When American cartoonist Chester Gould drew a watch on Dick Tracy's wrist, he didn't realize that science fiction could become a reality 70 years later. As a comic strip painter, Gould imagined the future of the device without considering too much detail. Today, these very real wrist devices and other wireless wearables (WWD) give engineers a range of design details that they must overcome. Engineers must seamlessly integrate complex sensing, processing, display, and wireless technologies in affordable, eye-catching, ultra-compact designs that can operate for months, even on a single, small, and cost-effective battery, even Years. Let's discuss the specific needs for wearables, technology, and component selection, and how to implement complex functions, long battery life, and seamless wireless connectivity in ultra-small form factors.
In wearable product design, engineers must consider three key factors: power consumption in various operating modes (energy saving), proper RF design from matching circuits to antennas, and device integration in the design. We will discuss the challenges of integration in more detail, as it is difficult to discuss this factor independently without considering power consumption and RF design.
Most wireless wearable devices cover common components, including batteries, antennas, microcontrollers (MCUs), radios, and sensors. From this list, it is clear that the battery will greatly affect the functions that can be achieved and the working life of WWD. Considering that the battery power will be exhausted quickly, most WWDs do not always maintain continuous data transmission, so we usually assume that the communication is bursty and sporadic. In addition, an integrated MCU, often referred to as a wireless MCU (WMCU), is easy to use, saves board space, and reduces power consumption, so we also assume WMCUs are used in wearable designs.
Choosing the right WMCU for your application is a complex decision-making process because the high functionality of a feature-rich device will be limited by the battery's operational life. If we only focus on the peak power consumption of the WMCU, then the evaluation result is quite disappointing from the single factor of battery life. However, WWD typically operates in a variety of different power modes (EMs) and enters high power states only in rare cases. Therefore, by considering the time spent in various energy consumption modes, we can evaluate the actual life of the battery.
Silicon Labs defines five energy modes for its ARM-based EFM32 MCU: EM0 (active/running), EM1 (sleep), EM2 (deep sleep), EM3 (stop), and EM4 (off). These five modes give designers the flexibility to make decisions and optimize the overall power consumption of the system. However, being able to identify these patterns and the specification data in the data sheet does not guarantee "low power consumption in all modes" or, simply, does not ensure "energy saving". Ensuring energy savings and developing a good end-user experience is a way to build WMCUs that can run on these different modes. In fact, depending on the time interval between burst transfers, active mode EM0 may only account for a very small percentage of the overall power consumption. The time taken by the deep sleep mode EM2 can represent the maximum proportion of battery life.
When choosing the best WMCU for your application, engineers should focus on the following features, including a low-power WMCU that provides a highly integrated, well-architected architecture. Some features of the ultra-low-power WMCU need not be said, but should also be fully listed:
·Minimum operating power consumption (EM0)
· Minimum standby current (EM1 and EM2)
Microprocessor core selection, including 8-bit and 32-bit ARM Cortex (from M0+ to M4)
· Radio configuration options, including single-receipt, single-issue, transceiver, and performance levels
Other MCU features, including related architecture and integration, are equally important and require further clarification:
· Very short wake-up time
· Autonomous peripheral operation
· Autonomous inter-peripheral operation (peripheral reflection system)
·Low energy sensor interface (LESENSE)
Rich rich energy-efficient peripherals and interfaces
·RF integration
Minimum standby current and very short wake-up time
When designing a wireless wearable device that is as energy efficient as possible, one must think of all possible power optimizations. When the device wakes up, it must be as fast as possible, such as collecting and processing data as fast as possible, and then returning to sleep mode as quickly as possible. Ensuring a fast transition between sleep mode and active mode is a key element that must be considered. The impact of one processor in active mode, even if it is only 10% more than the other, has a huge impact on battery life. For example, suppose processor 1 spends 99.9% of its time in sleep mode (1μA), 0.1% of its time in active mode (10mA), while processor 2 spends 99.89% of its time in sleep mode and 0.11% of time in active mode, Then the overall current consumption of the second processor will increase by 9.1%. Interestingly, if processors 1 and 2 are in active mode for 100ms and 110ms, respectively, every 6 hours, the result highlights the importance of very low deep sleep currents. In this case, the second processor consumes only 0.44% more power than the first one. However, if the time in active mode is the same and the deep sleep current is increased from 1 μA to 1.1 μA, the current consumption will increase by 9.6%!
Autonomous peripheral operation
Depending on the functional characteristics of the wearable device, frequent or even continuous interaction or monitoring of the on-chip peripherals may be required. In this case, the CPU's need to remain active during these times will result in a significant drain on battery power. Ensuring that there is an autonomous operation on the chip that does not require CPU involvement allows the system to operate in a low-power mode while still performing very advanced tasks. These peripherals can include serial interfaces (eg, low-power UART, crystal-free USB), I/O ports (eg, external interrupts, GPIO), timers, and triggers (eg, low-power timers, low-power sensor interfaces) ), analog modules (eg ADC, LCD controller) and security (eg AES accelerator).
Operation between autonomous peripherals (peripheral reflection system)
There are also cases where communication between peripherals may be required. In these cases, a peripheral needs to be able to generate one or more events that can be immediately sensed by another on-chip peripheral. For example, a timer can be set to create an event and then trigger an ADC to start sampling. Autonomous operation between peripherals eliminates the need to wake up the CPU and ensures the lowest system power consumption. This capability is a key feature of the Silicon Labs EFM32 MCU architecture and is known as the Peripheral Reflex System.
Low energy sensor interface (LESENSE)
Eventually when the CPU needs to be woken up to perform a specific task, most MCUs are set to wake up at a specific set of times and monitor its interface, and if there is no action required, it will return to sleep mode. These periodic wake-up cycles create unnecessary battery energy consumption. The LESENSE architecture of the EFM32 MCU allows for the autonomous monitoring of analog sensors (resistive, capacitive, and inductive) and wakes up the CPU only when the relevant event or condition is met, just like other event processing. For example, LESENSE can be set to autonomously monitor a temperature sensor and only wake up the CPU through the peripheral reflection system when the programmable 99-degree Fahrenheit threshold is exceeded. Therefore, using LESENSE can minimize the CPU enable time, and when the maximum power consumption has to be consumed, the running time at the maximum power consumption is reduced as much as possible.
Rich energy-efficient peripherals
Developing a wearable device that minimizes energy consumption in all modes of operation requires careful review of the various operational aspects of the MCU. Although we have already discussed the autonomous operation of peripherals, we need to further discuss the low power requirements of the peripherals themselves. If the peripheral itself consumes a lot of power or if the clock is enabled when it is not necessary, the autonomous operation will have a very small effect.
As far as the peripheral itself is concerned, the clock management unit plays an important role in the overall power consumption of the MCU or WMCU. The clock management unit allows individual control of multiple clocks and oscillators and optimizes clock selection based on the power modes used and the peripherals enabled. Using a low-power oscillator combined with a flexible clock control scheme minimizes power consumption in the application. Energy-efficient clock management units include low-current oscillators, low startup times, dynamic system clock dividers, clock gating, and 32-kHz peripheral modules and clock prescalers.
The effectiveness of low-power autonomous UARTs is equally important for achieving ultra-low system power consumption, especially in Deep Sleep (EM2) mode, where most other peripherals and CPUs are turned off. The UART should include the necessary hardware support to minimize software intervention in asynchronous serial communications. By using a 32.768 kHz clock source, the low-power UART can support up to 9600 baud/s, and when the UART frame is received, the CPU can be quickly woken up.
The low energy timer can be used for timing and output when most of the components of the device are powered down, thus allowing the absolute minimum of system power consumption while performing simple tasks. If properly configured, this timer can provide error-free waveforms up to 16 kHz (half the 32 kHz oscillator frequency).
For analog resources in MCUs or WMCUs, such as ADCs, DACs, LCD controllers, analog comparators, and other peripherals, their power consumption and flexibility should be carefully analyzed. For example, a 12-bit 1Msps ADC can consume 350 μA at full speed, but not all applications need to run at this rate. In applications that only require 6-bit, 1ksps, the ADC consumes only 0.5uA and the power consumption is significantly reduced. The LCD controller should be able to run custom animations without any CPU intervention and only wake up the CPU when updating data.
Encryption takes up very large on-chip resources and consumes significant battery power. The lowest cost 8-bit MCUs typically require security logic to be executed as runtime code, while 32-bit MCUs most likely include an AES accelerator. When a hardware AES accelerator is available, it should be capable of autonomous operation without CPU involvement and should include DMA that supports autonomous crypto mode to minimize battery drain.
RF integration
The above discussion is mainly focused on the MCU architecture. However, other features associated with wireless transceivers should also be of concern. Wireless wearable devices may never need to receive information based on application requirements, but most devices need to transmit data at some point. Low-power amplifiers for battery-powered devices can significantly increase system power consumption and increase the size and cost of applications to meet the operational life of the system. For example, long-range communication devices may require RF output power levels of +13 dBm, 16 dBm, or even +20 dBm. Although the integration of a +10dBm RF power amplifier (PA) in a WMCU is ubiquitous, an off-chip transistor or amplifier is required if the application requires more output power. The problem is that these off-chip boosters are not useful for creating low-cost and practical solutions because the solution is both efficient and low-cost. Therefore, in applications requiring long distances and/or frequent communication, efficiency and battery life are often contradictory to achieving competitive cost targets. One way to overcome this problem is to ensure that the appropriate size of the PA is integrated into the WMCU, even up to +20 dBm. By integrating the PA in the WMCU device, the current consumption of the PA can be minimized. Thanks to the proper matching between the PA output and the booster amplifier, and the safe design of the transmit chain compensate for temperature and voltage variations, there is no loss. A fully integrated PA allows full control of PA operation, ensuring the lowest power consumption.
Many applications run in the 2.4 GHz band, in which case IC vendors have the opportunity to simplify system design by integrating matching circuits and providing single-ended RF inputs and outputs. Sub-GHz applications tend to cover a very wide frequency range, from hundreds of MHz to 1 GHz. In these cases, integrating the matching components is not realistic. However, passive devices that are typically used off-chip are integrated in WMCUs and are feasible in most popular frequency band applications due to their cost advantages for separation implementations.
Finally, what we have not discussed in wireless wearable devices is the antenna transmit and receive characteristics. Due to size and cost constraints, most wireless wearable devices typically have poor antenna emission characteristics because they typically simply print the antenna on the PCB surface material (like FR4). To compensate for antenna loss or low gain, the simplest method is to increase the RF output power to achieve the desired output power. Unfortunately, as discussed earlier, this transmitter will consume more energy than those that have been optimized for the antenna. Better design and lower matching circuit losses will be the guarantee of optimal operation, but the antenna design is extremely difficult to design, especially when considering the changing RF environment in which the wearable device is located. Mismatch fluctuations that result from being close to the end user's body (e.g., when the hand is over the device) can cause many problems. Some WMCU devices, such as Silicon Labs' Si4010 "on-chip remote" transmitter, have an integrated antenna tuning circuit that dynamically compensates for the antenna at these times. This circuit plays a very important role in not only controlling power consumption, but also ensuring that radio emissions remain within regulatory limits.
One method of compensating for poor antenna reception performance is to design the system to receive antenna diversity, that is, to use multiple antennas. While many applications will benefit from implementing antenna diversity, there are some factors to consider. First, antenna diversity tends to help those at the distance between the transmitter and the receiver: the received signal level is close to the background noise level (ie, near the edge of the link coverage), or by multipath transmission or A fading transmission environment caused by object occlusion.
To reduce power consumption and chip cost, WMCU ICs typically only integrate one receive path, so antenna diversity must be switched through an off-chip antenna switch to alternate between the two antennas. However, a scheme in which one receive path is shared by two antennas may consume more power than would be expected. Because in this case, the length of the transmitted preamble must be extended to provide sufficient time for the two antennas to be evaluated in order. To analyze and select the best antenna, it also increases the computational cost and current consumption.
Finally, there is a spacing problem. The distance between antennas in a wireless communication system is recommended to be an integer multiple or fractional multiple of the wavelength (??), and the minimum spacing is? ? ? . At 2.4 GHz, the wavelength is 125mm, depending on the minimum spacing? ? ? Or a 31.25mm split antenna design is possible in some wireless wearable devices. However, for WWD operating in the Sub-GHz band, overcoming this challenge will become extremely difficult. In the 868 MHz band, the antenna should be kept at a minimum of 86 mm spacing, which results in antenna diversity not being available in many WWD applications.
Therefore, engineers must balance the improvement in transmission distance and reception performance with increased complexity and size, computational cost, and current consumption. Assuming antenna diversity is not an issue, the increased computational cost and corresponding power consumption can be overcome. Then, in a changing and non-synchronous environment, periodic switching between antennas is also required because the radio does not know which antenna can achieve better reception before the packet arrives. Silicon Labs' EZRadioPRO transceivers have an integrated preamble quality detector to determine signal quality based on RSSI values ​​and to confirm that valid packets arrive at both antennas. The benefit of the integrated detector is that it is able to select the best antenna, offload the MCU, and thus reduce overall power consumption during the selection process.
to sum up
If Chester Gould is still alive today, he must be impressed and his imagination has been greatly exceeded. Numerous companies have introduced watch devices that far exceed Dick Tracy's wireless phone capabilities and are developing more advanced wearable devices. However, when designers try to integrate more features and functions into wireless wearables, the underlying focus is almost always the same – how to get lower power consumption, how to adapt to small form factors in the design, and how to ensure The device has reliable wireless communication. And the ultimate concern will be how to get these product design goals at the lowest possible price, but that's another topic for us... "Six-two and even, over and out."
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