An Adaptive Coding Approach Using Source-Relay Channel State Information and Hamming Codes to Trade off Power and Error Probability in Wireless Sensor Networks

Wireless sensor networks have attracted a great deal of attention as one of the key enabling technologies for 5G cellular networks. One of the main challenges ahead of such networks is limitation of energy resources which directly affects their lifespan. In this paper, an adaptive coding technique for wireless sensor networks is presented. On the contrary to the previous studies which have considered block fading channels, where a constant fading factor is assumed during the transmission of a block of data, we track slow time variations that channel experiences during the transmission of a block of data. We design an adaptive coding technique for this case. The proposed algorithm is based on iterative decoding and aims to achieve an error probability lower than the permissible threshold while minimizing the energy consumption. Our simulation results, employing Hamming codes, demonstrate that the proposed adaptive coding scheme, decreases the power consumption and consequently increases the network lifespan.