Energy Efficient Virtual MIMO Communication for Wireless Sensor Networks

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Virtual multiple input multiple output (MIMO) techniques are used for energy efficient communication in wireless sensor networks. We investigate virtual MIMO for fixed and variable rates. We propose energy efficient routing based on virtual MIMO. The simulation results show that virtual MIMO based routing is more energy efficient as compared to SISO (single input single output) for larger distances.


In recent years, virtual MIMO has attracted a growing interest because of its energy efficiency in large field of networks. In virtual MIMO network, a group of sensors cooperate to transmit and receive data. Although the participation of multiple transmitters and receivers in a transmission save significant energy in long-range communications, the increase in the number of transmitters and receivers also increases the circuitry power consumption.

As a result, the energy optimization techniques have to be adapted with the environment. Due to the circuitry complexity and difficulty of integrating separate antenna, virtual MIMO concepts are applied in wireless sensor networks (WSNs) for energy efficient communication to save energy and increase reliability.

A large number of protocols and methods are proposed for energy efficient communications in WSNs. In this paper, we would like to investigate cooperative virtual MIMO that provides energy efficient communication by sharing the transmission and reception of information. In virtual MIMO, multiple senders and receivers participate in long-range communication to improve data reliability in fading channels. The performance of virtual MIMO in WSNs depends on the structure of network layer and data link layer. There are several approaches for implementing virtual antenna array in WSNs.

Although the core implementation of virtual antenna array or co-operative transmission lies on physical layer, there is deep dependency on the higher layers (network and data link) to implement this issue. In a cognitive network framework, the network components can modify the operational parameters to respond to the needs of particular environment. We propose a cluster based virtual MIMO cognitive model with the aim of changing operational parameters (constellation size) to meet the optimum design.
Author: Sajid Hussain, Anwarul Azim, and Jong-Hyuk Park
Source: Acadia University

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