The results can be seen in Figure 10, where the best pentagonal design shows a significant reduction in ripple when compared to the square device, which was the starting point for the exercise. It is important to note that each of the 3,640 designs were simulated in full 3D, a study that would take a legacy solver nearly a year to complete on the same computing resources. The results provided are indicative of the type of design improvements that can be achieved with cloud based CAE using OnScale’s solvers.
Summary
Despite the lack of standards, 5G is promising faster data rates for mobile phones and will be an enabler for autonomous vehicles and the IoT. The move from 4G to 5G represents orders of magnitude higher data rates at frequency bands beyond 3 GHz. However, legacy CAE tools are incapable of performing complete 3D design studies, which are a critical step in optimizing the design and improving the time to market for these highly complex structures. OnScale’s cloud solvers open the possibility of doing this analysis in parallel, reducing prototyping costs and speeding time to market.
Infinite Synthesized Networks Deliver RF Filter Design Tools for 5G
Bob Hammond
Resonant
Santa Barbara, Calif.
Where 4G/LTE was a single specification for high speed mobile device services, 5G is a family of technologies designed to serve different use cases ranging from ultra-broadband fixed wireless to low data-rate IoT services. The transition to this new network technology will result in dramatic increases in filter and RFFE complexity.
5G devices will exist in a mobile device environment that includes more complexity, more components (particularly filters), more performance demands, smaller size and lower cost components, plus dual connectivity between cellular and Wi-Fi networks. More bandwidth will be needed, which will require higher frequency components, more carrier aggregation (CA), more complex MIMO antennas, new and adaptable waveforms and improved interference mitigation.
5G RFFE designs for all wireless-enabled products will be driven by cost, power efficiency and available space within the mobile device. The requirements for 5G filters will include complex multiplexing, increasing integration, more filters and the capability to handle much higher frequencies than are currently in use.
Resonant Infinite Synthesized Networks
To address these needs, Resonant has developed a comprehensive filter Electronic Design Automation (EDA) platform called Infinite Synthesized Networks (ISN). Resonant’s ISN platform brings together the following elements:
- Modern filter theory.
- Finite element modeling, both electro-magnetic and acoustic.
- Novel optimization algorithms.
- Ecosystem of foundry and packaging/back-end partners.
ISN was initially focused on designing acoustic wave filters, which are a key design block for the RFFE. ISN is specifically intended to solve many of the 5G challenges that will face design engineers: speed, flexibility and tools that drive down system cost. As of August 2018, more than 10 companies have committed to produce more than 60 devices using ISN.
Figure 11 is a schematic that shows the design-to-mask flow through the ISN process. Testing has proven that ISN’s models are highly accurate and reflect physical details of the filter structures, matching the measured performance of manufactured filters, not only in loss and isolation but also in power handling and linearity. Thus, ISN is a capable platform for quickly, efficiently and cost-effectively scaling filter design to meet emerging 5G demand.
Figure 11 ISN schematic, showing process flow from initial design to completed mask.
Figure 12 Measured (blue trace) and modeled (green trace) duplexer performance.
Traditional acoustic wave filter design uses a ladder structure and empirical models (linked to a particular fab manufacturer). This typically results in an iterative approach to filter development that involves multiple foundry runs and can take months or more. The ISN platform enables filter design teams to create novel filter structures that outperform traditional filter designs, in a smaller footprint and using lower-cost technologies. Figure 12 shows how closely ISN-modeled performance tracks the actual data measured on a Band 3 duplexer.
ISN’s grounding in fundamental materials physics, while optimizing for high-volume design screening, enables designs that are unconstrained by traditional acoustic wave filter design techniques. Consequently, a designer using ISN can create multiplexers, wide passbands and high-power performance, and predict manufacturing yields as well, before a design is committed to mass production.
Thousands of designs can be developed simultaneously and screened to maximize the ultimate performance of the device. Leveraging the expertise of filter design engineers for an increasing number of more complex designs can be achieved using ISN.
Implications for the 5G RF Front-End
ISN can be used to develop RF filters for 4G/LTE and other wireless networks, but it is especially impactful for 5G designs that need the high performance, small size and complex passband design benefits of the design tool.
The current state-of-the-art for a 4G/LTE mobile smartphone RFFE separates the frequency spectrum into low-band (698 to 960 MHz), mid-band (1710 to 2200 MHz) and high-band (2400 to 3800 MHz) frequencies, which isolates the RF components, minimizes cross-talk and optimizes the entire power amplifier-filter-switch path (see Figure 13). Although integration of components is logical, the increasing complexity of 5G limits the number of manufacturers that have the expertise to execute on such a complex RF sub-system.
Figure 13 Current state-of-the-art RF front-end architecture.
5G RFFEs for all wireless-enabled products will be driven by cost, power efficiency and available space within the unit. So they will need to be small, highly efficient and able to be manufactured in large quantities to meet fast-growing global demand. To commercialize affordable custom parts for IoT devices in particular, RFFEs will need to be designed with a minimum number of components and manufacturing volumes will have to increase dramatically from current levels to reduce per-unit cost. In the current environment, most IoT devices are being built with low-cost parts originally developed for high-volume mobile phone production.
As we move toward 5G, the complexity of the RFFE continues to increase. For instance, in addition to the main antenna path modules, diversity antennas provide both link robustness and increased downlink data rates. Designers are increasingly using receive diversity modules to process the diversity path, comprised of receive (Rx) filters and switches (and increasingly incorporating LNAs). Wireless carriers demanding higher 5G data rates will drive more carrier aggregation, creating more potential interference. Consequently, the onus on RFFE designers moving forward will be to reduce complexity, reduce cost, while at the same time improving performance.
5G Filter Requirements
The growth in the number of filters, and the ever more demanding performance requirements, make RF filtering the critical pain point of the RFFE. The basic requirements for a 5G filter includes complex multiplexing driven by CA and increasing integration to maintain high performance of the RFFE. Maximizing PA efficiency on the uplink, and receiver sensitivity on the downlink, will require optimization of the entire RF chain. As complexity increases, it will be crucial to understand the RF chain and any interactions between elements.
Isolation, loss and power handling requirements continue to create new performance challenges. Filters in the RF chain are a major contributor to loss, which is critical for total Tx efficiency (and ultimately for the current draw for the PA and battery life), and the total noise figure in the Rx path (and ultimately for the SNR and the data rate). Figure 14 shows the estimated losses from each component in the Tx path.
LTE, which is optimized for high speed data, demanded significantly higher power than 3G protocols such as CDMA. And as such, the requirements for isolation and minimizing leakage into the Rx path, and vice versa, grew. This will only be further exacerbated by high-power user equipment (HPUE), which uses more Tx power for improved cell edge coverage. In addition, power durability of progressively smaller filters becomes a major concern.
Figure 14 TX path component line-up with estimated losses.
For 5G, frequencies greater than 6 GHz will require different filter technology than the current acoustic wave filters used in mobile devices. Significant advances will be needed to reduce size and cost. The 5G RFFE for mobile broadband will be extremely complex and that the goal for filter design will be to both simplify the design process and the RFFE itself.
Innovations that enable 5G RFFEs will need to include a low-loss triplexer (to minimize the number of antennas), multi-mode, multi-band PAs and multi-band filters (to reduce the number of filters and switches), all of which will need to be optimized as a complete system to reduce matching components.
Summary
With RF complexity expected to grow significantly in 5G devices, the time is right for a filter design tool that can design better, more complex components in a time and capital efficient way. ISN delivers on this need with highly accurate, highly integrated and highly manufacturable filters with complex features.n
References
- “RF Front-Ends for Mobile Devices 2018,” Mobile Experts Inc., 2018.
- “5G Wireless Market Worth $250 Billion by 2025: $6 Billion Spend Forecast on R&D for 2015–2020,” PR Newswire, March 2016.
- R. Ruby, “A Decade of FBAR Success and What Is Needed for Another Successful Decade,” 2011 Symposium on Piezoelectricity, Acoustic Waves and Device Applications (SPAWDA), 2011, pp. 365–369.
