Software-Defined Analog Filters: A Paradigm Shift in Radio Filter Performance and Capability

Among the most abundant components in all wireless system designs, analog RF filters are used to block interference from various internal and external sources. Limited spectrum divided among an ever-increasing number of users is further driving the need for these ubiquitous but in some ways anachronistic devices. Currently, interference is quite common among cellular base stations, satellite systems, radar installations, and other types of access and backhaul communications systems. Traditional filters are unable to cope with the requirements; in many cases, most often due to insufficient guard bandf. For example, in some international locales, LTE base stations and satellite receivers share the L-band frequencies. At around 3.5 GHz, 5G operators, CBRS radios, and military radars are trying to co-exist. To address this in-band interference, a new, tunable filtering technology is entering the marketplace, uniquely blending the best of both analog and digital technologies.

Conventional Analog Filter — A Glimpse Back in Time

The wireless ecosystem has thrived during a period of exponential technology advancements, bringing dramatic advances in products and services for operators, enterprise users, and consumers alike. This includes moving from vacuum tubes to transistors to integrated circuits; the development of trunked, cellular, and digital radio systems; and the growth of unlicensed devices for consumers.

Yet analog RF filters, essential for combating interference and ensuring efficient use of radio spectrum resources, are still based on analog-era technology with significant performance, size, weight, and manufacturing limitations. RF filters are well-suited for legacy applications such as large, static infrastructure but when it comes to next-generation applications like consumer devices, advanced military communications equipment, or cutting-edge 5G networking devices, they fall significantly short.

Conventional radio filters require a transition or guard band — a range of frequencies over which losses decrease from the rejection band (where unwanted signals are blocked) to the pass band (where desired signals are allowed to pass). In practice, a guard band is a stretch of spectrum that must be sacrificed to accommodate the coarse behavior of conventional filters.

Another conventional analog filter limitation is that they are inherently frequency-specific and must be designed and manufactured for each and every unique application. If an application requires rejecting signals on different frequencies at different times, then a filter bank — a device containing multiple filters that can be switched in and out of the circuit — may be required.

The primary problem with conventional filters, however, is that they often fail to provide enough signal rejection. This occurs in a number of scenarios: the interfering signal is too close in frequency to the desired signal, the source of the interfering signal is too close to the receiver, or the interfering signal is simply too powerful.

Digital Filter — Sufficient for Legacy Implementations

Digital filters, based either on Finite Impulse Response (FIR) or Infinite Impulse Response (IIR) architectures, are widely available and are commonly used as part of practically any digital subsystem. They offer immense flexibility in their ability to shape the signal. By nature, these filters operate on digital samples of the original analog signal. Simply put, before any digital manipulations can be applied to the signal, they must be sampled and converted to digital representation. This process is not only time-consuming but it also degrades the resolution (the dynamic range) of the original signal, since Analog-to-Digital Converters (ADCs) have a finite number of bits of resolution.

Once available in digital representation, the digital filter (essentially a set of mathematical manipulations of the samples) can be applied. This process, again, takes time since every addition or multiplication consumes CPU cycles. Inherently, digital processing introduces latency in the data path that must be accounted for in the application. This often represents a challenge to RF applications given the propagation speed of the native analog signal. Finally, if the desired output of the system needs to be an analog RF signal (as in any transmitter), the digital samples have to be converted yet again, this time back to analog representation using Digital-to-Analog Converters (DACs) — further contributing to undesirable latency.

Software-Defined Analog Filters — A New Paradigm

Figure 1. Diagram of a Finite Impulse Response (FIR) filter.

The perfect RF filter would combine the no-latency, no-sampling characteristics of analog devices with the configurability and flexibility of digital implementations. The wireless electronics industry has been steadily progressing toward digitally controlled analog devices; for example, digitally controlled attenuators and phase shifters are extensively used in radars and other beam-forming applications. Implementation of filters, attenuators, and phase shifters is not enough — delay elements are also necessary; for instance, as part of an IIR or FIR (Figure 1) structure.

Analog delay elements are difficult to miniaturize — they typically rely on materials where waves are propagating slower than typically used conductors. The choice of material is a delicate balance between insertion loss and physical size/weight. Clearly, such solutions are not possible to implement in a low-cost CMOS IC. This is especially true for wireless applications where propagation delays necessitate long delay elements in the range of hundreds of nanoseconds or even microseconds, in aggregate.

Figure 2. Kumu Networks’ KU1500 RF integrated circuit.

As the only commercially available solution to embed long delay elements in a standard CMOS chip, the Kumu Networks KU1500 RFIC changes the existing paradigms (Figure 2). The software-controlled analog filter designed for wireless applications is essentially a multi-tap implementation in which each tap packs an adder, multiplier, and delay element (Figure 3). By adjusting the weights of its multipliers through a digitally controlled API, any desired filter response can be configured.

The software-defined analog filter was originally developed for Self-Interference Cancellation applications where the interferer is co-located next to the receiver. This is achieved by continuously modifying the response of the multi-tap analog filter to match the self-interference, using a tuning logic that estimates the self-interference channel. Traditional filter applications are obviously much simpler than that and can be handled with static configuration of the filter for the desired response.

Figure 3. The software-controlled analog filter is a multi-tap implementation in which each tap packs an adder, multiplier, and delay element.


For many legacy applications, conventional filters are cheap, reasonably small, and do an acceptable job. But in other applications, conventional filters fall short. A digitally controlled analog filter separates itself in environments where guard bands are unavailable or where spectrum cost dictates their elimination. Such filters could contribute dramatically to improved spectrum utilization. Additionally, self-interference cancellation based on these filters offers the ultimate solution for packaging multiple co-located radios into a small form-factor device, while sustaining total frequency agility across the entire band.

Using this technology, radios can communicate simultaneously using nearby, immediately adjacent, or even overlapping frequencies — a problem that actually occurs in the billions of mass-market devices that currently attempt to support both Wi-Fi and Bluetooth.

This article was written by Joel Brand, VP of Product Management at Kumu Networks (Sunnyvale, CA). For more information, visit here .