scholarly journals Turbo codes for multi-hop wireless sensor networks with decode-and-forward mechanism

2021 ◽  
Author(s):  
Nashat Abughalieh ◽  
Kris Steenhaut ◽  
Ann Nowé ◽  
Alagan Anpalagan
Keyword(s):  
Turbo Codes ◽  
Iterative Decoding ◽  
Convolutional Codes ◽  
High Energy ◽  
Error Correcting Codes ◽  
Base Station ◽  
Wireless Sensor ◽  
Viterbi Decoding ◽  
Decoding Algorithm ◽  
Decode And Forward

Wireless channels are prone to many impairments, such as noise and fading. Weak channels between the nodes in the wireless sensor network (WSN) can cause reception of erroneous packets. Retransmission mechanisms are mainly mused to tackle the problem of erroneous reception in WSN communication protocols. Weak channels can cause high number of retransmissions in order to deliver a packet correctly, which will consume high energy of both the transmitting and the receiving nodes. Error correcting codes (ECCs) can be used to reduce number of retransmissions, but most ECCs have complex decoding algorithms, which leads to high processing energy consumption at the receiving nodes in the WSN. In this paper, we present a low power consumption decode-and-forward approach for the multi-hop WSNs; a serial concatenation convolutional codes (SCCC) encoder is implemented at the source node while the complex iterative decoding algorithm is shifted to the sink (base station). The intermediate nodes run a Viterbi decoding algorithm to decode only the inner code of the SCCC encoder. We investigate the effect of changing constraint length of both the inner and the outer codes and the effect of changing encoding block size. We show that most packets can be decoded at the base station at low signal-to-noise ratio (SNR) channels with the penalty of small energy loss in decoding the packet at the nodes in the network.

scholarly journals Turbo codes for multi-hop wireless sensor networks with decode-and-forward mechanism

2021 ◽  
Author(s):  
Nashat Abughalieh ◽  
Kris Steenhaut ◽  
Ann Nowé ◽  
Alagan Anpalagan
Keyword(s):  
Turbo Codes ◽  
Iterative Decoding ◽  
Convolutional Codes ◽  
High Energy ◽  
Error Correcting Codes ◽  
Base Station ◽  
Wireless Sensor ◽  
Viterbi Decoding ◽  
Decoding Algorithm ◽  
Decode And Forward

Wireless channels are prone to many impairments, such as noise and fading. Weak channels between the nodes in the wireless sensor network (WSN) can cause reception of erroneous packets. Retransmission mechanisms are mainly mused to tackle the problem of erroneous reception in WSN communication protocols. Weak channels can cause high number of retransmissions in order to deliver a packet correctly, which will consume high energy of both the transmitting and the receiving nodes. Error correcting codes (ECCs) can be used to reduce number of retransmissions, but most ECCs have complex decoding algorithms, which leads to high processing energy consumption at the receiving nodes in the WSN. In this paper, we present a low power consumption decode-and-forward approach for the multi-hop WSNs; a serial concatenation convolutional codes (SCCC) encoder is implemented at the source node while the complex iterative decoding algorithm is shifted to the sink (base station). The intermediate nodes run a Viterbi decoding algorithm to decode only the inner code of the SCCC encoder. We investigate the effect of changing constraint length of both the inner and the outer codes and the effect of changing encoding block size. We show that most packets can be decoded at the base station at low signal-to-noise ratio (SNR) channels with the penalty of small energy loss in decoding the packet at the nodes in the network.

Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC) for Wireless Sensor Networks

2020 ◽  
Vol 13 (2) ◽  
pp. 168-172
Author(s):  
Ravi Kumar Poluru ◽  
M. Praveen Kumar Reddy ◽  
Syed Muzamil Basha ◽  
Rizwan Patan ◽  
Suresh Kallam
Keyword(s):  
Network Lifetime ◽  
Routing Protocols ◽  
Energy Efficient ◽  
High Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Energy ◽  
Stability Period ◽  
Energy Efficient Clustering

Background:Recently Wireless Sensor Network (WSN) is a composed of a full number of arbitrarily dispensed energy-constrained sensor nodes. The sensor nodes help in sensing the data and then it will transmit it to sink. The Base station will produce a significant amount of energy while accessing the sensing data and transmitting data. High energy is required to move towards base station when sensing and transmitting data. WSN possesses significant challenges like saving energy and extending network lifetime. In WSN the most research goals in routing protocols such as robustness, energy efficiency, high reliability, network lifetime, fault tolerance, deployment of nodes and latency. Most of the routing protocols are based upon clustering has been proposed using heterogeneity. For optimizing energy consumption in WSN, a vital technique referred to as clustering.Methods:To improve the lifetime of network and stability we have proposed an Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC).Results:In simulation results describes the protocol performs better regarding network lifetime and packet delivery capacity compared to EEDEC and DEEC algorithm. Stability period and network lifetime are improved in EADEEC compare to DEEC and EDEEC.Conclusion:The EADEEC is overall Lifetime of a cluster is improved to perform the network operation: Data transfer, Node Lifetime and stability period of the cluster. EADEEC protocol evidently tells that it improved the throughput, extended the lifetime of network, longevity, and stability compared with DEEC and EDEEC.

scholarly journals An improved cluster formation process in wireless sensor network to decrease energy consumption

2020 ◽  
Author(s):  
Hamid Reza Farahzadi ◽  
Mostafa Langarizadeh ◽  
Mohammad Mirhosseini ◽  
Seyed Ali Fatemi Aghda
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Information Transfer ◽  
Cluster Head ◽  
High Energy ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Death Time

AbstractWireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

scholarly journals Energy Efficient Cross Layer Based Multi-Hop Clustered Routing Protocol For Wireless Sensor Networks

2019 ◽  
Vol 8 (4) ◽  
pp. 11996-12003
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocols ◽  
Cluster Head ◽  
High Energy ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cross Layer ◽  
User Friendly

Wireless Sensor network becomes an essential part of Internet of things paradigm due their scalability, ease of deployment and user-friendly interface. However, certain issues like high energy consumption, low network lifetime and optimum quality of service requirement force researchers to develop new routing protocols. In WSNs, the routing protocols are utilized to obtain paths having high quality links and high residual energy nodes for forwarding data towards the sink. Clustering provide the better solution to the WSN challenges by creating access points in the form of cluster head (CH). However, CH must tolerate additional burden for coordinating network activities. After considering these issues, the proposed work designs a moth flame optimization (MFO) based Cross Layer Clustering Optimal (MFO-CLCO) algorithm to consequently optimize the network energy, network lifetime, network delay and network throughput. Multi-hop wireless communication between cluster heads (CHs) and base station (BS) is employed along with MFO to attain optimum path cost. The simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of energy consumption, network lifetime, delay and throughput.

scholarly journals Iterative Decoding of Turbo Codes

2018 ◽  
Vol 3 ◽  
pp. 15
Author(s):  
Dhaneshwar Sah
Keyword(s):  
Turbo Codes ◽  
Coding Theory ◽  
Iterative Decoding ◽  
Communication Systems ◽  
Error Control ◽  
Viterbi Algorithm ◽  
Convolutional Codes ◽  
Soft Information ◽  
Space Communications ◽  
College Of Engineering

<p><strong> </strong>This paper presents a Thesis which consists of a study of turbo codes as an error-control Code and the software implementation of two different decoders, namely the Maximum a Posteriori (MAP), and soft- Output Viterbi Algorithm (SOVA) decoders. Turbo codes were introduced in 1993 by berrouet at [2] and are perhaps the most exciting and potentially important development in coding theory in recent years. They achieve near- Shannon-Limit error correction performance with relatively simple component codes and large interleavers. They can be constructed by concatenating at least two component codes in a parallel fashion, separated by an interleaver. The convolutional codes can achieve very good results. In order of a concatenated scheme such as a turbo codes to work properly, the decoding algorithm must affect an exchange of soft information between component decoders. The concept behind turbo decoding is to pass soft information from the output of one decoder to the input of the succeeding one, and to iterate this process several times to produce better decisions. Turbo codes are still in the process of standardization but future applications will include mobile communication systems, deep space communications, telemetry and multimedia. Finally, we will compare these two algorithms which have less complexity and which can produce better performance.</p><p><strong>Journal of Advanced College of Engineering and Management</strong>, Vol.3, 2017, Page: 15-30</p>

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