Feedback Reduction for Multiuser MIMO Broadcast Channel with Zero-Forcing Beamforming

A multi-user multiple-input multiple-output (MU-MIMO) downlink system with zero-forcing beamforming and semi-orthogonal user selection (SUS) scheduling algorithm is considered in this paper. It is well known that in practical implementation of MU-MIMO, the channel state information (CSI) feedback overhead becomes a limiting factor as the number of users to be supported increases. A novel scheme to reduce the feedback load, in the event of large number of users, by using a threshold-based feedback strategy is proposed and studied in this paper. The key feature of the proposed approach uses the concept of order statistics to construct multiple thresholds on the CSI. This paper also proposes a new modified formulation of the expected signal to interference plus noise ratio (SINR) to address the mismatch of analytical sum rate and simulation results. Simulation results show a significant reduction of feedback load when the scheme is used, while the sum rate performance is not compromised.

[1]  Max H. M. Costa,et al.  Writing on dirty paper , 1983, IEEE Trans. Inf. Theory.

[2]  David Gesbert,et al.  Adaptive feedback rate control in MIMO broadcast systems , 2008, 2008 IEEE Information Theory Workshop.

[3]  Federico Boccardi,et al.  User Selection Schemes for MIMO Broadcast Channels with Limited Feedback , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[4]  Jinhong Yuan,et al.  A Lower Bound to the Sum-Rate of MIMO Broadcast Channels with Limited-Rate Feedback , 2008, 2008 IEEE International Conference on Communications.

[5]  Nihar Jindal,et al.  MIMO broadcast channels with finite rate feedback , 2006, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[6]  Babak Hassibi,et al.  On the capacity of MIMO broadcast channels with partial side information , 2005, IEEE Transactions on Information Theory.

[7]  Jeffrey G. Andrews,et al.  Space Division Multiple Access With a Sum Feedback Rate Constraint , 2007, IEEE Transactions on Signal Processing.

[8]  Andrea J. Goldsmith,et al.  Multi-Antenna Downlink Channels with Limited Feedback and User Selection , 2007, IEEE Journal on Selected Areas in Communications.

[9]  Hsuan-Jung Su,et al.  Opportunistic Feedback Reduction for Multiuser MIMO Broadcast Channel with Orthogonal Beamforming , 2014, IEEE Transactions on Wireless Communications.

[10]  David Gesbert,et al.  A Two-Stage Approach to Feedback Design in Multi-User MIMO Channels with Limited Channel State Information , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[11]  Mohamed-Slim Alouini,et al.  How much feedback is multi-user diversity really worth? , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[12]  Marios Kountouris.  Multiuser Multi-Antenna Systems with Limited Feedback , 2008 .

[13]  Kwang Bok Lee,et al.  Dynamic Channel Feedback Control for Limited-Feedback Multi-User MIMO Systems , 2009, 2009 IEEE International Conference on Communications.

[14]  Andrea J. Goldsmith,et al.  On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming , 2006, IEEE Journal on Selected Areas in Communications.