Abstract
In this paper the scheduling problem in downlink multiuser MIMO system is described as an optimization problem and particle swarm optimization (PSO) algorithm is introduced to address such problem. Two PSO scheduling methods with different objective functions applicable to different requirements on capacity and complexity are investigated. One is the capacity based PSO(C-PSO) scheduling method aiming at achieving the near optimal capacity; and the other is the lower bound of eigenvalue based PSO (LBE-PSO) scheduling method with the purpose of reducing computational complexity and at the same time achieving as large as possible capacity gain. Furthermore, convergence analysis of PSO from both the particle and the velocity aspects is also presented to derive the convergent condition, which is validated by several examples of different parameter values. Simulation results reveal that the C-PSO can obtain nearly the same capacity as the exhaustive search method with lower complexity, while the LBE-PSO provides a viable approach by striking a better tradeoff between capacity and computational complexity.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Maciel T F, Klein A. A low-complexity SDMA grouping strategy for the downlink of multiuser MIMO systems. In: Proc of the 17th IEEE Personal, Indoor and Mob. Radio Commun. (PIMRC), Helsinki, Finland, 2006. 1–5
Fuchs M, Galdo G D, Haardt M. A novel tree-based scheduling algorithm for the downlink of multi-user MIMO systems with ZF beamforming. IEEE Int Conf Acoust Speech Signal Proc, 2005, 12(3): 1121–1124
Spencer Q, Swindlehurst A L. Channel allocation in multiuser MIMO wireless communications system. IEEE Int Conf Commun, 2004, 24(5): 3035–3039
Tuan Z Y, Kang Z J. An improved norm-based user selection algorithm for multiuser MIMO systems with block diagonalization. In: IEEE 66th Vehicular Technology Conference, 2007. 601–605
Bayesteh A, Khandani A K. On the user selection for MIMO broadcast channels. IEEE Trans Inf Theory, 2008, 54(3): 1086–1107
Pedersen K I, Andersen J B. A stochastic multiple-input-multiple-output radio channel model for evaluation of spacetime coding algorithms. In: IEEE 52nd Vehicular Technology Conference, Boston USA, 2000. 893–897
Kennedy J, Eberhart R C. Particle swarm optimization. IEEE Int Conf Neural Networks, 1995, 5(3): 1942–1948
Meyer C D. Matrix Analysis and Applied Linear Algebra. Philadelphia: SIAM, 2000
Clerc M, Kennedy J. The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans Evolut Comput, 2002, 6(1): 58–73
Golub G H, Van Loan C F. Matrix Computations. Baltimore, MD: The John Hopkins Univ. Press, 1996
Coppersmith D, Winograd S. Matrix Multiplication via Arithmetic Progressions. Duluth, MN: Academic Press, 1990
Author information
Authors and Affiliations
Corresponding author
Additional information
Supported by the National Natural Science Foundation of China (Grant Nos. 60572148, 60702060), the “111 Project” (Grant No. B08038), the Special Project of ISN (Grant No. ISN03080005), the National Key Project of New Generation Broad Band Wireless Mobile Communication Network (Grant No. 2009ZX03003-005)
Rights and permissions
About this article
Cite this article
Hei, Y., Li, X., Yi, K. et al. Novel scheduling strategy for downlink multiuser MIMO system: Particle swarm optimization. Sci. China Ser. F-Inf. Sci. 52, 2279–2289 (2009). https://doi.org/10.1007/s11432-009-0212-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11432-009-0212-8