Network Technologies, Army STTR, Phase I
Underlay Communications with Wide SINR Range
Objective
Businesses should utilize Canonical Correlation Analysis to achieve high levels of interference suppression for tactical communications that support military networks’ underlay wireless communications.
Description
Army communications networks need to operate in a congested and contested electromagnetic spectrum environment. The tactical radio receiver in such environments may face significant co-channel interference.
The interference may result from other EMS users, including radio stations, radars or other interferers such as Electronic Warfare Systems. Traditional approaches to sustain resilient communications in such environments include spread-spectrum communications or high-coded communications that take advantage of the capacity, versus Low Probability of Detection and Anti -Jam performance trades space.
This approach requires significant channel bandwidth and treats the interference as noise that cannot excise from the receiver. However, recognizing that interference is not thermal noise, this topic seeks solutions (e.g., CCA, Singular Value Decomposition) that would enable the operation of communications links in the presence of considerable co-channel interference.
In cognitive radio literature, underlay communications is the ability to operate a link in the presence of a primary user at sufficiently low power to avoid interference. In the military context, underlay communications offer many benefits, including improved spectrum efficiency, improved covertness and improved resistance to interference.
The Army wants to operate an underlay network at a capacity that is significantly higher than expected in instances where interference is treated as noise. The technology solution should offer a physical layer design that supports tactically relevant bandwidths via a single-antenna transmitter with single or multiple antenna receivers.
The maximum number of antenna receivers is four. It’s important that the performance of the link does not suffer any sharp degradation if the primary signal varies in power or behaves intermittently. The underlay system cannot assume any prior knowledge of the primary signal.
Phase I
The feasibility study should outline the theory of operation, describe relevant signal processing algorithms, any limiting factors and simulation results. The study should also address how the proposed physical layer may integrate with higher-layer protocols.
The algorithm allows the underlay communications signal to maintain an SER/BER performance with interference degradation that is no more than a factor of six, compared to no interference at the same SNR.
Phase II
The Phase II effort should deliver a functioning underlay link, physical-layer prototype implemented on a widely used software defined radio platform. The prototype should perform an independent, lab-based assessment of link performance using a set of selected primary signals.
During Phase II, the Army does not require demodulation and decoding to occur in real time. For the proof of concept, post-processing of the received digital signal samples is a viable approach.
An important element in Phase II is the interaction between testing and iterative software refinement by the performer. Therefore, the business should have the first iteration of the prototype at least three months before the conclusion of Phase II.
The algorithm allows the underlay communications signal to maintain an SER/BER performance with interference degradation that is no more than a factor of five, compared to no interference at the same SNR.
Phase III
The Phase III effort should deliver a real-time implementation of the algorithm using hardware acceleration. The algorithm allows the underlay communications signal to maintain an SER/BER performance with interference degradation that is no more than a factor of five, compared to no interference at the same SNR.
Submission Information
All eligible businesses must submit proposals by noon ET.
To view full solicitation details, click here.
For more information, and to submit your full proposal package, visit the DSIP Portal.
STTR Help Desk: usarmy.rtp.devcom-arl.mbx.sttr-pmo@army.mil
References:
- M. S. Ibrahim and N. D. Sidiropoulos, “Blind Carbon Copy on Dirty Paper: Seamless Spectrum Underlay via Canonical Correlation Analysis,” 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 8123-8127, doi: 10.1109/ICASSP39728.2021.9414621.
- M. S. Ibrahim, P. Karakasis, and N. D. Sidiropoulos, “A Simple and Practical Underlay Scheme for Short-range Secondary Communication”, in IEEE Transactions on Wireless Communications, vol. 21, no. 11, pp. 9990-10004, Nov. 2022, doi: 10.1109/TWC.2022.3181618.
- M. S. Ibrahim, and N. D. Sidiropoulos, “Cell-Edge Interferometry: Reliable Detection of Unknown Cell-Edge Users via Canonical Correlation Analysis,” at the 20th IEEE SPAWC, Cannes, France, July 2020.
- M. S. Ibrahim, and N. D. Sidiropoulos, “Reliable Detection of Unknown Cell-Edge Users via Canonical Correlation Analysis”, IEEE Transactions on Wireless Comm., vol. 19, Mar. 2020.
- M. Sørensen, C. I. Kanatsoulis and N. D. Sidiropoulos, “Generalized Canonical Correlation Analysis: A Subspace Intersection Approach,” in IEEE Transactions on Signal Processing, vol. 69, pp. 2452-2467, 2021, doi: 10.1109/TSP.2021.3061218.
- M. S. Ibrahim, and N. D. Sidiropoulos, “Underlay Scheme for Short-range Secondary Communication”, US Patent pending.
- M. S. Ibrahim, A. Hussain and N. D. Sidiropoulos, “A Novel Linear Precoder Design for Reliable UL/DL Detection in TDD Cellular Networks,” in IEEE Transactions on Communications, vol. 70, no. 12, pp. 8167-8180, Dec. 2022, doi: 10.1109/TCOMM.2022.3217129.
- M. S. Ibrahim, P. A. Karakasis and N. D. Sidiropoulos, “A link between Multiuser MMSE and Canonical Correlation Analysis,” in IEEE Wireless Communications Letters, doi: 10.1109/LWC.2023.3319292.
- KEYWORDS: Underlay networks, spectrum efficiency, congested spectrum, contested spectrum, Symbol Error Rate (SER), Bit Error Rate (BER), Signal to Noise (SNR).
Objective
Businesses should utilize Canonical Correlation Analysis to achieve high levels of interference suppression for tactical communications that support military networks’ underlay wireless communications.
Description
Army communications networks need to operate in a congested and contested electromagnetic spectrum environment. The tactical radio receiver in such environments may face significant co-channel interference.
The interference may result from other EMS users, including radio stations, radars or other interferers such as Electronic Warfare Systems. Traditional approaches to sustain resilient communications in such environments include spread-spectrum communications or high-coded communications that take advantage of the capacity, versus Low Probability of Detection and Anti -Jam performance trades space.
This approach requires significant channel bandwidth and treats the interference as noise that cannot excise from the receiver. However, recognizing that interference is not thermal noise, this topic seeks solutions (e.g., CCA, Singular Value Decomposition) that would enable the operation of communications links in the presence of considerable co-channel interference.
In cognitive radio literature, underlay communications is the ability to operate a link in the presence of a primary user at sufficiently low power to avoid interference. In the military context, underlay communications offer many benefits, including improved spectrum efficiency, improved covertness and improved resistance to interference.
The Army wants to operate an underlay network at a capacity that is significantly higher than expected in instances where interference is treated as noise. The technology solution should offer a physical layer design that supports tactically relevant bandwidths via a single-antenna transmitter with single or multiple antenna receivers.
The maximum number of antenna receivers is four. It’s important that the performance of the link does not suffer any sharp degradation if the primary signal varies in power or behaves intermittently. The underlay system cannot assume any prior knowledge of the primary signal.
Phase I
The feasibility study should outline the theory of operation, describe relevant signal processing algorithms, any limiting factors and simulation results. The study should also address how the proposed physical layer may integrate with higher-layer protocols.
The algorithm allows the underlay communications signal to maintain an SER/BER performance with interference degradation that is no more than a factor of six, compared to no interference at the same SNR.
Phase II
The Phase II effort should deliver a functioning underlay link, physical-layer prototype implemented on a widely used software defined radio platform. The prototype should perform an independent, lab-based assessment of link performance using a set of selected primary signals.
During Phase II, the Army does not require demodulation and decoding to occur in real time. For the proof of concept, post-processing of the received digital signal samples is a viable approach.
An important element in Phase II is the interaction between testing and iterative software refinement by the performer. Therefore, the business should have the first iteration of the prototype at least three months before the conclusion of Phase II.
The algorithm allows the underlay communications signal to maintain an SER/BER performance with interference degradation that is no more than a factor of five, compared to no interference at the same SNR.
Phase III
The Phase III effort should deliver a real-time implementation of the algorithm using hardware acceleration. The algorithm allows the underlay communications signal to maintain an SER/BER performance with interference degradation that is no more than a factor of five, compared to no interference at the same SNR.
Submission Information
All eligible businesses must submit proposals by noon ET.
To view full solicitation details, click here.
For more information, and to submit your full proposal package, visit the DSIP Portal.
STTR Help Desk: usarmy.rtp.devcom-arl.mbx.sttr-pmo@army.mil
References:
- M. S. Ibrahim and N. D. Sidiropoulos, “Blind Carbon Copy on Dirty Paper: Seamless Spectrum Underlay via Canonical Correlation Analysis,” 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 8123-8127, doi: 10.1109/ICASSP39728.2021.9414621.
- M. S. Ibrahim, P. Karakasis, and N. D. Sidiropoulos, “A Simple and Practical Underlay Scheme for Short-range Secondary Communication”, in IEEE Transactions on Wireless Communications, vol. 21, no. 11, pp. 9990-10004, Nov. 2022, doi: 10.1109/TWC.2022.3181618.
- M. S. Ibrahim, and N. D. Sidiropoulos, “Cell-Edge Interferometry: Reliable Detection of Unknown Cell-Edge Users via Canonical Correlation Analysis,” at the 20th IEEE SPAWC, Cannes, France, July 2020.
- M. S. Ibrahim, and N. D. Sidiropoulos, “Reliable Detection of Unknown Cell-Edge Users via Canonical Correlation Analysis”, IEEE Transactions on Wireless Comm., vol. 19, Mar. 2020.
- M. Sørensen, C. I. Kanatsoulis and N. D. Sidiropoulos, “Generalized Canonical Correlation Analysis: A Subspace Intersection Approach,” in IEEE Transactions on Signal Processing, vol. 69, pp. 2452-2467, 2021, doi: 10.1109/TSP.2021.3061218.
- M. S. Ibrahim, and N. D. Sidiropoulos, “Underlay Scheme for Short-range Secondary Communication”, US Patent pending.
- M. S. Ibrahim, A. Hussain and N. D. Sidiropoulos, “A Novel Linear Precoder Design for Reliable UL/DL Detection in TDD Cellular Networks,” in IEEE Transactions on Communications, vol. 70, no. 12, pp. 8167-8180, Dec. 2022, doi: 10.1109/TCOMM.2022.3217129.
- M. S. Ibrahim, P. A. Karakasis and N. D. Sidiropoulos, “A link between Multiuser MMSE and Canonical Correlation Analysis,” in IEEE Wireless Communications Letters, doi: 10.1109/LWC.2023.3319292.
- KEYWORDS: Underlay networks, spectrum efficiency, congested spectrum, contested spectrum, Symbol Error Rate (SER), Bit Error Rate (BER), Signal to Noise (SNR).