An example application for adaptive RF DSP is shown in Figure 3. Here, three simultaneous, single-timeslot GSM bursts are injected co-channel to a victim UMTS uplink signal. This interference scenario often occurs at international borders, due to cross-border mobile station (MS) transmissions. It is also an interference scenario that must be managed by an operator when deploying UMTS in spectrum previously allocated to GSM.
Figure 3: Tracking and attenuation of frequency-hopped single timeslot GSM signals.
GSM-as-interference is among the most difficult sources for adaptive RF DSPs to track, since due to the hybrid TDMA/FDMA structure of the air interface the signal is highly dynamic in both the frequency- and time-domains. The GSM burst must be acquired and attenuated in a timeframe short relative to its 577 μs duration, adequate attenuation must be provided to reduce the power over its 200 kHz modulation bandwidth, and multiple sources (at multiple frequencies) must typically be tracked simultaneously. In the example shown, three independent bursts are tracked and attenuated by approximately 20 dB each. This result is achieved by the RF DSP alone, and requires no synchronization with the interfering GSM network.
In this example, the spectral efficiency benefits provided by the technology are most easily demonstrated by evaluating the link budget from the interfering GSM MSs to the victim Node B. As illustrated in Figure 4, in a mixed suburban environment, UMTS and GSM networks operating in the same band must be kept 23 km apart to ensure that any GSM transmissions received at the Node B are below the thermal noise floor. The additional 20 dB of margin provided by the RF DSP allows the networks to be brought within 6 km of each other under the same constraints. The ability to deploy UMTS in such close proximity to GSM, in a geographic region in which the spectrum would otherwise have been unused, represents an enormous improvement in spectral efficiency – greater than 50% in this case.
Figure 4: Spectral efficiency benefits provided by RF DSPs applied to the GSM-on-UMTS co-channel interference scenario. The required isolation distance between GSM and UMTS is reduced by 75%.
RF DSPs can also be used to improve adjacent channel selectivity (ACS). In Figure 5, highly selective band-reject filters have been configured to provide additional isolation on the GSM channels operating at the smallest frequency offsets from the UMTS carrier frequencies. Since the filters are software configurable, here their frequencies and bandwidths have been set to match the channel frequencies and modulations envelopes, respectively, of the adjacent channel GSM signals. This ensures ACS is optimized for this specific application.
Figure 5: Attenuation of adjacent channel GSM interference with RF DSPs allows GSM to operate at narrower frequency offsets from UMTS.
This approach allows UMTS to be deployed in spectrum previously used for GSM, while minimizing the impact on the existing 2G network. The effectiveness of the filtering from the RF DSPs is such that the adjacent channel interference ratio (ACIR) is comparable to the case when the nearest adjacent channel is not used at all – allowing UMTS to be operated in the presence of GSM operating at small offsets with no penalty in UMTS capacity. Obviously, the use of radio channels that would otherwise be unavailable in this scenario is another direct demonstration of improvement of spectral efficiency by using smart RF DSPs to manage spectrum.
Spectrum awareness allows smarter spectrum management
Tuning information used to adapt the frequency response of the RF DSP in response to detected interference can be stored, which allows a repository of information regarding the interference environment to be built up in the course of operation. The information can then be downloaded and postprocessed, providing operational teams a powerful additional view into the RF environment in which their network is operating. This information can then be used to augment traditional interference tracking methods, when appropriate. In this case, while the response team acts on the interference information gathered by the device, the adaptive filter subsystem continues to protect the radio, providing uninterrupted high quality of service levels even in the face of severe interference.
An example of such data is shown in Figure 6. Here, the time of the interference event is plotted against frequency, and interferer power is indicated by the false color scale on the right. This spectrogram view provides a powerful visual summary of the interference environment over a period of time in a single integrated view – and also, since the channel conditions are not static, clearly demonstrates the advantages of adapting the radio to the channel conditions. Deployed over a wide network area, the RF channel “situational awareness” offered by this technology provides a valuable information source for ensuring spectrum fidelity.
Figure 6: Spectrogram interference data gathered by an adaptive RF DSP system in a live site, illustrating the power and frequency variability of the interfering signals.
Spectrum conditioning: A core component of any comprehensive spectrum strategy
As the impending spectrum crunch approaches, the need to treat spectrum as a precious resource is becoming more acute. Additional spectrum allocations will be required to meet long-term demand, but maintaining high spectral efficiency across the spectrum allocated to terrestrial wireless services will be equally vital. Just as advances in air interface technologies have steadily improved the spectral efficiency of wireless networks, advances in RF DSP techniques have allowed adaptive RF to become a reality, and provide a method for maintaining high spectral efficiency, even in suboptimal and unpredictable real-world RF environments.
About the Author Dr. Cordone joined ISCO International in 2000 as a member of the technical staff. His early work at ISCO focused on the development of a novel compact superconducting RF filter for 3G wireless applications. Dr. Cordone subsequently served as Senior System Architect and Director of Engineering, and directed the development of the company’s portfolio of RF conditioning products. In his current role, Dr. Cordone leads the company's research and development efforts, with particular focus on innovations in time-adaptive RF techniques. Dr. Cordone holds four patents, and has two additional patents pending relating to the adaptive mitigation of interference in wireless networks.
Prior to joining ISCO, Dr. Cordone was with the Department of Physics at the University of Wisconsin. There, in collaboration with NASA GSFC, he developed signal processing methods and cryogenic micro- and mm-wave detector technology for astrophysical research. Dr. Cordone was a Fulbright Scholar in Germany at the Universität Osnabrück, and is a Senior Member of the IEEE. He holds an MS in Physics from Brown University, and a PhD in Physics from the University of Wisconsin at Madison.
thanks for the perceptive comments. You touch on many relevant points.
You are correct, implementation on the mobile equipment would be a logical next step - subject of course to the power and processing constraints on the mobile platform.
The conversion to RF has to do with realistic integration constraints - it's not a core part of the design. The system described integrates essentially like a "smart" RF cable in existing infrastructure. As the technology is adopted, it would inevitably be integrated at baseband in the radio.
I also agree that adaptive spatial techniques would provide huge benefits in capacity. This should be complementary technology to the adaptive filtering approach described above.
Thank you very much for such a thought provoking descriptions of RF interference problems and solutions to them.
My first thought is the article is very base station centric. As Moore marches on much of this will be applicable to the mobile end of the channel as well. Second thought; why after all this elegant processing would you want to convert back to RF?
The next thing that comes to mind, which you touched on very briefly, is the dynamic range requirement for the A/D in a strong interference scenario.
The biggest thing that comes to mind though is the wild ride we have before us as data use rises exponentially. You mention the ultimate need for further bandwidth. But this too has its limits. We don’t want this to turn into another water resource fight. Fortunately we have another three dimensions to play with, spatial resources. The situational awareness that you speak of should include a spatial RF refractive and reflective index map, including as precise as possible real time mobile device location. We can thereby use directionality to spatially increase capacity.