Abstract
Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.
Highlights
During the last several decades, wireless sensor networks (WSNs) have been widely used in various areas, including environmental monitoring, home automation, healthcare, agriculture, unmanned battle fields, public space surveillance and intelligent traffic systems (ITSs) [1]
We propose an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission scheme for mobile wireless multimedia sensor networks (WMSNs), which performs spatial MIMO mode adaptation and antenna set switching with associated multiple sensor nodes
We introduced a MN MIMO switching scheme for spatially-correlated channels
Summary
During the last several decades, wireless sensor networks (WSNs) have been widely used in various areas, including environmental monitoring, home automation, healthcare, agriculture, unmanned battle fields, public space surveillance and intelligent traffic systems (ITSs) [1]. Correlation-based adaptive approaches require much less feedback overhead and incur a small performance penalty relative to instantaneous adaptation Along these lines, [34] proposes to switch between statistical beamforming, double space-time transmit diversity and spatial multiplexing with linear receivers and a four-antenna system based on ergodic link capacity (the ergodic mutual information assuming a certain transmit configuration). The resulting capacity expressions depend on the MIMO transmission scheme, antenna correlation and signal-to-noise power ratio as in the SN systems, and on the path gain and transmit antenna set selected from multiple sensor nodes Based on these models, spatial MIMO mode adaptation and antenna set switching algorithms are proposed.
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