Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Strong Minimum Energy Topology in Wireless Sensor Networks: NP-Completeness and Heuristics
IEEE Transactions on Mobile Computing
Wireless Communications
MIMO antenna subset selection with space-time coding
IEEE Transactions on Signal Processing
Virtual MIMO-based cooperative communication for energy-constrained wireless sensor networks
IEEE Transactions on Wireless Communications
Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Receive antenna selection for MIMO flat-fading channels: theory and algorithms
IEEE Transactions on Information Theory
Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks
IEEE Journal on Selected Areas in Communications
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In this paper, we present two practical algorithms to select a subset of channels in virtual MIMO wireless sensor networks (WSN). One is the Singular-Value Decomposition-QR with Threshold (SVD-QR-T) approach that selects the best subset of transmitters while keeping all receivers active. The threshold is adaptive by means of Fuzzy C-Mean (FCM). The other is the Maximum Spanning Tree Searching (MASTS) algorithm on a basis of graph theory in respect of cross-layer design, which potentially provides a path connecting all sensors that benefits routing and QoS of networks. The MASTS algorithm keeps all sensors active but selects Mt + Mr -1 subchannels, where Mt and Mr are the number of transmitters and receivers, respectively. These two approaches are compared against the case without channel selection in terms of capacity, bit error rate (BER), and multiplexing gain in the presence of water-filling as well as the circumstance of without water-filling under the same total transmission power constraint. Despite less multiplexing gain, when water-filling is applied, MASTS achieves higher capacity and lower BER than that of virtual MIMO without channel selection at moderate to high SNR while SVD-QR-T FCM provides the lowest BER at high SNR; in case of no water-filling and equal transmission power allocation, MASTS still offers the highest capacity at moderate to high SNR but SVD-QR-T FCM achieves the lowest BER. Both algorithms provide satisfying performances with reduced cost and resources compared to the case without channel selection.