Swami Hindle's 2017 RF/Microwave Industry Predictions
Every year Swami Hindle makes his RF and microwave industry predictions for the New Year. Here are the predictions for 2017:
- Drone detection systems will be a hot product and offered by many companies with increasing capabilities such as detection, location, disabling, data high-jacking, jamming and more.
- Electronic Warfare will see a resurgence and become a more of a DoD priority
- 3D Printing (and other forms of Additive Manufacturing) will take off for microwave components
- 5G will hit an inflexion point where mmWave components will be commercially available at a reasonable cost for infrastructure and backhaul and force some adoption by 2020 (although most of the first systems will be sub 6 GHz)
- IoT will see its largest deployments in industrial and automotive applications
- Autonomous vehicles and V2V communications will become reality much faster than anticipated and be a major focus for RF companies
- GaN will overtake GaAs in backhaul and point-to-point applications plus Si LDMOS in cellular infrastructure in many sockets
- The Chinese will buy so many semiconductor companies that the US will start blocking some sales of US companies
New this year, we invited ADI and MathWorks to contribute their 2017 industry forecasts so Greg Henderson and Ken Karnofsky have contributed the following perspectives:
2017 Wireless and RF Forecast
Greg Henderson, Vice President, RF and Wireless business unit, Analog Devices, Inc.
There are two mega-trends driving RF, microwave and millimeter wave technology: the insatiable demand for broadband connectivity, and the emergence of wireless sensing.
The exponential growth of broadband data is driving wireless (and wired) communications systems to more effectively use existing bandwidth, even as the industry searches for wider bandwidth spectrum at higher frequencies. To make effective use of the wireless channel, system operators are moving toward massive-MIMO, multi antenna systems that transmits multiple wide-bandwidth data streams – geometrically adding to system complexity and power consumption. This trend can be seen in markets such as cellular access, point-to-point radio, and satellite and military communications, where peak data rates have been increasing by about 58% each year for last six years and the total mobile data traffic is expected to grow at 45% CAGR to 2020. For system operators, higher-frequency systems provide the promise of greatly increased data rates, but with significant added complexity due to propagation challenges and inherently lower power efficiency.
The other rapidly emerging market is wireless sensing. Originally serviced by discrete solutions for military systems, the technology has evolved to a point where there are a broad array of wireless sensing applications such as automotive radar for driver assistance, industrial radar for applications such as drone collision avoidance and smart traffic systems, and millimeter wave scanners for airport security. In wireless sensing, higher bandwidth means higher resolution, and this is driving systems to higher frequencies. As with the communications sector, wireless sensing is moving to multi-antenna (phased-array) systems that allow for sophisticated beam steering and multi-beam sensing configurations.
In these cases, the only effective path forward is to provide system-level solutions that leverage optimum technologies and interfaces across the complete signal chain. This requires a deep understanding of system applications, signal chain components (data converters, frequency and clock generation, RF switching and amplification) and a broad range of technologies, including low-geometry CMOS, SiGe, BiCMOS, GaAs, GaN, and system-level packaging. Each sub-market presents unique architectural and system challenges that requires customized signal chains and integrated solutions to meet performance, cost, and power consumption requirements.
Wireless predictions for 2017
Ken Karnofsky, Senior Strategist, Signal Processing Applications, MathWorks
In 2017, emerging 5G technologies and the increasing power of low-cost software-defined radios will challenge the way engineers research, design, and build wireless products. These technologies are driving deep integration of RF and digital technologies to implement mmWave radios, massive MIMO antenna arrays, and flexible multifunction radios for commercial, military, and public safety systems.
For example, radios operating at mmWave frequencies will employ extremely compact MIMO array designs, with the RFIC integrated with the antenna elements. Similarly, 5G systems are expected to achieve high throughput at relatively low power by using hybrid beamforming techniques. These techniques partition the processing between RF and digital components to optimize signal-to-noise ratio and efficiently focus transmitted signals on a specific location.
Another growing challenge is the coexistence of various wireless systems, including radar, in a crowded spectrum environment. Managing interference – intentional or not – also drives the need for adaptive techniques to tune the behavior of the radio front end. In these smart radio transceivers, the RF and digital components of these designs cannot be modeled independently.
These highly integrated devices require engineers to design across traditional silos of expertise and domain-specific tools. As a result, we see 5G and designers of other advanced wireless technologies relying on multi-domain simulation tools. By modeling the antenna, RF, and digital subsystems together, they can quickly explore alternative architectures and algorithms and measure the impact of design tradeoffs on system performance. Importantly, these tools enable modeling at different levels of fidelity to get the details right before moving to hardware. Verifying critical behavior in simulation reduces the risk of costly hardware re-spins.
In 2017, we will also see expanded use of SDR technology to meet the need for hardware prototypes and testbeds for a range of wireless applications, including 5G. System designers and R&D engineers see an opportunity to use SDR hardware to speed development of these prototypes, but often lack the FPGA or SoC programming expertise to implement their designs on that hardware. They will increasingly turn to a Model-Based Design workflow that uses generation of portable HDL and C code from models. Using this workflow, they can design, prototype, and verify algorithms on a range of commercial SDR hardware and create production-ready IP for implementation on custom hardware.