Fundamentals and Key Technologies of LoRaWAN

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The Relationship Between LPWAN and LoRaWAN

LPWAN, or Low Power Wide Area Network, refers to a type of wireless network that emphasizes low power consumption and long range, typically used for networking battery-powered sensor nodes. Due to its low power and low-speed characteristics, this network is distinctly different from other wireless networks used for commercial and personal data sharing (such as WiFi, Bluetooth, etc.).

In applications, LPWAN can be configured into a private network using concentrators or can connect to public networks via gateways.

Because LPWAN and LoRaWAN have similar names, and due to the recent hype around LoRaWAN in the IoT field, many people confuse these two concepts. In fact, LoRaWAN is just one type of LPWAN, and there are several similar technologies competing with LoRaWAN.

Figure 1 Comparison of LPWAN with Other Wireless Networks

In summary, LPWAN has the following characteristics:

Two-way communication with acknowledgment

Star topology (generally does not use repeaters or mesh networking for simplicity)

Low data rate

Low cost

Very long battery life

Long communication range

Applications suitable for LPWAN:

IoT, M2M

Industrial automation

Low-power applications

Battery-powered sensors

Smart cities, smart agriculture, meter reading, streetlight control, etc.

The Relationship Between LoRaWAN and LoRa

Due to the similar names, many people confuse the concepts of LoRaWAN and LoRa. In fact, LoRaWAN refers to the MAC layer networking protocol, while LoRa is merely a physical layer protocol. Although existing LoRaWAN networks primarily use LoRa as the physical layer, the LoRaWAN protocol also states that GFSK can be used as the physical layer in certain frequency bands. From a network layering perspective, LoRaWAN can utilize any physical layer protocol, and LoRa can also serve as the physical layer for other networking technologies. In fact, several technologies competing with LoRaWAN also adopt LoRa at the physical layer.

Figure 2 LoRaWAN Network Layering (The physical layer uses LoRa, but note that the physical layer and MAC layer are independent; regarding the wireless frequency band, the ISM band is used in the figure, but technically any frequency band can be used)

Main Competing Technologies of LoRaWAN

There are multiple LPWAN technologies in the market that also use LoRa as the physical layer, such as AISenz Inc.’s aiCast. aiCast supports unicast, multicast, and broadcast, making it more complex and comprehensive than LoRaWAN. Many applications that are not feasible under LoRaWAN can therefore be realized.

Sigfox uses a slow BPSK rate (300bps), and there are some promising application cases.

NB-IoT (Narrow Band-IoT) is an IoT network based on existing mobile communication technology in the telecommunications industry. Its characteristics include using existing cellular communication hardware and frequency bands. Both telecom operators and hardware vendors are very enthusiastic about this technology.

Introduction to Key Technology LoRa

The core technology of LoRaWAN is LoRa. LoRa is a proprietary modulation technology from Semtech (acquired from CycleoSAS in 2012). To help readers unfamiliar with digital communication technology understand, we will first introduce two common modulation techniques: FSK and OOK. These two modulation methods were chosen because:

They are the simplest, most basic, and most common digital communication modulation methods.

Both are supported on Semtech’s SX127x chip along with LoRa, especially FSK, which is often used to compare performance with LoRa.

OOK

OOK stands for On-Off Keying. The core idea is to use a carrier wave to represent a binary value (generally 1, but can also represent 0 inversely), while the absence of a carrier wave represents another binary value (positive for 0, negative for 1).

Figure 3 OOK Time Domain Waveform

When switching between 0 and 1, a short empty gap without a carrier wave is also inserted, which can add some redundancy to cope with multipath delays for the receiver’s demodulation. OOK has advantages for low-power wireless applications because it only transmits about half of the carrier, allowing the carrier to be turned off to save power during the remaining time. The downside is that it has poor noise performance.

FSK

FSK stands for Frequency Shift Keying. The LoRaWAN protocol also specifies that besides LoRa, it also supports (G)FSK in certain frequency bands. The core idea of FSK is to use two different carrier frequencies to represent 1 and 0. As long as the two frequencies differ sufficiently, the receiver can demodulate using a simple filter.

Figure 4 FSK Time Domain Waveform

For the transmitter, a simple approach is to use two frequency generators, one frequency at Fmark and the other at Fspace. The output can be controlled by the baseband signal’s 1 and 0 to complete FSK modulation. However, in such implementations, the two frequency sources are usually not phase-synchronized, resulting in discontinuities when switching between 0 and 1, ultimately causing additional interference for the receiver. Actual FSK systems typically use only one frequency source, controlling the frequency source to shift when switching between 0 and 1.

GFSK adds a Gaussian window to the baseband signal before modulation, making the frequency shift smoother. The goal is to reduce the power of the sideband frequencies to lower interference with adjacent bands. The trade-off is an increase in inter-symbol interference.

The Core of CSS-LoRa

LoRa is a new modulation method that uses Chirp for spreading, which is a crucial component of all networking technologies based on LoRa technology (including LoRaWAN, aiCast, etc.). The technical name for this modulation method should be FM (Chirp). From an implementation perspective, the core technology of LoRa is the use of fractional PLL to generate stable Chirp signals.

First, let’s look at the Chirp signal (note: this term comes from the signal characteristics of the calls of the bird of the same name, which can also be referred to as frequency sweeping in signal processing). The characteristic of Chirp is that the frequency of the signal changes in a certain pattern, while the FSK signal only switches between two frequency points.

Figure 5 Linear Chirp Signal Time Domain Diagram

In the spectrum diagram, this signal appears as a line:

Figure 6 Linear Chirp Signal Spectrum Diagram

Of course, the frequency of the Chirp signal does not only change linearly; there are many other types of changes, such as exponential Chirp, logarithmic Chirp, etc. The core idea of LoRa modulation is to use this frequency change pattern to modulate the baseband signal, and the rate of change in Chirp is referred to as “Chirpness”, which Semtech’s data sheets and documents refer to as the spreading factor. The larger the spreading factor, the farther the transmission distance. The trade-off is the data rate, as longer chips are needed to represent a symbol.

Figure 7 Time Domain Signal of LoRa

Figure 8 Frequency Domain Signal of LoRa

In summary, the LoRa modulation based on frequency sweeping has several clear advantages over traditional modulation methods:

At both the receiver and transmitter, the time/frequency offset is equal. This greatly reduces the design complexity of the receiver. The frequency bandwidth of the sweeping equals the frequency domain bandwidth of the signal.

Sweeping spreading generates processing gain, allowing the receiver to demodulate signals with amplitudes lower than the noise. This significantly increases the transmission distance at the same transmission power.

Processing gain (PG) is the ratio of the bandwidth after spreading to the bandwidth before spreading. To understand processing gain, let’s use a metaphor. At a certain moment, if a radio is playing a poor signal, producing mostly noise, and you record a segment of audio at T0, defining it as Audio0 (and remember the pattern of Audio0). If the radio later plays audio similar to Audio0, it can be said that Audio0 has been received. The practical significance is that when a signal is below the noise level, the receiver can only find this signal by filtering out all the noise with a specialized filter. This is the key to LoRa’s receiving sensitivity performance; for example, FSK requires a signal-to-noise ratio (SNR) of around 10dB for stable reception, while LoRa has much lower SNR requirements:

Figure 9 Different Spreading Factors Corresponding to the Demodulation SNR of LoRa Transceiver Chip SX127X

Scalable Bandwidth

Can be used for both narrowband and wideband.

Constant Envelope/Low Power Consumption

Like FSK, it is a constant envelope modulation method, allowing for the direct use of existing FSK power amplifiers, and due to PG (processing gain), it can achieve or exceed FSK’s link budget at lower power consumption.

High Robustness

Because it uses spread spectrum modulation, a single LoRa symbol is longer than the short burst periods of typical frequency hopping communication, thus providing strong suppression of AM pulse interference, with typical out-of-channel selectivity reaching 90dB and in-channel rejection reaching 20dB. For FSK, these parameters are approximately 50dB and -6dB, respectively.

Resistance to Multipath/Fading

Because the bandwidth of a single sweeping pulse is relatively large, it is largely unaffected by multipath/fading.

Resistance to Doppler Effect

The frequency shift caused by the Doppler effect will only result in a negligible time-axis shift in the LoRa baseband signal.

Large Network Capacity

In terms of a single spreading factor, the capacity of LoRa is less than that of FSK. However, since multiple spreading factor channels are orthogonal, the overall capacity of the LoRa network equals the sum of the capacities of all spreading factor channels. For example, for a 125kHz bandwidth:

If allocated to 12 narrowband FSK channels, each channel’s equivalent baud rate is 1200, then:

Capacity_FSK = 12 * 1200 = 14400 bps

If the same bandwidth is allocated to a single LoRa channel for modulation, since all SFs are orthogonal:

Capacity_LoRa = 1 * (SF12 + SF11 + SF10 + SF9 + SF8 + SF7 + SF6)

= 1 * (293 + 537 + 976 + 1757 + 3125 + 5468 + 9375)

= 21531 bps