Transceiver Designs to Improve Spectrum Utilization in MIMO Interference Channels

  • Le Ty Khanh Ho Chi Minh City University of Technology, Vietnam
  • Ha Hoang Kha Ho Chi Minh City University of Technology, Vietnam
  • Nguyen Minh Hoang Saigon Insti-tute of ICT (SaigonICT

Abstract

This paper is concerned with a multiple-input multiple-output (MIMO) multi-user wireless networks in which multiple secondary users (SUs) can share the same radio spectrum with a single primary user (PU). The design problems of the transceivers in such MIMO interference channels are to find the precoding matrices at the transmitters and the receiving matrices at the receivers to minimize the mean square error (MSE) or to maximize the sum-rate of the SUs while guaranteeing the interference power at the PU receiver below an acceptable threshold. In this paper, we consider to design the transceivers using the interference alignment techniques. The objective is to align the interference at the SUs and maintain an acceptable leakage interference level from the SUs into the signal subspace of the PU receiver. Due to the nonlinearity and nonconvexity of the underlaying problems, we develop an alternating algorithm which efficiently solves a convex optimization in each iteration. The numerical results are provided to validate the performance of our algorithm.

Downloads

Download data is not yet available.

References

[1] A. Goldsmith, S. Jafar, I. Maric, and S. Srinivasa, “Breaking spectrum gridlock with cognitive radios: An information theoretic perspective,” Proc. IEEE, vol. 97, pp. 894–914, May 2009.
[2] Q. Zhao and B. Sadler, “A survey of dynamic spectrum access,” IEEE Signal Processing Mag., vol. 24, pp. 79–89, May 2007.
[3] H. Shen, B. Li, M. Tao, and X. Wang, “MSE-based transceiver designs for the MIMO interference channel,” IEEE Trans. Wireless Commun., vol. 9, pp. 3480–3489, Nov. 2010.
[4] M. Toutounchian and R. Vaughan, “SINR-based transceiver design in the K-user MIMO interference channel using multiobjective optimization,” in Proc. IEEE Veh. Technol. Conf. (VTC Fall), pp. 1–5, Sept. 2013.
[5] A. Alizadeh and H. Bahrami, “Optimal distributed beamforming for cooperative cognitive radio networks,” in Proc. IEEE Veh. Technol. Conf. (VTC Spring), pp. 1–5, Jun. 2013.
[6] Y. Zhang, E. DallAnese, and G. Giannakis, “Distributed optimal beamformers for cognitive radios robust to channel uncertainties,” IEEE Trans. Signal Process., vol. 60, pp. 6495–6508, Dec. 2012.
[7] V. Cadambe and S. Jafar, “Interference alignment and degrees of freedom of the K -user interference channel,” IEEE Trans. Inform. Theory, vol. 54, pp. 3425–3441, Aug. 2008.
[8] K. Gomadam, V. Cadambe, and S. Jafar, “A distributed numerical approach to interference alignment and applications to wireless interference networks,” IEEE Trans. Inform. Theory, vol. 57, pp. 3309–3322, Jun. 2011.
[9] K. Gomadam, V. Cadambe, and S. Jafar, “Approaching the capacity of wireless networks through distributed interference alignment,” in Proc. IEEE Global Telecommun., pp. 1–6, Mar. 2008.
[10] M. Razaviyayn, M. Sanjabi, and Z. Q. Luo, “Linear transceiver design for interference alignment: complexity and computation,”IEEE Trans. Inform. Theory, vol. 58, pp. 2896–2910, May 2012.
[11] H. Du and T. Ratnarajah, “Robust joint signal and interference alignment for MIMO cognitive radio network,” in Proc. IEEE Wireless Commun. and Networking Conf. (WCNC), pp. 448–452, Apr. 2012.
[12] H. Zhou, T. Ratnarajah, and Y.-C. Liang, “On secondary network interference alignment in cognitive radio,” in Proc. IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), pp. 637–641, May 2011.
[13] H. Du, T. Ratnarajah, H. Zhou, and Y.-C. Liang, “Interference alignment for peer-to-peer underlay MIMO cognitive radio network,” in Proc. the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), pp. 349–353, Nov. 2011.
[14] S. Peters and R. Heath, “Interference alignment via alternating minimization,” in Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Process., (ICASSP), pp. 2445–2448, Apr. 2009.
[15] S. Ganesan, M. Sellathurai, and T. Ratnarajah, “Opportunistic interference projection in cognitive MIMO radio with multiuser diversity,” in Proc. IEEE Symposium on New Frontiers in Dynamic Spectrum, pp. 1–6, Apr. 2010.
[16] A. Paulraj, R. Nabar, and D. Gore, Introduction to Space-Time Wireless Communications. Cambridge University Press, 2003.
[17] G. Scutari and D. Palomar, “MIMO cognitive radio: A game theoretical approach,” IEEE Trans. Signal Process., vol. 58, pp. 761–780, Feb. 2010.
[18] D. Papailiopoulos and A. Dimakis, “Interference alignment as a rank constrained rank minimization,” IEEE Trans. Signal Process., vol. 60, pp. 4278–4288, Aug. 2012.
[19] M. Maddah-Ali, A. Motahari, and A. Khandani, “Signaling over MIMO multi-base systems: Combination of multi-access and broadcast schemes,” in Proc. EEE Int. Symposium on Inform. Theory, pp. 2104–2108, Jul. 2006.
[20] S. Peters and R. Heath, “Cooperative algorithms for MIMO interference channels,” IEEE Trans. Veh. Technol., vol. 60, pp. 206–218, Jan. 2011.
[21] H. Tuy, Convex Analysis and Global Optimization. Kluwer Academic, 1997.
[22] D. Peaucelle, D. Henrion, Y. Labit, and K. Taitz, “Users guide for seumi interface 1.04,” Sept. 2002, Available:
http://homepages.laas.fr/peaucell/software/sdmguide.pdf.

Published
2015-08-31
How to Cite
KHANH, Le Ty; KHA, Ha Hoang; HOANG, Nguyen Minh. Transceiver Designs to Improve Spectrum Utilization in MIMO Interference Channels. Journal of Science and Technology: Issue on Information and Communications Technology, [S.l.], v. 1, p. 47-52, aug. 2015. ISSN 1859-1531. Available at: <http://ict.jst.udn.vn/index.php/jst/article/view/11>. Date accessed: 22 nov. 2024. doi: https://doi.org/10.31130/jst.2015.11.