Coordinated Multicell Multiuser Precoding for Maximizing Weighted Sum Energy Efficiency

• Published in: IEEE transactions on signal processing Vol. 62; no. 3; pp. 741 - 751
• Main Authors: Shiwen He, Yongming Huang, Luxi Yang, Ottersten, Bjorn
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2014; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Array signal processing; Coding, codes; Computational efficiency; Computing time; Coordinated multicell precoding; Covariance matrices; Detection, estimation, filtering, equalization, prediction; Educational institutions; Energy efficiency; energy efficient optimization; Energy management; Exact sciences and technology; Exact solutions; Heuristic; Information, signal and communications theory; Iterative algorithms; Optimization; Polynomials; Signal and communications theory; Signal processing algorithms; Signal to noise ratio; Signal, noise; sum rate maximization; Telecommunications and information theory; weighted sum energy efficiency maximization; Wireless communication; Performance evaluation; Multiple access; Wireless telecommunication; Coordinated multicell precoding; sum rate maximization; energy efficient optimization; Iterative method; Conditional probability; Algorithm; Beam forming; Optimization; Algorithm performance; Coding; Energetic efficiency; Electric power consumption; Signal processing; Numerical simulation; Minimum energy; weighted sum energy efficiency maximization; Pretreatment; Low-power electronics; Signal to noise ratio
• ISSN: 1053-587X; 1941-0476; 1941-0476
• DOI: 10.1109/TSP.2013.2294595

Energy efficiency optimization of wireless systems has become urgently important due to its impact on the global carbon footprint. In this paper we investigate energy efficient multicell multiuser precoding design and consider a new criterion of weighted sum energy efficiency, which is defined as the weighted sum of the energy efficiencies of multiple cells. This objective is more general than the existing methods and can satisfy heterogeneous requirements from different kinds of cells, but it is hard to tackle due to its sum-of-ratio form. In order to address this non-convex problem, the user rate is first formulated as a polynomial optimization problem with the test conditional probabilities to be optimized. Based on that, the sum-of-ratio form of the energy efficient precoding problem is transformed into a parameterized polynomial form optimization problem, by which a solution in closed form is achieved through a two-layer optimization. We also show that the proposed iterative algorithm is guaranteed to converge. Numerical results are finally provided to confirm the effectiveness of our energy efficient beamforming algorithm. It is observed that in the low signal-to-noise ratio (SNR) region, the optimal energy efficiency and the optimal sum rate are simultaneously achieved by our algorithm; while in the middle-high SNR region, a certain performance loss in terms of the sum rate is suffered to guarantee the weighed sum energy efficiency.