Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Block-Level MU-MISO Interference Exploitation Precoding: Optimal Structure and Explicit Duality (2401.00166v1)

Published 30 Dec 2023 in cs.IT, eess.SP, and math.IT

Abstract: This paper investigates block-level interference exploitation (IE) precoding for multi-user multiple-input single-output (MU-MISO) downlink systems. To overcome the need for symbol-level IE precoding to frequently update the precoding matrix, we propose to jointly optimize all the precoders or transmit signals within a transmission block. The resultant precoders only need to be updated once per block, and while not necessarily constant over all the symbol slots, we refer to the technique as block-level slot-variant IE precoding. Through a careful examination of the optimal structure and the explicit duality inherent in block-level power minimization (PM) and signal-to-interference-plus-noise ratio (SINR) balancing (SB) problems, we discover that the joint optimization can be decomposed into subproblems with smaller variable sizes. As a step further, we propose block-level slot-invariant IE precoding by adding a structural constraint on the slot-variant IE precoding to maintain a constant precoder throughout the block. A novel linear precoder for IE is further presented, and we prove that the proposed slot-variant and slot-invariant IE precoding share an identical solution when the number of symbol slots does not exceed the number of users. Numerical simulations demonstrate that the proposed precoders achieve a significant complexity reduction compared against benchmark schemes, without sacrificing performance.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (36)
  1. E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, “Massive MIMO for next generation wireless systems,” IEEE Commun. Mag., vol. 52, no. 2, pp. 186–195, Feb. 2014.
  2. L. Lu, G. Y. Li, A. L. Swindlehurst, A. Ashikhmin, and R. Zhang, “An overview of massive MIMO: Benefits and challenges,” IEEE J. Sel. Topics Signal Process., vol. 8, no. 5, pp. 742–758, Oct. 2014.
  3. L. Zheng and D. Tse, “Diversity and multiplexing: A fundamental tradeoff in multiple-antenna channels,” IEEE Trans. Inf. Theory, vol. 49, no. 5, pp. 1073–1096, May 2003.
  4. N. Sidiropoulos, T. Davidson, and Z.-Q. Luo, “Transmit beamforming for physical-layer multicasting,” IEEE Trans. Signal Process., vol. 54, no. 6, pp. 2239–2251, Jun. 2006.
  5. C. Windpassinger, R. Fischer, T. Vencel, and J. Huber, “Precoding in multiantenna and multiuser communications,” IEEE Trans. Wireless Commun., vol. 3, no. 4, pp. 1305–1316, Jul. 2004.
  6. G. Caire and S. Shamai, “On the achievable throughput of a multiantenna Gaussian broadcast channel,” IEEE Trans. Inf. Theory, vol. 49, no. 7, pp. 1691–1706, Jul. 2003.
  7. C. Peel, B. Hochwald, and A. Swindlehurst, “A vector-perturbation technique for near-capacity multiantenna multiuser communication-part I: Channel inversion and regularization,” IEEE Trans. Commun., vol. 53, no. 1, pp. 195–202, Jan. 2005.
  8. M. Costa, “Writing on dirty paper,” IEEE Trans. Inf. Theory, vol. 29, no. 3, pp. 439–441, May 1983.
  9. B. Hochwald, C. Peel, and A. Swindlehurst, “A vector-perturbation technique for near-capacity multiantenna multiuser communication-part II: Perturbation,” IEEE Trans. Commun., vol. 53, no. 3, pp. 537–544, Mar. 2005.
  10. M. Bengtsson and B. Ottersten, “Optimal downlink beamforming using semidefinite optimization,” in Proc. 37th Annu. Allerton Conf. Commun., Control Comput., Sep. 1999, pp. 987–996.
  11. ——, “Optimum and suboptimum transmit beamforming,” in Handbook of Antennas in Wireless Communications.   Boca Raton, FL, USA: CRC Press, 2002, pp. 18–1.
  12. A. Wiesel, Y. Eldar, and S. Shamai, “Linear precoding via conic optimization for fixed MIMO receivers,” IEEE Trans. Signal Process., vol. 54, no. 1, pp. 161–176, Jan. 2006.
  13. E. Karipidis, N. D. Sidiropoulos, and Z.-Q. Luo, “Quality of service and max-min fair transmit beamforming to multiple cochannel multicast groups,” IEEE Trans. Signal Process., vol. 56, no. 3, pp. 1268–1279, Mar. 2008.
  14. C. Masouros and E. Alsusa, “A novel transmitter-based selective-precoding technique for DS/CDMA systems,” IEEE Signal Process. Lett., vol. 14, no. 9, pp. 637–640, Sep. 2007.
  15. ——, “Dynamic linear precoding for the exploitation of known interference in MIMO broadcast systems,” IEEE Trans. Wireless Commun., vol. 8, no. 3, pp. 1396–1404, Mar. 2009.
  16. C. Masouros, “Correlation rotation linear precoding for MIMO broadcast communications,” IEEE Trans. Signal Process., vol. 59, no. 1, pp. 252–262, Jan. 2011.
  17. M. Alodeh, S. Chatzinotas, and B. Ottersten, “Constructive multiuser interference in symbol level precoding for the MISO downlink channel,” IEEE Trans. Signal Process., vol. 63, no. 9, pp. 2239–2252, May 2015.
  18. C. Masouros and G. Zheng, “Exploiting known interference as green signal power for downlink beamforming optimization,” IEEE Trans. Signal Process., vol. 63, no. 14, pp. 3628–3640, Jul. 2015.
  19. A. Li, D. Spano, J. Krivochiza, S. Domouchtsidis, C. G. Tsinos, C. Masouros, S. Chatzinotas, Y. Li, B. Vucetic, and B. Ottersten, “A tutorial on interference exploitation via symbol-level precoding: Overview, state-of-the-art and future directions,” IEEE Commun. Surveys Tuts., vol. 22, no. 2, pp. 796–839, 2nd Quart. 2020.
  20. M. Alodeh, S. Chatzinotas, and B. Ottersten, “Energy-efficient symbol-level precoding in multiuser MISO based on relaxed detection region,” IEEE Trans. Wireless Commun., vol. 15, no. 5, pp. 3755–3767, May 2016.
  21. ——, “Symbol-level multiuser MISO precoding for multi-level adaptive modulation,” IEEE Trans. Wireless Commun., vol. 16, no. 8, pp. 5511–5524, Aug. 2017.
  22. A. Haqiqatnejad, F. Kayhan, and B. Ottersten, “Symbol-level precoding design based on distance preserving constructive interference regions,” IEEE Trans. Signal Process., vol. 66, no. 22, pp. 5817–5832, Nov. 2018.
  23. S. Domouchtsidis, C. G. Tsinos, S. Chatzinotas, and B. Ottersten, “Symbol-level precoding for low complexity transmitter architectures in large-scale antenna array systems,” IEEE Trans. Wireless Commun., vol. 18, no. 2, pp. 852–863, Feb. 2019.
  24. D. Spano, M. Alodeh, S. Chatzinotas, and B. Ottersten, “Symbol-level precoding for the nonlinear multiuser MISO downlink channel,” IEEE Trans. Signal Process., vol. 66, no. 5, pp. 1331–1345, Mar. 2018.
  25. M. Alodeh, D. Spano, A. Kalantari, C. G. Tsinos, D. Christopoulos, S. Chatzinotas, and B. Ottersten, “Symbol-level and multicast precoding for multiuser multiantenna downlink: A state-of-the-art, classification, and challenges,” IEEE Commun. Surveys Tuts., vol. 20, no. 3, pp. 1733–1757, 3rd Quart. 2018.
  26. R. Liu, M. Li, Q. Liu, A. L. Swindlehurst, and Q. Wu, “Intelligent reflecting surface based passive information transmission: A symbol-level precoding approach,” IEEE Trans. Veh. Technol., vol. 70, no. 7, pp. 6735–6749, Jul. 2021.
  27. R. Liu, M. Li, Q. Liu, and A. L. Swindlehurst, “Joint symbol-level precoding and reflecting designs for IRS-enhanced MU-MISO systems,” IEEE Trans. Wireless Commun., vol. 20, no. 2, pp. 798–811, Feb. 2021.
  28. A. Li, F. Liu, C. Masouros, Y. Li, and B. Vucetic, “Interference exploitation 1-bit massive MIMO precoding: A partial branch-and-bound solution with near-optimal performance,” IEEE Trans. Wireless Commun., vol. 19, no. 5, pp. 3474–3489, May 2020.
  29. A. Li, C. Masouros, A. L. Swindlehurst, and W. Yu, “1-bit massive MIMO transmission: Embracing interference with symbol-level precoding,” IEEE Commun. Mag., vol. 59, no. 5, pp. 121–127, May 2021.
  30. F. Liu, C. Masouros, A. Li, T. Ratnarajah, and J. Zhou, “MIMO radar and cellular coexistence: A power-efficient approach enabled by interference exploitation,” IEEE Trans. Signal Process., vol. 66, no. 14, pp. 3681–3695, Jul. 2018.
  31. R. Liu, M. Li, Q. Liu, and A. L. Swindlehurst, “Dual-functional radar-communication waveform design: A symbol-level precoding approach,” IEEE J. Sel. Topics Signal Process., vol. 15, no. 6, pp. 1316–1331, Nov. 2021.
  32. A. Li, C. Shen, X. Liao, C. Masouros, and A. L. Swindlehurst, “Practical interference exploitation precoding without symbol-by-symbol optimization: A block-level approach,” IEEE Trans. Wireless Commun., vol. 22, no. 6, pp. 3982–3996, Jun. 2023.
  33. Y. Liu, M. Shao, W.-K. Ma, and Q. Li, “Symbol-level precoding through the lens of zero forcing and vector perturbation,” IEEE Trans. Signal Process., vol. 70, pp. 1687–1703, Feb. 2022.
  34. J. Yang, A. Li, X. Liao, and C. Masouros, “Speeding-up symbol-level precoding using separable and dual optimizations,” IEEE Trans. Commun., vol. 71, no. 12, pp. 7056–7071, Aug. 2023.
  35. M. Damen, H. El Gamal, and G. Caire, “On maximum-likelihood detection and the search for the closest lattice point,” IEEE Trans. Inf. Theory, vol. 49, no. 10, pp. 2389–2402, Oct. 2003.
  36. S. Yang and L. Hanzo, “Fifty years of MIMO detection: The road to large-scale MIMOs,” IEEE Commun. Surveys Tuts., vol. 17, no. 4, pp. 1941–1988, 4th Quart. 2015.
Citations (2)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now