Comparison between Ω'-QPP and random interleavers for space-time turbo codes using doubly iterative decoding algorithm

2011 ◽  
Author(s):  
Ana-Mirela Rotopanescu ◽  
Lucian Trifina
Keyword(s):  
Turbo Codes ◽  
Iterative Decoding ◽  
Space Time ◽  
Decoding Algorithm

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.

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