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The next generation of IOT's core node: ultra low power consumption

Source: unknown Editor: admin Time: 16:39, May 14, 2019


 

With the gradual spread of the Internet of things, people have seen more and more IOT modules in their lives: intelligent water meters, shared bicycles, etc. At present, the Internet of things is still mainly driven by operators, and the IOT module needs to use standard cellular protocol to communicate with base stations. Because the base station needs to cover as much area as possible, the IOT module needs to be able to communicate when it is far away from the base station, which has a high requirement for the RF transmission power of the IOT module; on the other hand, the IOT module still needs to consume up to 30mA current when making wireless communication, which makes the current IOT module still need to cooperate Higher capacity batteries (such as the No. 5 battery) can work, which also makes it difficult to make the size of the IOT module smaller.

 

In order to further popularize the Internet of things, we must overcome the limitation of power consumption and size. For example, if the Internet of things is to be implanted into the human body in the future, it is impossible to match it with No. 5 battery. Instead, it is necessary to use a smaller battery or even use an energy acquisition system to obtain energy from the environment and completely get rid of the limitation of batteries. In order to achieve this goal, in terms of communication protocol, we can use lower power consumption ad hoc network technology, similar to ble; while in circuit implementation, we must use innovative circuits to reduce power consumption.
 

Energy acquisition technology
 

According to the previous discussion, the current battery size and cost have become the bottleneck restricting IOT equipment from entering the potential market. So, is it possible to use energy from the environment to support the work of IOT nodes? This kind of module which obtains energy from the environment to support the work of IOT nodes is called "energy harvesting". At present, the research of energy acquisition circuit chip has become a hot research direction.

 

At present, the most mature energy acquisition system can be said to be solar cells. Traditional solar cells can provide better energy acquisition efficiency, but the cost is difficult to integrate into CMOS chips. Recently, many research institutions are using new CMOS solar cells, which can be integrated into the same chip with other modules of Internet of things nodes, greatly increasing the integration and reducing the module size. Of course, the solar cells integrated in CMOS chips need to pay the cost of low energy output. At present, the common CMOS on-chip solar cells can provide NW level power output under indoor light, and can provide UW level power output under strong light, which puts forward high requirements for the overall power consumption optimization of IOT modules. On the other hand, the energy acquisition can also be used with small-size micro batteries. When the light is good, the solar cells are used, and when the light is weak, the battery life of the whole IOT module can be improved.

 

In addition to solar cells, another well-known environmental energy is WiFi signals. At the ISSCC this year, a team from Oregon State University published a chip that gets energy from WiFi signals in the environment. First of all, background knowledge: the maximum transmitting power of WiFi is 30dBm (i.e. 1W). In simple environment (i.e. there is no occlusion, etc.), the signal power decreases with the square of the distance from the transmitting equipment, and the signal power will be reduced to about 1uw (- 30dBm) at a distance of about 3M. If there is object occlusion, the power will be smaller. In the paper published by Oregon State University, the chip can work with an antenna with a diameter of 1.5cm, which can charge the battery at very low wireless signal power (- 33dbm, i.e., 500nw), and the energy acquisition efficiency is about 5-10% (that is, the output power is about 50nw when the distance from the transmitter is 3M). Therefore, WiFi signal can also be used to provide energy for the IOT module, but its output power is not large in the real distance, and the node module is also required to do deep optimization for power consumption.

 

 

In addition, mechanical energy can also be used as the energy source of IOT nodes. Piezoelectric effect can convert mechanical energy into electrical energy, so that using piezoelectric materials (such as piezoelectric MEMS) can charge IOT nodes. A variety of materials such as piezoelectricity sensors can be used to make statistics on the amount of piezoelectric energy applied to vehicles, such as piezoelectric sensors. In this way, the mechanical pressure can be used as the signal to be measured, and it can also be used as the energy source, so there is no need to waste energy when there is no signal! The output power of piezoelectric materials varies greatly with the size of mechanical energy, which is generally in the order of magnitude of NW MW.
 

Wake up wireless system

 

Traditional IOT wireless transceiver systems often use periodic communication or active event driven communication. Periodic communication means that the IOT node periodically opens communication with the central node and sleeps at other times; event driven communication refers to that the IOT node only communicates with the central node when the sensor detects a specific event, while it sleeps at other times.

 

In both modes, IOT nodes need to actively establish connections and communicate with the central node. However, this process of establishing connections is very energy intensive. Therefore, the concept of wake-up wireless system came into being.

 

What is wake-up wireless system? The system is dormant most of the time, and only when the master node sends a specific signal, it wakes up the wireless system. In other words, the energy-consuming process of connection establishment is not completed by the IOT node, but by the central node by sending a wake-up signal.

 


 

When the events that establish the connection are driven by the central node, everything becomes simple. Firstly, the central node can transmit a radio frequency signal, and the IOT node can obtain energy from the RF signal through the energy harvesting circuit to charge the internal capacitor. When the capacitor of the IOT node is fully charged, the wireless connection system can use the energy in the capacitor to transmit RF signals to communicate with the central node. In this way, you can operate without batteries. Imagine if you use an IOT active connection instead of a wake-up wireless system, it will be difficult to have no battery, because there is no guarantee that the IOT node will have enough energy in the node when it needs to communicate. On the other hand, with wake-up system, the central node first charges the IOT node when it needs to work, which can ensure that each IOT node has enough energy to communicate.

 

So, how low is the power consumption of such a wake-up wireless system? On the ISSCC in 2016, the wake-up receiver supporting ble network published by the start-up company psikick only needs 400 NW of power for wireless communication. In 2017, the wake-up receiver published by the University of California, San Diego, achieved a power consumption of 4.5 NW, which is 4-6 orders of magnitude smaller than the traditional IOT chip which needs milliwatt level!

 


 

4.5 NW ultra low power wake-up receiver from UCSD

 

Reflection modulation system

 

The wake-up receiver mainly solves the problem of how to receive signals with low power consumption in wireless links, but if the traditional transmitter is used, it still needs to actively transmit RF signals. The transmitter is also very power consuming, and the power consumption required to transmit signals is often in the order of milliwatts. So, is it possible to make some innovations in the transmitter to reduce power consumption?

 

Indeed, some people have found a new way to transmit the information from IOT node sensors without transmitting RF signals, which is the use of transmit modulation proposed by researchers at the University of Washington. Reflection modulation is a bit like the sun signal mirror in navigation and field exploration. The sunlight signal mirror transmits information by reflecting sunlight from different angles. Here, the carrier of the signal is sunlight, but the sunlight energy is not emitted by the person who transmits the signal, but is provided by the sun as a third party. Similarly, the approach proposed by researchers at the University of Washington is the same: the central node transmits RF signals, while the output of IOT nodes changes (modulates) the transmission coefficient of the antenna, so that the central node can receive the signal of the IOT node by detecting the reflected signal. In this way, the radio frequency signal of the IOT center node is not transmitted in the whole process.

 

The research team led by Professor Shyam gollakota of the University of Washington has completed three related projects in the field of ultra-low power IOT realized by reflection modulation. Last year, they completed the passive WiFi and inter scatter projects. Passive WiFi is used for long-distance reflective communication, which uses WiFi router to transmit relatively high power RF signals, while IOT nodes modulate antenna reflection coefficient to transmit information. Multiple IOT nodes can coexist and transmit information at the same time in a way similar to CDMA spread spectrum. Interscatter is used for short distance data transmission, using mobile devices to transmit low-power RF signals, while IOT nodes modulate the reflection of the RF signals to achieve the purpose of information transmission. The power consumption of passive WiFi and interscatter chips is around 10-20 MW, which is several orders of magnitude smaller than the traditional IOT wireless chips with milliwatt starting level. At the same time, it also paves the way for the Internet of things nodes to enter the human body and other application scenarios.

 

Passive WiFi (upper) and interscatter (lower) use reflection modulation, respectively for long-distance and short-range applications.

 

Passive WiFi and inter scatter also need to use electrical signals, so they need to be powered. However, Professor gollakota's recently published printed WiFi goes a step further and does not need power at all!

 

In the application of Internet of things, many physical quantities need to be detected are not electrical signals, such as speed, liquid flow and so on. Although these physical quantities are not electrical physical quantities, but because the current mainstream signal processing and transmission are using electronic systems, so the traditional method is to use sensor electronic chips to convert these physical quantities into electrical signals, and then transmit them through wireless connection. In fact, this transformation process is not necessary, and will introduce additional energy consumption. The innovation of printed WiFi is to use mechanical system to modulate the reflection coefficient of antenna, so as to transmit these physical quantities through reflection modulation. In this way, the electronic system is completely avoided in the IOT node, so as to truly realize battery free work!

 

 

At present, these mechanical systems are made in 3D printing, which is why the project is named printed WiFi.

 

The image above is an example of a printed WiFi, a speed sensor. As long as the rotation speed of the antenna is changed below the rotation speed of the antenna, i.e. the rotation period of the antenna can be changed as long as the rotation speed of the antenna is changed. The bottom figure shows the change of the reflected signal of the sensor at different speeds in the time domain. It can be seen that the speed information can be extracted by the reflected signal.

 

Ultra low power sensor

 

The basic goal of IOT node is to provide sensing function, so ultra-low power sensor is also essential. At present, the temperature and light sensor can achieve the power consumption of NW UW after deep optimization, while the sound sensor widely used in intelligent audio often consumes MW order of magnitude or even higher power consumption, so it has become the focus of research and development in the next step.

 

In the field of sound sensor, the recent breakthrough comes from piezoelectric MEMS. The traditional sound sensor (i.e. microphone) must keep the whole system (including back-end ADC and DSP) in active standby state to avoid missing any useful sound signal. Therefore, the average power consumption is close to MW. However, in many environments, such a system actually causes a waste of energy, because most of the time there may be no sound in the environment, resulting in the energy waste of ADC, DSP and other modules. The use of piezoelectric MEMS can avoid such problems: when there is no sound signal, the piezoelectric MEMS system is in sleep state, only the front-end piezoelectric MEMS microphone is on standby, while the back-end ADC and DSP are in sleep state, and the overall power consumption is UW order of magnitude. Once the useful sound signal appears and is detected by piezoelectric MEMS, the piezoelectric MEMS microphone can output wake-up signal to wake up the ADC and DSP, which is better than the useful signal. Therefore, the average power consumption of the whole sound sensor can be controlled in UW order of magnitude in conventional application scenarios, so that the sound sensor can enter more application scenarios.

 

Ultra low power MCU
 

The last key module in the IOT node is MCU. As the core module of controlling the whole Internet of things node, the power consumption of MCU can not be ignored. How to reduce the power consumption of MCU? MCU is divided into two parts: dynamic power dissipation and static power dissipation. In the static leakage part, in order to reduce the leakage, we can reduce the power supply voltage and use the standard unit design with low leakage. In the dynamic power consumption part, we can reduce the power consumption by reducing the power supply voltage or reducing the clock frequency. It can be seen that the static leakage and dynamic power consumption can be reduced by reducing the power supply voltage. Therefore, the design of sub threshold circuit which can reduce the power supply voltage is the only way to design ultra-low power MCU. For example, reducing the power supply voltage from 1.2V to 0.5V can reduce the dynamic power consumption by nearly six times, and the static leakage current will decrease exponentially. Of course, subthreshold circuit design will involve some design process challenges, such as how to determine the delay of subthreshold gate circuit, build / hold time and so on, which need careful simulation and optimization. In academia, the University of Virginia's research team has released sensor SOC with dynamic power consumption as low as 500nw, which includes computing accelerator and wireless baseband in addition to MCU. In terms of commercialized technologies, ambiq's Apollo Series MCU can achieve ultra-low power consumption of 35ua / MHz, and its design uses spot subthreshold design technology accumulated for many years by ambiq. In the future, we can expect to see MCU with power consumption as low as NW, thus paving the way for IOT nodes using energy acquisition technology.

 

 

epilogue
 

With the development of the Internet of things, the first generation of wide area Internet of things has rapidly spread into thousands of households. However, the wide area Internet of things nodes have to meet the coverage requirements, so it is difficult to reduce the RF power consumption, which limits the application scenarios (such as human body sensors and other scenarios where large capacity batteries cannot be used). The local Internet of things will become the next step in the development of the Internet of things. The energy acquisition technology introduced in this paper, combined with ultra-low power wireless communication, MCU and sensors, is expected to break through the traditional limitations of IOT nodes, and make revolutionary breakthroughs in size and battery life, thus paving the way for the Internet of things to enter new applications such as implantable sensors.
 


 

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