Energy efficient coordinated beamforming for multi-cell MISO systems

In this paper, we investigate the optimal energy efficient coordinated beamforming in multi-cell multiple-input single-output (MISO) systems with K multiple-antenna base stations (BS) and K single-antenna mobile stations (MS), where each BS sends information to its own intended MS with cooperatively designed transmit beamforming. We assume single user detection at the MS by treating the interference as noise. By taking into account a realistic power model at the BS, we characterize the Pareto boundary of the achievable energy efficiency (EE) region of the K links, where the EE of each link is defined as the achievable data rate at the MS divided by the total power consumption at the BS. Since the EE of each link is non-cancave (which is a non-concave function over an affine function), characterizing this boundary is difficult. To meet this challenge, we relate this multi-cell MISO system to cognitive radio (CR) MISO channels by applying the concept of interference temperature (IT), and accordingly transform the EE boundary characterization problem into a set of fractional concave programming problems. Then, we apply the fractional concave programming technique to solve these fractional concave problems, and correspondingly give a parametrization for the EE boundary in terms of IT levels. Based on this characterization, we further present a decentralized algorithm to implement the multi-cell coordinated beamforming, which is shown by simulations to achieve the EE Pareto boundary.

[1]  Ling Qiu,et al.  Energy Efficiency Optimization for MIMO Broadcast Channels , 2012, IEEE Trans. Wirel. Commun..

[2]  Chenyang Yang,et al.  On the energy efficiency of base station sleeping with multicell cooperative transmission , 2011, 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications.

[3]  Wei Yu,et al.  Coordinated beamforming for the multi-cell multi-antenna wireless system , 2008, 2008 42nd Annual Conference on Information Sciences and Systems.

[4]  Leonard J. Cimini,et al.  Energy-efficient transmission for MIMO interference channels , 2013, IEEE Transactions on Wireless Communications.

[5]  Siegfried Schaible Fractional programming , 1983, Z. Oper. Research.

[6]  Ling Qiu,et al.  Improving network energy efficiency through cooperative idling in the multi-cell systems , 2011, EURASIP J. Wirel. Commun. Netw..

[7]  Cong Xiong,et al.  Energy- and Spectral-Efficiency Tradeoff in Downlink OFDMA Networks , 2011, IEEE Transactions on Wireless Communications.

[8]  Shuguang Cui,et al.  Cooperative Interference Management in Multi-Cell Downlink Beamforming , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[9]  Gerhard Fettweis,et al.  Framework for Link-Level Energy Efficiency Optimization with Informed Transmitter , 2011, IEEE Transactions on Wireless Communications.

[10]  Erik G. Larsson,et al.  Complete Characterization of the Pareto Boundary for the MISO Interference Channel , 2008, IEEE Transactions on Signal Processing.

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

[12]  Jie Xu,et al.  Energy Efficiency Optimization for MIMO Broadcast Channels , 2013, IEEE Transactions on Wireless Communications.

[13]  Gerhard Fettweis,et al.  Framework for Link-Level Energy Efficiency Optimization with Informed Transmitter , 2012, IEEE Trans. Wirel. Commun..

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

[15]  Shuguang Cui,et al.  Optimal distributed beamforming for MISO interference channels , 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.

[16]  Shuguang Cui,et al.  Cooperative Interference Management With MISO Beamforming , 2009, IEEE Transactions on Signal Processing.

[17]  Geoffrey Ye Li,et al.  Distributed Interference-Aware Energy-Efficient Power Optimization , 2011, IEEE Transactions on Wireless Communications.

[18]  H. Vincent Poor,et al.  Multiuser MISO Interference Channels With Single-User Detection: Optimality of Beamforming and the Achievable Rate Region , 2011, IEEE Transactions on Information Theory.

[19]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.