The Business Case for Densifying LoRaWAN Deployments

LoRaWAN networks are deployed for coverage, and network capacity can be scaled gracefully by adding more gateways. Densifying LoRaWAN deployments and optimizing Adaptive Data Rate (ADR) and power consumption algorithms comprise a two-pronged force that yields a ~10X reduction in both power consumption and operator TCO while increasing the capacity of the network massively.

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Image of densified networks
Illustration: © IoT For All

LoRaWAN has recently emerged as one of the key radio technologies to address the challenges of Low Power Wide Area Network (LPWAN) deployments, namely power efficiency, long range, scalable deployments, and cost-effectiveness.

The LoRa Alliance has had an exponential growth with 500+ members with the recent arrival of heavyweight members such as Google, Alibaba, and Tencent joining the alliance.

The first wave of LoRaWAN was primarily focussed on large country-wide deployments led by operators such as KPN, Orange, Swisscom and many more. However, the next wave that is already coming is the arrival of private LoRaWAN deployments from large enterprises and enabling roaming for inter-connection amongst public/private networks, especially for use cases which involve LPWAN Geolocation.

As the IoT deployments grow in both the densification and geographical footprint, it’s inevitable that network design becomes one of the important factors ensuring long-term success and profitability of both operators and end-customers relying on LoRaWAN connectivity for their IoT use cases.

A typical example is the recent three million water meter contract awarded by Veolia Birdz to Orange. Such large-scale projects require careful network planning to achieve the required densification and quality of service while optimizing costs.

A Closer Look at Densification Techniques for LoRaWAN

LoRaWAN deployments use a star topology with a frequency reuse factor of one, which allows simplicity in network deployment and ongoing densification: there is no need for frequency pattern planning or reshuffling as more gateways are added to the infrastructure.

Compared to mesh technologies, the single hop to network infrastructure minimizes power consumption as nodes do not need to relay communication from other nodes. Another advantage is that gradual initial network deployment in a sparse mode with low node density is possible, compared to mesh, which requires minimum node density to operate. Even more importantly, LoRaWAN is immune from the exponential packet loss suffered by multi-hop RF mesh technologies in presence of increasing interferers and noise floor power.

Another unique feature of LoRaWAN networks is that messages in uplink can be received by any gateway (Rx macro-diversity). It’s the function of a network server to remove duplicates in uplink and select the best gateway for downlink transmission based on the uplink RSSI estimates. This allows features such as geolocation to be easily built into LoRaWAN deployments. It also enables uplink macro-diversity that significantly improves network capacity and Quality of Service (QoS).

LoRaWAN also supports features such as Adaptive Data Rate (ADR) that allows a network server dynamically to change parameters of end-devices such as transmit power, frequency, and signal spreading factor via downlink MAC commands. Optimization of these settings is key to increase the capacity and reduce the power consumption of end-devices.

The optimization of LoRaWAN parameters along with network densification can lead massive amounts of capacity increase in the network. In fact, the LoRaWAN capacity of the network can scale almost indefinitely with densification.

Designing LoRaWAN network for Dense Deployment
Image Credit: Actility

The future of LoRaWAN networks, particularly in urban environments where the noise floor is expected to get higher due to increased traffic, goes towards micro-cellular networks

How Does Densification Lead to Lower TCO for Enterprise Deployments?

As the network is densified by deploying more LoRaWAN Gateways, and adaptive data rate (ADR) and power control algorithms are applied intelligently in the network, the result is a dramatic reduction of power consumption of end-device and thus reduction in Total Cost of Ownership (TCO) of end devices.

The figures below show clearly that densification can lead to up to 10X savings in both power consumption and an overall reduction in 10-year TCO for enterprise deployment. Changing the batteries require manual labor, which is the cost that can significantly dominate 10-year TCO of large-scale enterprise deployment (e.g. smart gas or water metering use cases).

Battery Lifetime Improvement with densification
Image Credit: Actility

Densification leads to very dramatic reduction in power consumption of the end-devices thus reducing overall TCO.

Impact on 10-year TCO due to densification
Image Credit: Actility

LoRaWAN Offers Disruptive Deployment Models

LoRaWAN is generally deployed in unlicensed spectrum, which allows anyone to roll-out IoT/LPWAN networks based on LoRaWAN. This allows three deployment models:

1. Public Operator Network

In this traditional model, the operator invests in a regional or nation-wide network and sells connectivity services to its customers.

2. Private/Enterprise Network

In this model, enterprise customers typically setup LoRaWAN gateways on private premises (e.g. an airport). They either have these gateways managed by an operator or use their own LoRaWAN network platform. This second mode of deployment is a game changer for dense device use cases, as network capacity and enhanced QoS can be provided at marginally increased cost. It becomes possible because LoRaWAN runs in unlicensed spectrum, and gateways are quite inexpensive and easy to deploy.

 3. Hybrid Model

This is the most interesting model that LoRaWAN allows due to its open architecture. This isn’t possible (or rather it’s difficult) with other competing LPWA technologies or Cellular IoT. This is due to licensed spectrum and absence of roaming/peering model between private and public networks. There are initiatives like CBRS and MulteFire from 3GPP Players, but they’re still in progress and far from maturity for large scale IoT deployments—especially for use cases that demand 10-15+ years battery lifetime.

In a hybrid model, an operator provides light country-wide outdoor coverage, but different stakeholders, such as private enterprises or individuals, help in densifying the network further based on their needs on their premises via managed networks. This model enables a win-win private/public partnership in sharing the costs and revenues from the network and densify the network where the applications and devices are most present.

This model is possible because multiple gateways can receive LoRaWAN messages and network server removes duplication. In the cases in which different operators/enterprises run their networks, LoRa Alliance already has approved roaming architecture in “LoRaWAN Backend Interfaces 1.0 Specification” to enable network collaboration.

This model significantly reduces the operator investment and offers a disruptive business model to build IoT capacity where it’s most needed.

LoRaWAN Hybrid Deployment Model
Image Credit: Actility

LoRaWAN enables Public-Private deployment that allows disruptive model for cost/revenue sharing and densifying the network where it is needed most, depending on IoT application needs

LoRaWAN Densification: A Key Driver for Reducing Operator TCO

When designing and deploying a LoRaWAN network, the system operator must balance the cost of a dense network (and it’s served sensors) against the cost of a sparse network (and it’s served sensors).

Traditional vs. Opportunistic Network Designs

In the traditional deployment model, the operator deploys LoRaWAN gateways on telecom towers. This entails leasing the space from the tower owner, purchasing a waterproof outdoor gateway, climbing the tower to hang the gateway, and perhaps paying for additional power, zoning, permitting, and backhaul. The operator does the detailed RF propagation study and hangs enough gateways to provide coverage for the sensor locations required to provide the services he wants to provide.

Another option is opportunistically to deploy “femto” gateways in devices that the operator is already fielding. The gateways are stateless and thus don’t add much complexity to the hosting device. An 8-channel LoRaWAN reference design is mated to the host device using either USB or I2C. The options here are quite diverse. The operator can embed a simple 8 channel gateway into ongoing WiFi hotspots, power supplies, amplifiers, cable modems, thermostats, virtual assistants, or any mass-produced device that already has backhaul. The Bill of Materials adder is quite modest, the power consumption and heat dissipation are less than 3 Watts, and the size delta is roughly 7 cm by 3 cm.

Calculating the number of opportunistic gateways to provide adequate coverage for a given deployment can be challenging. The height of the gateways has a large impact on the coverage of the gateway. A gateway deployed in the 20th story of an apartment building has a much better coverage pattern than the same gateway deployed in the basement of a single-family home. Gateways deployed in WiFi hotspots mounted on power poles have a different coverage area than a gateway deployed on light poles. So, the actual number of gateways deployed in each scenario varies widely.

When you complete the detailed design of each network type, you typically find that an opportunistic deployment model allows the operator to cover a given area by deploying roughly 100 times as many gateways for roughly 1/10th of the cost (when compared to the traditional 3rd party leased tower model).

Water Metering: An Exemplary Use Case

For the rest of this analysis, we will assume that the operator needs to deploy a LoRaWAN network to service 100K water meters. Water meters represent a difficult RF propagation model. They are installed at or below ground level, must last 20 years, and suburban meters tend to have accumulations of grass and dirt collect over time. Let’s assume a North American deployment model, and we have the option of using a high power (27dBm) or a low power (17dBm) meter.

One possible design is to use a tower-based approach. In a tower-based approach, the operator typically ends up deploying high power water meters in order to reduce the number of (expensive) tower leases. In order to run at high power, the North American regulations require the sensor to send across 50+ channels, which drives the operator to deploy 64 channel gateways.

Let’s assume that the average distance between a water meter and a tower-based gateway is ~3km and the sensors need to send one reading per day. Many of the meters thus operate at SF10 at 27dBm. The sensor designer includes a high-power RF amplifier, calculates the energy requirements over the life of the sensor, and sizes the battery appropriately.

Another possible design is to opportunistically deploy thousands of femto gateways into the area. The question boils down to this: “How many femto gateways do I need to cover the desired area?”

Working backward from the densest possible deployment, most MSOs (Multiple-System Operators) serve 1/3 of the households in their footprint. In many urban environments, the average distance between a given operator’s subscribers is 30 meters. If such an operator could opportunistically deploy in most of those sites, they would have inter-gateway distances as small as 30 meters. For the purposes of this analysis, let’s say that the average distance between the sensor and the closest gateway is reduced from 3000 meters to 100 meters. When a sensor is 100 meters from a gateway, it can typically operate at SF7 at 17dBm (or lower). Clearly, the network designer must account for a distribution of distances between a given sensor and its closest gateway, but the overall power savings are significant.

It’s also instructive to compare the overall capacity of a tower-based LoRaWAN network to the overall capacity of the opportunistic LoRaWAN network. Remembering that 100 eight channel opportunistic gateways cost about 1/10th of a single 64 channel gateway, we realize that we get ~13 times as much network capacity for 1/10th of the cost. As the sensor density increases, we could deploy additional opportunistic gateways and get ~130 times as much network capacity for the same cost as a tower-based network.

When we compare the cost to build a sensor designed to last 20 years using SF10 at 27dBm to the cost to build a sensor designed to last 20 years using SF7 at 17dBm, we find that we can save more than $10 per sensor by deploying the denser network.

So, in addition to saving a significant amount of capital by opportunistically deploying the gateways, the operator can save more than $10 per water meter by opportunistically deploying a dense network. This saves more than $1M on the 100K water meter deployment.

When one considers additional use cases, the dense LoRaWAN network model provides sensor savings on each additional set of sensors. Most of the sensors don’t have the 20 years requirement and thus don’t save the same amount of money, but batteries are one of the primary drivers for any sensor’s cost.

Conclusion

This analysis is somewhat simplified, and a very large-scale deployment may require a certain amount of traditional gateway placement to provide an “umbrella” of coverage that is then densified using opportunistic methods. By densifying the network, the overall sensor power budget is decreased significantly. One could also envision a deployment model in which an opportunistic gateway is deployed in conjunction with a set of services. The operator would add IoT-based services to an existing bundle (let’s say voice/video/data, thermostat control or personal assistant) and know that the sensors would be co-resident with the gateway.

What Is the Future of LoRaWAN?

LoRaWAN exhibits significant capacity gains and a massive reduction in power consumption and TCO when ADR algorithms are used intelligently in the network. I showed how LoRaWAN networks are deployed for coverage and how network capacity can be scaled gracefully by adding more gateways.

There are already 16 channels in EU, but there have been recent modifications of the regulatory framework to relax the spectrum requirements and increase transmit power, duty cycle and number of channels.

Moreover, Semtech released the latest version of LoRa chipsets, with the following key features:

  •    50% less power in receive mode
  •    20% extended cell range
  •    +22 dBm transmit power
  •    A 45% reduction in size: 4mm by 4mm
  •    Global continuous frequency coverage: 150-960MHz
  •    Simplified user interface with implementation of commands
  •    New spreading factor of SF5 to support dense networks
  •    Protocol compatible with existing deployed LoRaWAN networks

The above LoRaWAN features and upcoming changes to EU regulations will allow significant scaling of unlicensed LoRaWAN deployments for years to come to meet the needs of IoT applications and use cases. LoRaWAN capacity depends indeed on the regional and morphology parameters.

As I have shown above, if the network is deployed carefully and advanced algorithms such as ADR are used, there can be a dramatic increase in network capacity and a massive reduction in TCO. This will be one of the main factors that will determine the success of LoRaWAN deployments as the demands and breadth of IoT applications scale in future.

I also showed earlier how LoRaWAN offers innovative public/private deployment model in which operators can build capacity incrementally and supplement with extra capacity by leveraging gateways deployed from private individuals/enterprises. Typically, for cellular networks, there can be anywhere from 5-10 percent IoT devices on cell-edge which are in an outage. This applies especially to deep indoor nodes (for example, smart meters with an additional 30 dB penetration loss).

Such nodes can only be covered through densification of a cellular network, which is expensive considering it’s being done only for 5-10 percent of IoT devices. One way to address this problem is deploying private LoRaWAN on cell-edge and using a multi-technology IoT platform that combines both LoRaWAN and Cellular IoT.

On the other hand, LoRaWAN offers a cost-effective way to augment network capacity where it’s needed most. LoRaWAN gateways are very cost-effective and can be deployed using Ethernet/3G/4G backhaul with minimal investment in comparison to 3GPP small cells. This allows building IoT networks in a cost-effective manner. Operators can scale those networks progressively based on the application needs. I believe that his deployment model has a dramatic effect on ROI for IoT connectivity based on LoRaWAN.

The LoRa Alliance has standardized the roaming feature, which enables multiple LoRaWAN networks to collaboratively serve IoT devices. Macro-diversity used across deployments enables operators/enterprises to jointly densify their networks, hence providing better coverage at lower costs in, for example, industrial use cases. The future of LoRaWAN as shown below will be private/enterprise network deployments and disruptive business models through roaming with the public networks.

Future of LoRaWAN deployment
Image Credit: Actility

LoRaWAN Provides horizontal connectivity solution to address wide-ranging needs for IoT applications for LPWAN deployments. However, these benefits are only possible with intelligent network server algorithms proprietary to network solution vendors