Energy-Efficient Configuration of Spatial and Frequency Resources in MIMO-OFDMA Systems

In this paper, we investigate adaptive configuration of spatial and frequency resources to maximize energy efficiency (EE) and reveal the relationship between the EE and the spectral efficiency (SE) in downlink multiple-input-multiple-output (MIMO) orthogonal frequency division multiple access (OFDMA) systems. We formulate the problem as minimizing the total power consumed at the base station under constraints on the ergodic capacities from multiple users, the total number of subcarriers, and the number of radio frequency (RF) chains. A three-step searching algorithm is developed to solve this problem. We then analyze the impact of spatial-frequency resources, overall SE requirement and user fairness on the SE-EE relationship. Analytical and simulation results show that increasing frequency resource is more efficient than increasing spatial resource to improve the SE-EE relationship as a whole. The EE increases with the SE when the frequency resource is not constrained to the maximum value, otherwise a tradeoff between the SE and the EE exists. Sacrificing the fairness among users in terms of ergodic capacities can enhance the SE-EE relationship. In general, the adaptive configuration of spatial and frequency resources outperforms the adaptive configuration of only spatial or frequency resource.

[1]  Ashutosh Sabharwal,et al.  Adaptive RF chain management for energy-efficient spatial-multiplexing MIMO transmission , 2009, ISLPED.

[2]  Gustavo de Veciana,et al.  A cross-layer approach to energy efficiency for adaptive MIMO systems exploiting spare capacity , 2009, IEEE Transactions on Wireless Communications.

[3]  Vasilis Friderikos,et al.  Green spectrum management for mobile operators , 2010, 2010 IEEE Globecom Workshops.

[4]  Liesbet Van der Perre,et al.  SmartMIMO: An Energy-Aware Adaptive MIMO-OFDM Radio Link Control for Next-Generation Wireless Local Area Networks , 2007, EURASIP J. Wirel. Commun. Netw..

[5]  Cong Xiong,et al.  Energy-efficient wireless communications: tutorial, survey, and open issues , 2011, IEEE Wireless Communications.

[6]  Mokhtar S. Bazaraa,et al.  Nonlinear Programming: Theory and Algorithms , 1993 .

[7]  Geoffrey Ye Li,et al.  Fundamental trade-offs on green wireless networks , 2011, IEEE Communications Magazine.

[8]  Gerhard Fettweis,et al.  Energy-Efficient Multi-Carrier Link Adaptation with Sum Rate-Dependent Circuit Power , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[9]  Yan Chen,et al.  Improving Energy Efficiency through Bandwidth, Power, and Adaptive Modulation , 2010, 2010 IEEE 72nd Vehicular Technology Conference - Fall.

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

[11]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[12]  Babak Daneshrad,et al.  Energy-Constrained Link Adaptation for MIMO OFDM Wireless Communication Systems , 2010, IEEE Transactions on Wireless Communications.

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

[14]  Andrea J. Goldsmith,et al.  Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks , 2004, IEEE Journal on Selected Areas in Communications.