Title :
Energy efficiency in multi-cell MIMO broadcast channels with interference alignment
Author :
Jie Tang ; So, Daniel K. C. ; Alsusa, Emad ; Hamdi, Khairi Ashour ; Shojaeifard, Arman
Author_Institution :
Sch. of Electr. & Electron. Eng., Univ. of Manchester, Manchester, UK
Abstract :
Characterizing the fundamental metric of energy efficiency (EE) of multiple-input multiple-output interfering broadcast channels (MIMO-IFBC) is important for the development of green wireless communications. In this paper, we address the EE optimization problem for multi-cell MIMO-IFBC within the context of interference alignment (IA). We employ grouping-based IA scheme to cancel both inter-cell interference (ICI) and inter-user inference (IUI), and thus transform the MIMO-IFBC to a single cell single user MIMO scenario. A gradient-based optimal power adaptation scheme is proposed which utilizes water-filling approach and singular value decomposition (SVD) to maximize EE for each cell. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation algorithm can efficiently approach the optimal EE.
Keywords :
MIMO communication; broadcast channels; cellular radio; energy conservation; gradient methods; radiofrequency interference; singular value decomposition; telecommunication power management; EE optimization problem; energy efficiency; gradient-based optimal power adaptation scheme; green wireless communications; grouping-based IA scheme; inter-cell interference; inter-user inference; interference alignment; multicell MIMO broadcast channels; multicell MIMO-IFBC; multiple-input multiple-output interfering broadcast channels; resource allocation algorithm; single cell single user MIMO scenario; singular value decomposition; water-filling approach; Array signal processing; Interference; MIMO; Optimization; Receivers; Throughput; Vectors;
Conference_Titel :
Global Communications Conference (GLOBECOM), 2014 IEEE
Conference_Location :
Austin, TX
DOI :
10.1109/GLOCOM.2014.7037439