Interference management with realistic assumptions on the knowledge of channel state information at the transmitters

• Applicant: Professor Peter Schreier, Ph.D., since 4/2018
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: from 2017 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 327962471

• Final Report Year: 2022

Final Report Abstract

Our project developed efficient transmission and reception schemes for interference-limited multiuser communication networks with realistic assumptions on the availability of channel state information at the transmitter side. With the growing number of users and the scarcity of the frequency spectrum, wireless networks have become interference-limited, and therefore interference management is now an important task. We considered various problems that are of interest in this context. We proposed a simple interference-alignment scheme to achieve the optimal degrees-of-freedom of the temporally correlated two-user Multiple-Input-Multiple-Output (MIMO) Interference Channel with delayed channel state information at the transmitters. For most antenna configurations, the proposed scheme achieves the optimal degrees-of-freedom-region of this channel by precoding (resp. decoding) over a finite number of time slots at each transmitter (resp. receiver). We also considered hardware imperfections. We derived the rate region of a MIMO system with imperfect transmitters when interference is treated as noise at the receiver side. We proposed a cooperative distributed framework to optimize a variety of rate and energy-efficiency utility functions, such as the minimum-weighted rate or the global energy efficiency, for the K-user interference channel. We introduced a regularization approach to enhance the performance of a detector for MIMO communications, based on lattice reduction and successive interference cancellation, which was shown to enable significant performance improvements. Finally, we addressed a very general hypothesis testing problem whether a covariance matrix can be expressed by an unknown linear combination of a set of known matrices or by another unknown linear combination of a set of different, but known, matrices.

Publications

• “A degrees-of-freedom-achieving scheme for the temporally correlated MIMO interference channel with delayed CSIT,” IEEE Trans. Wireless Comm., vol. 17, pp. 5397-5408, Aug. 2018
  M. Rezaee and P. J. Schreier
  (See online at https://doi.org/10.1109/TWC.2018.2843345)
• “Regularized lattice reduction-aided ordered successive interference cancellation for MIMO detection,” in Proc. IEEE Stat. Signal Proc. Workshop, Freiburg, Germany, June 2018
  J. Tong, Q. Guo, J. Xi, Y. Yu, and P. J. Schreier
  (See online at https://doi.org/10.1109/SSP.2018.8450791)
• “A general test for the linear structure of covariance matrices of Gaussian populations,” in Proc. Intl. Conf. Acoustics, Speech, Signal Processing (ICASSP), Barcelona, Spain, May 2020
  Y.-H. Xiao, D. Ramirez, and P. J. Schreier
  (See online at https://doi.org/10.1109/ICASSP40776.2020.9053718)
• “Distributed algorithms for spectral and energy-efficiency maximization of K-user interference channels,” IEEE Access, pp. 96948- 96963
  M. Soleymani, I. Santamaria, and P. J. Schreier
  (See online at https://doi.org/10.1109/ACCESS.2021.3094976)
• “Rate region of the K-user MIMO interference channel with imperfect transmitters,” in Proc. European Signal Processing Conference (EUSIPCO), Amsterdam, Jan. 2021
  M. Soleymani, I. Santamaria, B. Maham, and P. J. Schreier
  (See online at https://doi.org/10.23919/Eusipco47968.2020.9287450)