Energy-efficient scheduling for downlink multi-user MIMO

Multi-user MIMO is the enabling technology for LTE-Advanced systems to meet IMT-Advanced targets. The gain of multi-user MIMO is achieved partially through advanced user-grouping, user-scheduling, and precoding. Traditionally, multiuser MIMO scheduling focuses solely on spectral-efficiency [1]. That is, the scheduler will strike to balance the cell-edge user spectral-efficiency as well as the cell-average spectral-efficiency. Similar to spectral-efficiency, energy-efficiency is becoming increasingly important for wireless communications. The energy efficiency is measured by a classical measure, “throughput per Joule”, while both RF transmit power and device electronic circuit power consumptions are considered. In this paper, an energy-efficient proportional-fair scheduling is proposed for downlink multi-user MIMO systems. To specific, the scheduling algorithm is proposed to balance cell-edge energy-efficiency and the cell-average energy-efficiency. The energy-efficient proportional-fair metric is defined and the optimal power allocation maximizing the performance measure is identified. System level evaluation suggests that multi-user MIMO could improve the energy-efficiency of a wireless communication system significantly.

[1]  Sergio Verdú,et al.  Spectral efficiency in the wideband regime , 2002, IEEE Trans. Inf. Theory.

[2]  Andrea J. Goldsmith,et al.  Energy-constrained modulation optimization , 2005, IEEE Transactions on Wireless Communications.

[3]  Jianzhong Zhang,et al.  Proportional fair scheduling for multi-cell multi-user MIMO systems , 2010, 2010 44th Annual Conference on Information Sciences and Systems (CISS).

[4]  Guidelines for evaluation of radio interface technologies for IMT-Advanced , 2008 .

[5]  A. Raghunathan,et al.  Battery-driven system design: a new frontier in low power design , 2002, Proceedings of ASP-DAC/VLSI Design 2002. 7th Asia and South Pacific Design Automation Conference and 15h International Conference on VLSI Design.

[6]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[7]  Elmar Wolfstetter,et al.  Topics in microeconomics - industrial organization, auctions, and incentives (repr.) , 1999 .

[8]  Shlomo Shamai,et al.  The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel , 2006, IEEE Transactions on Information Theory.

[9]  Geoffrey Ye Li,et al.  Energy-efficient link adaptation in frequency-selective channels , 2010, IEEE Transactions on Communications.

[10]  SeongHwan Cho,et al.  Energy efficient modulation and MAC for asymmetric RF microsensor systems , 2001, ISLPED'01: Proceedings of the 2001 International Symposium on Low Power Electronics and Design (IEEE Cat. No.01TH8581).

[11]  Elmar G. Wolfstetter.  Topics in Microeconomics: Technical Supplements , 1999 .

[12]  Elmar Wolfstetter.  Topics in Microeconomics: Frontmatter , 1999 .

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

[14]  H. Vincent Poor,et al.  An energy-efficient approach to power control and receiver design in wireless data networks , 2005, IEEE Transactions on Communications.