Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
162 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

Cooperative ISAC Networks: Performance Analysis, Scaling Laws and Optimization (2404.14514v3)

Published 22 Apr 2024 in cs.IT, eess.SP, and math.IT

Abstract: Integrated sensing and communication (ISAC) networks are investigated with the objective of effectively balancing the sensing and communication (S&C) performance at the network level. Through the simultaneous utilization of multi-point (CoMP) coordinated joint transmission and distributed multiple-input multiple-output (MIMO) radar techniques, we propose an innovative networked ISAC scheme, where multiple transceivers are employed for collaboratively enhancing the S&C services. Then, the potent tool of stochastic geometry is exploited for characterizing the S&C performance, which allows us to illuminate the key cooperative dependencies in the ISAC network and optimize salient network-level parameters. Remarkably, the Cramer-Rao lower bound (CRLB) expression of the localization accuracy derived unveils a significant finding: Deploying N ISAC transceivers yields an enhanced average cooperative sensing performance across the entire network, in accordance with the ln2N scaling law. Crucially, this scaling law is less pronounced in comparison to the performance enhancement of N2 achieved when the transceivers are equidistant from the target, which is primarily due to the substantial path loss from the distant base stations (BSs) and leads to reduced contributions to sensing performance gain. Moreover, we derive a tight expression of the communication rate, and present a low-complexity algorithm to determine the optimal cooperative cluster size. Based on our expression derived for the S&C performance, we formulate the optimization problem of maximizing the network performance in terms of two joint S&C metrics. To this end, we jointly optimize the cooperative BS cluster sizes and the transmit power to strike a flexible tradeoff between the S&C performance.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (42)
  1. K. Meng and C. Masouros, “Cooperative sensing and communication for ISAC networks: Performance analysis and optimization,” arXiv preprint arXiv:2403.20228, 2024.
  2. A. Liu et al., “A survey on fundamental limits of integrated sensing and communication,” IEEE Commun. Surveys Tuts., vol. 24, no. 2, pp. 994–1034, Nov. 2022.
  3. J. A. Zhang et al., “An overview of signal processing techniques for joint communication and radar sensing,” IEEE J. Sel. Top. Signal Process., vol. 15, no. 6, pp. 1295–1315, 2021.
  4. K. V. Mishra et al., “Toward millimeter-wave joint radar communications: A signal processing perspective,” IEEE Signal Proces. Mag., vol. 36, no. 5, pp. 100–114, Sep. 2019.
  5. K. Meng, C. Masouros, K.-K. Wong, A. P. Petropulu, and L. Hanzo, “Integrated sensing and communication meets smart propagation engineering: Opportunities and challenges,” arXiv preprint arXiv:2402.18683, 2024.
  6. Y. Cui, F. Liu, X. Jing, and J. Mu, “Integrating sensing and communications for ubiquitous IoT: Applications, trends, and challenges,” IEEE Net., vol. 35, no. 5, pp. 158–167, Sep./Oct. 2021.
  7. C. Ouyang, Y. Liu, and H. Yang, “Performance of downlink and uplink integrated sensing and communications (ISAC) systems,” IEEE Wireless Commun. Lett., vol. 11, no. 9, pp. 1850–1854, Sep. 2022.
  8. K. Meng et al., “Throughput maximization for UAV-enabled integrated periodic sensing and communication,” IEEE Trans. Wireless Commun., vol. 22, no. 1, pp. 671–687, Jan. 2023.
  9. M. Hua, Q. Wu, W. Chen, and A. Jamalipour, “Integrated sensing and communication: Joint pilot and transmission design,” arXiv preprint arXiv:2211.12891, 2022.
  10. K. Meng, Q. Wu, W. Chen, and D. Li, “Sensing-assisted communication in vehicular networks with intelligent surface,” IEEE Trans. Veh. Technol., pp. 1–17, 2023.
  11. N. Babu, C. Masouros, C. B. Papadias, and Y. C. Eldar, “Precoding for multi-cell ISAC: from coordinated beamforming to coordinated multipoint and bi-static sensing,” arXiv preprint arXiv:2402.18387, 2024.
  12. R. Li, Z. Xiao, and Y. Zeng, “Towards seamless sensing coverage for cellular multi-static integrated sensing and communication,” IEEE Trans. Wireless Commun., pp. 1–1, 2023.
  13. W. Shin, M. Vaezi, B. Lee, D. J. Love, J. Lee, and H. V. Poor, “Coordinated beamforming for multi-cell MIMO-NOMA,” IEEE Commun. Lett., vol. 21, no. 1, pp. 84–87, Jan. 2017.
  14. K. Hosseini, W. Yu, and R. S. Adve, “A stochastic analysis of network MIMO systems,” IEEE Trans. Signal Process., vol. 64, no. 16, pp. 4113–4126, Aug. 2016.
  15. J. G. Andrews, F. Baccelli, and R. K. Ganti, “A tractable approach to coverage and rate in cellular networks,” IEEE Trans. Commun., vol. 59, no. 11, pp. 3122–3134, Nov. 2011.
  16. H.-S. Jo, Y. J. Sang, P. Xia, and J. G. Andrews, “Heterogeneous cellular networks with flexible cell association: A comprehensive downlink SINR analysis,” IEEE Trans. Wireless Commun., vol. 11, no. 10, pp. 3484–3495, Oct. 2012.
  17. G. Chen, L. Qiu, and Y. Li, “Stochastic geometry analysis of coordinated beamforming small cell networks with CSI delay,” IEEE Commun. Lett., vol. 22, no. 5, pp. 1066–1069, May 2018.
  18. H. Wei, N. Deng, and M. Haenggi, “Performance analysis of inter-cell interference coordination in mm-wave cellular networks,” IEEE Trans. Wireless Commun., vol. 21, no. 2, pp. 726–738, Feb. 2021.
  19. A. Al-Hourani et al., “Stochastic geometry methods for modeling automotive radar interference,” IEEE Trans. Intell. Transp. Syst., vol. 19, no. 2, pp. 333–344, Feb. 2017.
  20. Y. Wang, Q. Zhang, Z. Wei, Y. Lin, and Z. Feng, “Performance analysis of coordinated interference mitigation approach for automotive radar,” vol. 10, no. 13, pp. 11 683–11 695, Jul. 2023.
  21. J. D. Roth, M. Tummala, and J. C. McEachen, “Fundamental implications for location accuracy in ultra-dense 5G cellular networks,” IEEE Trans. Veh. Technol., vol. 68, no. 2, pp. 1784–1795, Feb. 2019.
  22. J. Schloemann, H. S. Dhillon, and R. M. Buehrer, “Toward a tractable analysis of localization fundamentals in cellular networks,” IEEE Trans. Wireless Commun., vol. 15, no. 3, pp. 1768–1782, 2016.
  23. W. Chen, L. Li, Z. Chen, B. Ning, G. Wang, and T. Quek, “An ISAC-based beam alignment approach for enhancing terahertz network coverage,” arXiv preprint arXiv:2212.01728, 2022.
  24. S. S. Ram, S. Singhal, and G. Ghatak, “Optimization of network throughput of joint radar communication system using stochastic geometry,” Frontiers in Signal Processing, vol. 2, Apr. 2022.
  25. K. Meng, C. Masouros, G. Chen, and F. Liu, “Network-level integrated sensing and communication: Interference management and BS coordination using stochastic geometry,” arXiv preprint arXiv:2311.09052, 2023.
  26. Y. Eldar, “Uniformly improving the CramÉr-Rao bound and maximum-likelihood estimation,” IEEE Trans. Signal Process., vol. 54, no. 8, pp. 2943–2956, 2006.
  27. S. Lu et al., “Integrated sensing and communications: Recent advances and ten open challenges,” IEEE Internet Things J., pp. 1–1, 2024.
  28. J. Ghimire and C. Rosenberg, “Revisiting scheduling in heterogeneous networks when the backhaul is limited,” IEEE J. Sel. Areas Commun., vol. 33, no. 10, pp. 2039–2051, 2015.
  29. N. R. Olson, J. G. Andrews, and R. W. Heath Jr, “Coverage and capacity of joint communication and sensing in wireless networks,” arXiv preprint arXiv:2210.02289, 2022.
  30. A. Salem, K. Meng, C. Masouros, F. Liu, and D. López-Pérez, “Rethinking dense cells for integrated sensing and communications: A stochastic geometric view,” arXiv preprint arXiv:2212.12942, 2022.
  31. X. Liu, T. Huang, N. Shlezinger, Y. Liu, J. Zhou, and Y. C. Eldar, “Joint transmit beamforming for multiuser MIMO communications and MIMO radar,” IEEE Trans. Signal Process., vol. 68, pp. 3929–3944, 2020.
  32. H. Hua, J. Xu, and T. X. Han, “Optimal transmit beamforming for integrated sensing and communication,” IEEE Trans. Veh. Technol., vol. 72, no. 8, pp. 10 588–10 603, 2023.
  33. M. Sadeghi, F. Behnia, R. Amiri, and A. Farina, “Target localization geometry gain in distributed MIMO radar,” IEEE Trans. Signal Process., vol. 69, pp. 1642–1652, 2021.
  34. J. Li and R. Compton, “Maximum likelihood angle estimation for signals with known waveforms,” IEEE Trans. Signal Process., vol. 41, no. 9, pp. 2850–2862, 1993.
  35. M. I. Skolnik, “Introduction to radar systems,” New York, 1980.
  36. J. Park, N. Lee, J. G. Andrews, and R. W. Heath, “On the optimal feedback rate in interference-limited multi-antenna cellular systems,” IEEE Trans. Wireless Commun., vol. 15, no. 8, pp. 5748–5762, Aug. 2016.
  37. Q. Zhang, C. Yang, and A. F. Molisch, “Downlink base station cooperative transmission under limited-capacity backhaul,” IEEE Trans. Wireless Commun., vol. 12, no. 8, pp. 3746–3759, 2013.
  38. I. Guvenc and C.-C. Chong, “A survey on TOA based wireless localization and NLOS mitigation techniques,” IEEE Commun. Surveys Tuts., vol. 11, no. 3, pp. 107–124, 2009.
  39. C. Li, J. Zhang, M. Haenggi, and K. B. Letaief, “User-centric intercell interference nulling for downlink small cell networks,” IEEE Trans. Commun., vol. 63, no. 4, pp. 1419–1431, 2015.
  40. K. A. Hamdi, “A useful lemma for capacity analysis of fading interference channels,” IEEE Trans. Commun., vol. 58, no. 2, pp. 411–416, Feb. 2010.
  41. H. Tuy, “Monotonic optimization: Problems and solution approaches,” SIAM J. Optim., vol. 11, no. 2, pp. 464–494, 2000.
  42. X. Zhang and M. Haenggi, “A stochastic geometry analysis of inter-cell interference coordination and intra-cell diversity,” IEEE Trans. Wireless Commun., vol. 13, no. 12, pp. 6655–6669, Dec. 2014.
Citations (4)
View on Semantic Scholar

Summary

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

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