Conference Paper
An Optimized User Selection Method for Cooperative Diversity Systems.
Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki
DOI: 10.1109/GLOCOM.2006.853 Conference: Proceedings of the Global Telecommunications Conference, 2006. GLOBECOM '06, San Francisco, CA, USA, 27 November  1 December 2006 Source: IEEE Xplore

Conference Paper: Distributed relay selection for virtual MIMO in spectral efficient broadcasting networks
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ABSTRACT: Virtual multipleinput multipleoutput (VMIMO) enables the implementation of conventional MIMO on mobile devices equipped with insufficient numbers of antennas via cooperation. This paper considers a spectral efficient broadcasting network in which selected mobile devices form a VMIMO system to relay the broadcasted data to help other devices decode the source data more reliably. In particular, the relay selection problem, a fundamental issue in the construction of VMIMO, is examined. We first review existing selection schemes for users operating in the amplifyandforward (AF) mode. We then propose a distributed selection scheme based on postprocessing SNR. In the proposed scheme, each user individually finds the most favorable candidates for VMIMO construction and then all users obtain a joint decision through a voting process. Simulation results show that the proposed distributed scheme outperforms existing distributed selection schemes and achieves a nearoptimal performance with lower complexity compared to the centralized scheme.Wireless Communications and Networking Conference (WCNC), 2013 IEEE; 01/2013 
Article: Joint User Grouping and Linear Virtual Beamforming: Complexity, Algorithms and Approximation Bounds
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ABSTRACT: In a wireless system with a large number of distributed nodes, the quality of communication can be greatly improved by pooling the nodes to perform joint transmission/reception. In this paper, we consider the problem of optimally selecting a subset of nodes from potentially a large number of candidates to form a virtual multiantenna system, while at the same time designing their joint linear transmission strategies. We focus on two specific application scenarios: 1) multiple single antenna transmitters cooperatively transmit to a receiver; 2) a single transmitter transmits to a receiver with the help of a number of cooperative relays. We formulate the joint node selection and beamforming problems as cardinality constrained optimization problems with both discrete variables (used for selecting cooperative nodes) and continuous variables (used for designing beamformers). For each application scenario, we first characterize the computational complexity of the joint optimization problem, and then propose novel semidefinite relaxation (SDR) techniques to obtain approximate solutions. We show that the new SDR algorithms have a guaranteed approximation performance in terms of the gap to global optimality, regardless of channel realizations. The effectiveness of the proposed algorithms is demonstrated via numerical experiments.IEEE Journal on Selected Areas in Communications 09/2012; · 3.12 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: In this paper, the utilization of mobile devices (MDs) as decodeandforward relays in a devicetodevice assisted virtual MIMO (VMIMO) system is studied. Single antenna MDs are randomly distributed on a 2D plane according to a Poisson point process, and only a subset of them are sources leaving other idle MDs available to assist them (relays). Our goal is to develop an efficient algorithm to cluster each source with a subset of available relays to form a VMIMO system under a limited feedback assumption. We first show that the NP hard optimization problem of precoding in our scenario can be approximately solved by semidefinite relaxation. We investigate a special case with a single source and analytically derive an upper bound on the average spectral efficiency of the VMIMO system. Then, we propose an optimal greedy algorithm that achieves this bound. We further exploit these results to obtain a polynomial time clustering algorithm for the general case with multiple sources. Finally, numerical simulations are performed to compare the performance of our algorithm with that of an exhaustive clustering algorithm, and it shown that these numerical results corroborate the efficiency of our algorithm.IEEE Transactions on Wireless Communications 12/2013; 13(3). · 2.42 Impact Factor
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