Abstract
This chapter investigates a multiuser multicell system where block-diagonalization (BD) precoding is utilized on a per-cell basis under two operating modes: competition and coordination. In the competition mode, the precoding design in the multicell system can be considered a strategic non-cooperative game (SNG), where each base-station (BS) greedily determines its BD precoding strategy in a distributed manner, based on the knowledge of the inter-cell interference at its connected mobile-stations (MS). Via the game-theory framework, the existence and uniqueness of a Nash equilibrium in this SNG are subsequently studied. In the coordination mode, the BD precoders are jointly designed across the multiple BSs to maximize the network weighted sum-rate (WSR). Since this WSR maximization problem is nonconvex, this chapter proposes a distributed algorithm to obtain at least a locally optimal solution. Finally, the analysis of the multicell BD precoding is extended to to the case of BD-Dirty Paper Coding (BD-DPC) precoding. Simulation results show significant network sum-rate improvements by jointly designing the BD or BD-DPC precoders across the multicell system in the coordination mode over the competition mode.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
To optimize the DPC in a multicell system under the IC mode, the numerical algorithm presented in Chap. 7 is utilized.
References
An, L.: D.C. programming for solving a class of global optimization problems via reformulation by exact penalty. In: C. Bliek, C. Jermann, A. Neumaier (eds.) Global Optimization and Constraint Satisfaction, Lecture Notes in Computer Science, vol. 2861, pp. 87–101. Springer Berlin / Heidelberg (2003)
Bertsekas, D.P., Tsitsiklis, J.N.: Parallel and Distributed Computation: Numerical Methods. Prentice-Hall, New Jersey (1989)
Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, United Kingdom (2004)
Caire, G., Shamai, S.: On the achievable throughput of a multiantenna Gaussian broadcast channel. IEEE Trans. Inform. Theory 49(7), 1691–1706 (2003)
Choi, L.U., Murch, R.: A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach. IEEE Trans. Wireless Commun. 3(1), 20–24 (2004)
Costa, M.: Writing on dirty paper. IEEE Trans. Inform. Theory 29(3), 439–441 (1983)
Dubey, P.: Inefficiency of Nash equilibria. Math. Oper. Res. 11(1), 1–8 (1986)
Horn, R.A., Johnson, C.R.: Matrix Analysis. Cambridge University Press, New York (1985)
Kim, S.J., Giannakis, G.B.: Optimal resource allocation for MIMO ad hoc cognitive radio networks. IEEE Trans. Inform. Theory 57(5), 3117–3131 (2011)
Larsson, E., Jorswieck, E.: Competition versus cooperation on the MISO interference channel. IEEE J. Select. Areas in Commun. 26(7), 1059–1069 (2008)
Marsch, P., Fettweis, G.: Coordinated Multi-point in Mobile Communications: From Theory to Practice. Cambridge University Press, New York: USA (2011)
Nguyen, D.H.N., Le-Ngoc, T.: Multiuser downlink beamforming in multicell wireless systems: A game theoretical approach. IEEE Trans. Signal Process. 59(7), 3326–3338 (2011)
Nguyen, D.H.N., Nguyen-Le, H., Le-Ngoc, T.: Block-diagonalization precoding in a multiuser multicell MIMO system: Competition and coordination. IEEE Trans. Wireless Commun. 13(2), 968–981 (2014)
Nguyen-Le, H., Nguyen, D.H.N., Le-Ngoc, T.: Game-based zero-forcing precoding for multicell multiuser transmissions. In: Proc. IEEE Veh. Technol. Conf., pp. 1–5. San Francisco, CA, USA (2011)
Pan, Z., Wong, K.K., Ng, T.S.: Generalized multiuser orthogonal space-division multiplexing. IEEE Trans. Wireless Commun. 3(6), 1969–1973 (2004)
Rosen, J.B.: Existence and uniqueness of equilibrium points for concave N-person games. Econometrica 33(3), 520–534 (1965)
Scutari, G., Palomar, D.P., Barbarossa, S.: Competitive design of multiuser MIMO system based on game theory: a unified view. IEEE J. Select. Areas in Commun. 26(9), 1089–1102 (2008)
Scutari, G., Palomar, D.P., Barbarossa, S.: The MIMO iterative waterfilling algorithm. IEEE Trans. Signal Process. 57(5), 1917–1935 (2009)
Shen, Z., Chen, R., Andrews, J., Heath, R., Evans, B.: Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization. IEEE Trans. Signal Process. 54(9), 3658–3663 (2006)
Spencer, Q., Swindlehurst, A., Haardt, M.: Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels. IEEE Trans. Signal Process. 52(2), 461–471 (2004)
Vishwanath, S., Jindal, N., Goldsmith, A.: Duality, achievable rates and sum-rate capacity of Gaussian MIMO broadcast channels. IEEE Trans. Inform. Theory 49(10), 2658–2668 (2003)
Wong, K.K., Murch, R., Letaief, K.: A joint-channel diagonalization for multiuser MIMO antenna systems. IEEE Trans. Wireless Commun. 2(4), 773–786 (2003)
Ye, S., Blum, R.S.: Optimized signaling for MIMO interference systems with feedback. IEEE Trans. Signal Process. 51(11), 2839–2848 (2003)
Yoo, T., Goldsmith, A.: On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming. IEEE J. Select. Areas in Commun. 24(3), 528–541 (2006)
Yu, W., Cioffi, J.: Sum capacity of Gaussian vector broadcast channels. IEEE Trans. Inform. Theory 50(9), 1875–1892 (2004)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 The Author(s)
About this chapter
Cite this chapter
Nguyen, D.H.N., Le-Ngoc, T. (2014). Block-Diagonalization Precoding in Multiuser Multicell MIMO Systems. In: Wireless Coordinated Multicell Systems. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-06337-9_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-06337-9_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06336-2
Online ISBN: 978-3-319-06337-9
eBook Packages: Computer ScienceComputer Science (R0)