a number of limitations were encountered. They are the following:

• This study was limited to exploring how variables such as environment, distance and configuration settings of MCS and GI can impact the capability of Wi-Fi HaLow.
• Another limitation that occurred during the data collection was that distance was limited to 7 km for the range testing as this was the maximum distance available at the testing location.
• This study involved limited communication between a pair of devices, with one acting as the AP and one as the STA device. While Wi-Fi HaLow has mesh capabilities, it was not feasible to explore it in this work.

8.2. Future Work

Wi-Fi HaLow is an emerging wireless communication technology. This presents potential for a number of future work directions, especially when focusing on real-world exploration. These include the following:

• The implementation and evaluation of a mesh topology, especially with a focus on extending coverage in more challenging environments.
• Incorporating additional Wi-Fi HaLow STA devices. This evaluation would provide data to understand the real impact of additional load on the AP as well as the potential impact from interference.
• Using the existing performance testing methodology, future work could explore additional locations where it is possible to explore greater distances and a larger range of environmental conditions. This could also be extended to run the testing over a longer period of time, potentially enriching the data.