Distributed Sensing and Communications use cases and categorization include sensors tightly integrated with communications to support autonomous systems. Use cases within the Distributed Sensing and Communications category describe a future state of the world with ubiquitous connectivity facilitated by TN and NTN connectivity services that unlock massive, creative, and value-driving sensor and data collection opportunities. These use cases address markets such as health care, agriculture, and environmental/ public safety markets with ideas such as implantable sensors, fully remote sensors, and ultrawideband video collection systems. Summarizing greatly, requirements of this future state include wide-area coverage with options such as massive throughput and ultra-low power operating modes from network providers and device manufacturers. These use cases look toward consumers to support industry with demand and government to empower industry through proper regulation.
1-1 Use Case – Remote Data Collection
1.1.1 Description
The recent launch of LEO satellites in pursuit of ubiquitous internet coverage rekindled interests in the IoT in rural areas. LEO satellite networks are expected to provide the fast connections, global coverage, and other services that the current TN networks cannot adequately provide for rural IoT services. NTN is an umbrella term for any network with base stations on non-terrestrial flying objects such as HAPs (e.g., balloons), UAVs, and satellites. To support IoT coverage in rural areas, NTNs are comprised of diverse connectivity links and can supplement inadequate rural coverage with TN infrastructure as shown in Figure 1.1-1.
This use case leverages interworked satellite-6G networks to provide global, ubiquitous mobile internet coverage for all kinds of devices. To better interwork with the terrestrial 6G network, the satellite segment needs to address and support the same functional aspects supported by the 6G system (e.g., interfaces, QoS, security)
1.1.2 Business Opportunity and Mapping to 6G Audacious Goals
The economic stake of IoT in the future world remains very high as these technologies find new application areas in health care, smart manufacturing, education, and, in particular, logistic tracking systems. With that said, business opportunities for remote-area data collection primarily reside in two realms: IoT communication using control systems based on LEO solutions and edge AI software targeted to enrich the IoT services.
The 2016 Market Watch valued the IoT devices market at USD 32 billion and forecasts that it will reach USD 158 billion in 2024. The global IoT devices market is expected to have a CAGR of 23% between 2017 and 2024. In addition, Northern Sky Research (NSR)39 expects the satellite IoT (S-IoT) market will include more than 5.3 million terminals by 2024 and have USD 495 million in revenue by 2024. Notably, increased adoption of cloud platforms across developing regions drives growth of the IoT devices market. Although cloud platforms provide advanced analytics and monitoring for IoT services, expensive cloud solutions create support challenges in remote areas. This presents growth opportunities for LEO adoption in IoT with edge computing as a cost-effective alternative.
Similar to other 6G use cases, the edge AI software development business is booming and has formed a sizable market. Edge AI provides faster, more reliable, more economical, and easier access to critical operations data, particularly at remote complex sites such as natural disaster areas. Satellite densification brings new problems and calls for complex solutions for on-the-fly AI/ML optimization approaches. The challenges include interference management, resource allocation, path selection, and adaptivity at different layers of the protocol stack40. For instance, in a complex mega-LEO system such as Starlink, characterized by a mesh network of inter-satellite links (ISLs) in space, an AI/ML scheme could be adopted to adjust routing paths using ISLs based on the link status. The routing in a 3D system with multiple layers (also involving UAVs/ HAPs) would be even more complex. Moreover, AI/ML can help maximize the number of users served under certain co-channel interference, mobility conditions, energy consumption levels, and link dynamics. AI/ML predictions can optimize handover decisions within layers and among layers of the 3D NTN architecture.
1.1.3 Business Opportunity and Mapping to 6G Audacious Goals
The remote data collection will operate in various environments requiring remote data gathering or teleoperations such as:
> Disaster relief mission in rural areas. This includes disaster prevention (e.g., forest fire prevention monitoring) and long-term monitoring of the land (e.g., debris flow monitoring).
> Remote exploration using sensor networks and Internet of Senses. In particular, logistics tracking in a remote area.
> Smart infrastructure such as IoT sensor networks and automation.
From a remote data gathering perspective, to act responsibly by taking timely actions and maintaining reliable operation for remote area data collection, two features need to be incorporated in LEO networks:
> Radio resource management (RRM) support: efficient RRM support of different traffic such as multimedia traffic (with eMBB) and IoT traffic (through mMTC).
> Routing support: perform routing at the nearest gateway in NTN systems, where the TN is used to connect to the destination.
In this scenario, multiple sensors produce large volumes of data, which are accumulated by entities in the NTN, to perform prescriptive and predictive analytics for real-time logistics tracking in remote areas as shown in Figure 1.1-2. In a LEO communication network, identification and sensing technologies enable integrated logistics such as a study in the harbor environment provides an overview for the operator to take action in a timely manner. The IoT network passes the information gathered to the data operator’s data center and Goals Remarks Cost Efficient Solutions Extreme low cost – Utilize AI and LEO infrastructure to provide low cost, especially for remote areas. Distributed Cloud and Communications Systems Extreme massive connectivity – Support for high density of IoT sensor networks covering special services such as logistics. Sustainability Extreme coverage – Orchestrate communications-computing-control localization among NTN resources to achieve extreme coverage. 24 also communicates through the overlayed LEO network. This requires coordinated action, especially in remote areas with extreme MTC connectivity and coverage challenges.
1.1.4 Requirements
Three requirements are derived from this use case:
> Extreme Massive Machine-Type Communications (mMTC) support: extreme massive use of sensors is considered for IoT applications (e.g., monitoring remote areas).
> Enhanced Mobile Broadband (eMBB): users in remote areas or disaster areas.
> Extreme Coverage: users in remote areas should have coverage.
1.1.5 Study Areas
The following topics can be studied to help improve the use case:
> Digital World Experience.
> IoT networks; tactile internet.
> Intelligent resource management.
> LEO, HAPs, UAVs.
> Agile/lean protocol stack; edge and cloud for intelligent systems.
1.2 Use Case – Untethered Wearables and Implants
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1.2.1 Description
This use case presents the concept of truly independent untethered wearables and implants with native 6G cellular connectivity. Advances in low-power 6G communications and chipsets shall enable cellular-based, low-power sensor systems and disrupt alternative, non-6G connectivity technologies such as Bluetooth, LoRa, Wi-Fi, or similar. Increased device connection density will further expand network demands and require additional network features such as energy harvesting and wireless charging
1.2.2 Business Opportunity and Mapping to 6G Audacious Goals
The number of cellular-connected devices will continue to grow exponentially as population increases, life expectancy lengthens, and cellular services advance. In 2018, there were an estimated 8 billion IoT connected devices in the world. In 2025, that number is expected to reach 31 billion or over 200% growth43. During that same period, the population grew from approximately 7.5 billion to approximately 8.2 billion, meaning that device-based service growth significantly outpaces human growth. In 2018, there were roughly three IoT devices per human, whereas in 2025, four are expected. The networks connected to these services simply need to keep up with that demand.
In the future, cellular device connectivity will benefit from the same advances that other connectivity technologies enable. Bluetooth, LoRa, Wi-Fi, and similar technologies capture a large share of the IoT device market because of their lowpower characteristics. But devices designed with these types of technology lack native cloud connectivity, which ultimately shifts the total cost of ownership from the sensing device to an accompanying radio or similar connectivity function. For network providers, the return on investment largely depends on the industry’s ability to reduce the size, weight, and power of cellular connectivity. Specifically, new low-power chipsets and low-power features within communications protocols built upon NB-IoT and CAT-M1 are required to enable cellular users to truly cut the cord from local cloud connectivity devices.
Attaining this future requires cellular devices and connectivity to improve baseline SWaP performance. In 2022, the two most widely used technologies are Wi-Fi (5.5 billion) and Bluetooth/Zigbee/similar (5.3 billion)44, and each far surpass cellular on power performance. Notwithstanding, with cellular as a minority technology in a much broader market presents a unique opportunity to increase market share in the upcoming years.
Connectivity Type
1.2.3 Study Areas
The following topics can be studied to help improve this use case: > Current and future power-draw levels of cellular devices when compared to competing technologies.
> Connectivity limitations in service areas.
> Deep understanding of competitive low-power/lowbandwidth interfaces to ensure feature parity with future offerings within this class.
> Study into RF, wireless charging, and energy harvesting.
1.3 Use Case – Eliminating the North American Digital Divide
1.3.1 Description
The term “digital divide” describes the gap between those benefiting from adequate broadband internet access and those suffering without it. The quality (e.g., speed) of the access accounts for the largest “gap” in broadband internet access. The FCC’s current speed benchmark is 25 Mbps download and 3 Mbps upload, which defines “advanced telecommunications capability.” Another contributing factor to this gap is availability of the access (e.g., percentages of urban, rural, and tribal areas with (fixed terrestrial) access to advanced telecommunications capability). The metric used to characterize the gap is if there are multiple providers offering competition and consumer choice. Lastly, “adoption” refers to the extent to which an individual uses fixed broadband45. While several programs target mobile broadband demands, the basic definition and scoping of the “digital divide” has longer roots in fixed and TNs.
Obvious digital inequality exists in several ways, including communities living in urban areas and those living in rural settlements, varying socioeconomic groups, varying economically developed countries, and varying education levels. Individuals with access to a broadband connection are also digitally split due to low-performance computers, limited broadband speeds, and limited access to subscriptionbased content.
Unfortunately, the term “adequate” fails to properly mandate a measure of success. This description does not require coverage in every household or at public facilities (e.g., schools and libraries). The Congressional report acknowledges that differing technologies vary in their ability to meet the benchmark metrics of their advanced telecommunications capability. Technical aspects of “adequate…access” include, but are not limited to, quality and capacity of existing infrastructure, broadband deployments, and capacity to support massive numbers of devices.
This use case focuses on an under-represented portion of the population: people living with physical disabilities who need hardware and software tools/aids for their independent access and use of the internet. These individuals may face additional technical challenges to access and use the internet due to the affordability of devices/tools/aids needed. This submission uses the term “universal access” to mean access to all consumers, regardless of physical abilities.
There are also non-technical aspects such as digital literacy and the development of digital skills to consider. Aspects may have both technical and non-technical components such as building trust and overcoming apprehension for digital economies (e.g., e-commerce, online banking, or telehealth). Affordability for devices and access also contributes to the digital divide. Non-subsidized costs for mainstream (e.g., smartphones) may be onerous to those individuals with limited income. The cost of specialized devices for those with disabilities is not a mainstream discussion point of this issue.
1.3.1 Business Opportunity and Mapping to 6G Audacious Goals
Network equipment and integration providers will grow topline revenue by expanding offers to underserved communities. This unaddressed portion of the connectivity TAM enables basic services for those in need while also expanding the footprint of high-speed coverage to enable new applications discussed in this report. Specifically, with a properly installed communication backbone, other data producers will leverage those channels and serve these communities with secondary gains. For example, the figure below shows the percentage of U.S. adults currently underserved but within the addressable market.
Providers shall expect additional revenue opportunities from these market segments in a post-pandemic world. Remote and hybrid work, education, and socialization are here to stay. But network providers cannot capture that market segment without offering ubiquitous coverage. The pandemic brought forward new ways to work, live, and play, yet customers remain underserved in many areas of the world. Specifically, some use cases presented in this report have been flagged as subject to the digital divide as shown in the table below.
Finally, as public/private partnerships emerge as a method for private companies to finance public entities, each and every public school, library, and service center should have “brought to you by” network connectivity to empower those in need and potentially capture loyalty coupled to purchased services. Summarizing greatly, the total population of schools and libraries in U.S. and Canada represents this total addressable market segment.
Note that in a future state with ubiquitous coverage, there will still be a portion of the U.S. population that will struggle with basic internet access due to physical limitations. With great advances in AI/ML, only high-speed, low-latency telecommunications channels manage services to ease internet access. Channels’ uses include inferencing, command and control, and management upgrades.
Mapping to 6G Audacious Goals:
1.4.3 Example Service Scenario
Business opportunities and services:
> Enhanced multimedia communication support for first responders.
> Wide-area monitoring, including urban and rural areas.
> Infrastructure monitoring.
> Natural resource monitoring.
> Parking, traffic, and public safety services.
1.4.4 Requirements
Public safety use cases require the following:
> The ability to stream ultra-high resolution and frame-rate video from urban and rural areas at acceptable costs.
> Course-change detection for potentially immobile assets (e.g., bridges).
> Detection and reporting of adverse weather conditions (e.g., tornado, fire, storms).
> Support for customized use cases required by providers of the smart city.
1.4.5 Study Areas
This paper would benefit from additional research into the following:
> Expected bandwidth requirements for 8K, 12K, 16K, and higher sensor resolution with frame rates up to 800 fps (assuming 60% motion). > Requirements for new technologies like LIDAR and point cloud streaming.
> Potential network advances to breakdown silos within the public sector.
> Understanding privacy concerns and proper technology to facilitate secure collaboration between entities.
1.5 Use Case – Synchronous Data Channels
1.5.1 Description
With the introduction of massive numbers of IoT sensors, data collection will continue to grow exponentially. Accurate data is critical for powering 6G applications and services, as well as timing and synchronization of data challenges with accuracy. It is expected that the massive amounts of data generated by increased sensors, AL/ML, and the metaverse will require accurate transport to deliver this data on time with full synchronization.
In 3GPP 5G Release 1653, network providers introduce capabilities to ensure synchronicity of cloud disseminated instruction for edge devices. This is particularly applicable to Industry 4.0, but drivers of other use cases demand timesensitive sensor devices. For example, the introduction of massive amounts of AI-enabled sensors, such as computervision-enabled cameras or NLP-enabled acoustic devices, create edge-based data insights. However, visualization of metadata concurrently with video or audio channels remains the implementer’s responsibility. It’s time for the network to facilitate a guaranteed time of arrival for all data producers, as shown in Figure 5.5-1. By specifying channels providing tightly synchronized data, edge and cloud applications shall focus on value driving applications including:
> Collaborative content manipulation.
> Lower power game play.
> Fully synchronous metaverse.
The high-level requirements establish capabilities for communications sessions enabling data publishing aligned to GPS/NTP time synchronization (e.g., 1PPS or similarly aligned subsample) to service data fusion algorithms and systems with extreme time sensitivity. A channel can be fully synchronous (e.g., hardware timed alignment via PLL) or synchronous emulation (e.g., edge resampled) to enable legacy hardware and deficient platforms to emulate compliance to the new requirement, as shown in Figure 1.5-2. Recipients of data on this channel receive data with a guaranteed epoch alignment without using error checking or correction mechanisms. The figure below shows a hardware pseudo-diagram for this use case
1.5.2 Business Opportunity and Mapping to 6G Audacious Goals
Network and service providers offering the lowest jitter and highest synchronicity will capture more of the sensor data collection market by establishing a competitive advantage over other providers. Creators and implementers of the metaverse, AI/ML applications, and other sensor fusion applications want data as fast, but also as accurately, as possible. When selecting between components of a system, designers understand opportunity costs associated with network stacks providing varying data quality levels.
Additionally, mandating well quantified jitter and synchronicity requirements will remove synchronizing steps taken on nearly every computing platform. Many methods and tools exist within software frameworks like Matlab, MathWorks, Octave, and embedded frameworks like Python, C/C++ to compensate for errors in poorly delivered data series. In consideration of these methods and the near 20 billion IoT devices around the world, the expectation of energy savings in data centers, remotely power devices, and grid connected equipment is very high.
Mapping to 6G Audacious Goals:
1.5.3 Example Service Scenario
Business opportunities and services needed:
> Automobiles, including autonomous vehicles.
> Human body sensors (wearables and CV-deduced synchronization).
> ML, data fusion, data insights.
