Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
133 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 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

Handoffs in User-Centric Cell-Free MIMO Networks: A POMDP Framework (2403.08900v1)

Published 13 Mar 2024 in cs.IT, cs.DC, cs.NI, cs.SY, eess.SP, eess.SY, and math.IT

Abstract: We study the problem of managing handoffs (HOs) in user-centric cell-free massive MIMO (UC-mMIMO) networks. Motivated by the importance of controlling the number of HOs and by the correlation between efficient HO decisions and the temporal evolution of the channel conditions, we formulate a partially observable Markov decision process (POMDP) with the state space representing the discrete versions of the large-scale fading and the action space representing the association decisions of the user with the access points (APs). We develop a novel algorithm that employs this model to derive a HO policy for a mobile user based on current and future rewards. To alleviate the high complexity of our POMDP, we follow a divide-and-conquer approach by breaking down the POMDP formulation into sub-problems, each solved separately. Then, the policy and the candidate pool of APs for the sub-problem that produced the best total expected reward are used to perform HOs within a specific time horizon. We then introduce modifications to our algorithm to decrease the number of HOs. The results show that half of the number of HOs in the UC-mMIMO networks can be eliminated. Namely, our novel solution can control the number of HOs while maintaining a rate guarantee, where a 47%-70% reduction of the cumulative number of HOs is observed in networks with a density of 125 APs per km2. Most importantly, our results show that a POMDP-based HO scheme is promising to control HOs.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (40)
  1. H. A. Ammar, R. Adve, S. Shahbazpanahi, G. Boudreau, and K. V. Srinivas, “POMDP-based handoffs for user-centric cell-free MIMO networks,” in GLOBECOM 2022 - 2022 IEEE Global Communications Conference, pp. 341–346, 2022.
  2. H. Q. Ngo, A. Ashikhmin, H. Yang, E. G. Larsson, and T. L. Marzetta, “Cell-free massive MIMO versus small cells,” IEEE Transactions on Wireless Communications, vol. 16, pp. 1834–1850, March 2017.
  3. E. Björnson and L. Sanguinetti, “Making cell-free massive MIMO competitive with MMSE processing and centralized implementation,” IEEE Transactions on Wireless Communications, vol. 19, no. 1, pp. 77–90, 2020.
  4. H. Q. Ngo, L.-N. Tran, T. Q. Duong, M. Matthaiou, and E. G. Larsson, “On the total energy efficiency of cell-free massive MIMO,” IEEE Transactions on Green Communications and Networking, vol. 2, no. 1, pp. 25–39, 2018.
  5. C. Zhu and W. Yu, “Stochastic modeling and analysis of user-centric network MIMO systems,” IEEE Transactions on Communications, vol. 66, no. 12, pp. 6176–6189, 2018.
  6. G. Interdonato, E. Björnson, H. Q. Ngo, P. Frenger, and E. G. Larsson, “Ubiquitous cell-free massive MIMO communications,” EURASIP Journal on Wireless Communications and Networking, vol. 2019, no. 1, pp. 1–13, 2019.
  7. H. A. Ammar, R. Adve, S. Shahbazpanahi, G. Boudreau, and K. V. Srinivas, “Downlink resource allocation in multiuser cell-free MIMO networks with user-centric clustering,” IEEE Trans. on Wireless Comm., vol. 21, no. 3, pp. 1482–1497, 2022.
  8. H. A. Ammar, R. Adve, S. Shahbazpanahi, G. Boudreau, and K. V. Srinivas, “Distributed resource allocation optimization for user-centric cell-free MIMO networks,” IEEE Trans. on Wireless Comm., vol. 21, no. 5, pp. 3099–3115, 2022.
  9. H. A. Ammar, R. Adve, S. Shahbazpanahi, G. Boudreau, and K. V. Srinivas, “User-centric cell-free massive MIMO networks: A survey of opportunities, challenges and solutions,” IEEE Communications Surveys & Tutorials, vol. 24, no. 1, pp. 611–652, 2022.
  10. C. D’Andrea, G. Interdonato, and S. Buzzi, “User-centric handover in mmwave cell-free massive MIMO with user mobility,” in 2021 29th European Signal Processing Conference (EUSIPCO), pp. 1–5, 2021.
  11. M. Zaher, E. Björnson, and M. Petrova, “Soft handover procedures in mmWave cell-free massive MIMO networks,” IEEE Transactions on Wireless Communications, pp. 1–1, 2023.
  12. R. Beerten, V. Ranjbar, A. P. Guevara, and S. Pollin, “Cell-free massive MIMO in the O-RAN architecture: Cluster and handover strategies,” arXiv preprint arXiv:2301.07618, 2023.
  13. H. A. Ammar and R. Adve, “Power delay profile in coordinated distributed networks: User-centric v/s disjoint clustering,” in 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 1–5, Nov 2019.
  14. H. Li, Y. Wang, C. Sun, and Z. Wang, “User-centric cell-free massive mimo for iot in highly dynamic environments,” IEEE Internet of Things Journal, pp. 1–1, 2023.
  15. J. Zheng, J. Zhang, E. Björnson, and B. Ai, “Cell-free massive MIMO with channel aging and pilot contamination,” in GLOBECOM 2020 - 2020 IEEE Global Communications Conference, pp. 1–6, 2020.
  16. K. T. Truong and R. W. Heath, “Effects of channel aging in massive MIMO systems,” Journal of Communications and Networks, vol. 15, no. 4, pp. 338–351, 2013.
  17. J. Zheng, J. Zhang, E. Björnson, and B. Ai, “Impact of channel aging on cell-free massive MIMO over spatially correlated channels,” IEEE Transactions on Wireless Communications, vol. 20, no. 10, pp. 6451–6466, 2021.
  18. H. A. Ammar, R. Adve, S. Shahbazpanahi, G. Boudreau, and K. Srinivas, “Resource allocation and scheduling in non-coherent user-centric cell-free MIMO,” in ICC 2021 - IEEE International Conference on Communications, pp. 1–6, 2021.
  19. W. Jiang and H. D. Schotten, “Impact of channel aging on zero-forcing precoding in cell-free massive MIMO systems,” IEEE Communications Letters, pp. 1–1, 2021.
  20. R. Chopra, C. R. Murthy, H. A. Suraweera, and E. G. Larsson, “Performance analysis of FDD massive MIMO systems under channel aging,” IEEE Transactions on Wireless Communications, vol. 17, no. 2, pp. 1094–1108, 2018.
  21. V. Krishnamurthy, Partially observed Markov decision processes. Cambridge university press, 2016.
  22. S. Sharifi, S. Shahbazpanahi, and M. Dong, “A POMDP-based antenna selection for massive MIMO communication,” IEEE Transactions on Communications, vol. 70, no. 3, pp. 2025–2041, 2022.
  23. G. Shani, J. Pineau, and R. Kaplow, “A survey of point-based POMDP solvers,” Autonomous Agents and Multi-Agent Systems, vol. 27, no. 1, pp. 1–51, 2013.
  24. W. S. Lovejoy, “A survey of algorithmic methods for partially observed markov decision processes,” Annals of Operations Research, vol. 28, no. 1, pp. 47–65, 1991.
  25. R. D. Smallwood and E. J. Sondik, “The optimal control of partially observable markov processes over a finite horizon,” Operations Research, vol. 21, no. 5, pp. 1071–1088, 1973.
  26. E. J. Sondik, “The optimal control of partially observable markov processes over the infinite horizon: Discounted costs,” Operations research, vol. 26, no. 2, pp. 282–304, 1978.
  27. J. Pineau, G. Gordon, S. Thrun, et al., “Point-based value iteration: An anytime algorithm for POMDPs,” in IJCAI, vol. 3, pp. 1025–1032, Citeseer, 2003.
  28. C. J. Watkins and P. Dayan, “Q-learning,” Machine learning, vol. 8, pp. 279–292, 1992.
  29. A. Slivkins et al., “Introduction to multi-armed bandits,” Foundations and Trends® in Machine Learning, vol. 12, no. 1-2, pp. 1–286, 2019.
  30. O. Madani, S. Hanks, and A. Condon, “On the undecidability of probabilistic planning and infinite-horizon partially observable markov decision problems,” in AAAI/IAAI, pp. 541–548, 1999.
  31. P. Frenger, J. Hederen, M. Hessler, and G. Interdonato, “Antenna arrangement for distributed massive MIMO,” Aug. 18 2022. US Patent App. 17/736,550.
  32. W. C. Jakes and D. C. Cox, Microwave mobile communications. Wiley-IEEE Press, 1994.
  33. H. A. Ammar, R. Adve, S. Shahbazpanahi, and G. Boudreau, “Statistical analysis of downlink zero-forcing beamforming,” IEEE Wireless Communications Letters, vol. 9, no. 11, pp. 1965–1969, 2020.
  34. E. J. Sondik, The optimal control of partially observable Markov processes. Stanford University, 1971.
  35. A. Condon, “The complexity of stochastic games,” Information and Computation, vol. 96, no. 2, pp. 203–224, 1992.
  36. https://cran.r-project.org/web/packages/pomdp/index.html.
  37. Z. Wang, E. K. Tameh, and A. R. Nix, “Joint shadowing process in urban peer-to-peer radio channels,” IEEE Trans. on Vehicular Technology, vol. 57, no. 1, pp. 52–64, 2008.
  38. M. Gudmundson, “Correlation model for shadow fading in mobile radio systems,” Electronics Letters, vol. 27, no. 23, pp. 2145–2146, 1991.
  39. S. Buzzi, C. D’Andrea, A. Zappone, and C. D’Elia, “User-centric 5G cellular networks: Resource allocation and comparison with the cell-free massive MIMO approach,” IEEE Trans. on Wireless Comm., vol. 19, pp. 1250–1264, Feb 2020.
  40. J. Walfisch and H. L. Bertoni, “A theoretical model of UHF propagation in urban environments,” IEEE Transactions on Antennas and Propagation, vol. 36, pp. 1788–1796, Dec 1988.
Citations (1)
View on Semantic Scholar

Summary

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

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