Reference : Distributed coordinated beamforming for multi-cell multigroup multicast systems

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/29253

Title :	Distributed coordinated beamforming for multi-cell multigroup multicast systems
Language :	English
Author, co-author :	Pennanen, Harri [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Christopoulos, Dimitrios [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	Jul-2016
Main document title :	Communications (ICC), 2016 IEEE International Conference on
Publisher :	IEEE
Peer reviewed :	Yes
Audience :	International
ISBN :	978-1-4799-6664-6
Event name :	Communications (ICC), 2016 IEEE International Conference on
Event date :	from 23-05-2016 to 27-05-2016
Event place (city) :	Kuala Lumpur
Event country :	Malaysia
Keywords :	[en] Array signal processing ; Interference ; Signal to noise ratio ; Optimization ; Multicast communication ; Minimization ; Wireless communication
Abstract :	[en] This paper considers coordinated multicast beam-forming in a multi-cell wireless network. Each multiantenna base station (BS) serves multiple groups of single antenna users by generating a single beam with common data per group. The aim is to minimize the sum power of BSs while satisfying user-specific SINR targets. We propose centralized and distributed multicast beamforming algorithms for multi-cell multigroup systems. The NP-hard multicast problem is tackled by approximating it as a convex problem using the standard semidefinite relaxation method. The resulting semidefinite program (SDP) can be solved via centralized processing if global channel knowledge is available. To allow a distributed implementation, the primal decomposition method is used to turn the SDP into two optimization levels. The higher level is in charge of optimizing inter-cell interference while the lower level optimizes beamformers for given inter-cell interference constraints. The distributed algorithm requires local channel knowledge at each BS and scalar information exchange between BSs. If the solution has unit rank, it is optimal for the original problem. Otherwise, the Gaussian randomization method is used to find a feasible solution. The superiority of the proposed algorithms over conventional schemes is demonstrated via numerical evaluation.
Permalink :	http://hdl.handle.net/10993/29253
DOI :	10.1109/ICC.2016.7510951

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