A New Energy-Efficient Data Transmission Scheme Based on DSC and Virtual MIMO for Wireless Sensor Network

Li, Na; Zhang, Liwen; Li, Bing

doi:10.1155/2015/904274

Cited by 4 publications

(3 citation statements)

References 17 publications

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“…The compression processes of the source nodes,

X_{2,}

and

X_{1}

are similar; the only difference being that source node

X_{2}

transmits the second half of the information bit and its related parity bit, P 2 . The compression rates of both source nodes are identical, and that of related LDPC codes is equal [6,12].…”

Section: Dsc –Mimomentioning

confidence: 99%

“…However, correlated information collected from the neighboring nodes are directly proportional to sensor node density. These correlated data are transmitted to a base station (BS), as a result of which energy efficiency of the WSNs to decreases [6,7]. A virtual MIMO has a similar effect as a MIMO system in the WSNs; it reduces the energy consumption of the WSNs and resolves the energy consumption problem of the entire network [8].…”

Section: Introductionmentioning

confidence: 99%

“…In [9], Abughalieh and others demonstrated that the lifetime of a WSN can be improved through compression of the correlated information, using the DSC scheme. In [6] and [10], the authors proved that the DSC‐MIMO technique reduces energy consumption through the MIMO scheme, and enhances energy efficiency by compressing the correlated data using the DSC scheme. Sartipi and others [11,12] revealed that the DSC of two correlated source nodes at any arbitrary rate is based on the Slepian‐Wolf (SW) theorem.…”

Section: Introductionmentioning

confidence: 99%

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Energy‐efficient data transmission technique for wireless sensor networks based on DSC and virtual MIMO

Singh

Amin

2020

ETRI Journal

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In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple‐input multiple‐output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space‐time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple‐input multiple‐output (MIMO) data transmission technique in the WSNs. The DSC‐MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC‐MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single‐input single‐output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

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“…The compression processes of the source nodes,

X_{2,}

and

X_{1}

are similar; the only difference being that source node

X_{2}

transmits the second half of the information bit and its related parity bit, P 2 . The compression rates of both source nodes are identical, and that of related LDPC codes is equal [6,12].…”

Section: Dsc –Mimomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%