Analyzing the Effect of a Block FEC Algorithm’s Symbol Size on Energy Consumption in Wireless Sensor Networks
This paper evaluates the effect of a block Forward Error Correction (FEC) algorithm’s symbol size on power consumption in wireless sensor networks (WSN). The WSN channels exhibit frequent bursty errors with a high average Bit Error Rate (BER) due to low transmission power, random deployment, and moving intermediate objects obstructing WSN communications. For resisting against the bursty errors, WSN would adopt a block FEC algorithm that restores more tainted bits than other kinds of FEC algorithms as errors become burstier since it recovers errors symbol-by-symbol not bit-by-bit. Even when the same amount of bits are allocated for FEC code, different FEC symbol size meaning different number of FEC symbols vary the packet error rate and the transmission energy over a given WSN. They also affect the computational energy since their decoding and encoding complexities depend on the number of FEC symbols per packet. The analytical evaluation based on long-term sensor traffic traces indicates that the appropriate FEC symbol size saves a sensor node’s energy consumption by up-to 85 % comparing to other sizes.
KeywordsSensor Node Wireless Sensor Network Complementary Cumulative Distribution Function Symbol Error Probability Symbol Size
Unable to display preview. Download preview PDF.
- 1.Levisianou, A., Assimakopoulos, C., Pavlidou, F.-N., Polydoros, A.: A recursive IR protocol for multicarrier communications. In: Proceedings of the 6th International OFDM-Workshop, pp. 22-1–22-4 (September 2001)Google Scholar
- 2.Zhao, L., Mark, J.W., Yoon, Y.C.: A combined link adaptation and incremental redundancy protocol for enhanced data transmission. In: Proceedings of the GLOBECOM 2001, pp. 25–29 (November 2001)Google Scholar
- 3.Ahn, J.S., Hong, S.W., Heidemann, J.: An adaptive FEC code control algorithm for mobile wireless sensor networks. JCN 7(4), 489–499 (2005)Google Scholar
- 4.Reed, I.S., Solomon, G.: Polynomial codes over certain fields, Soc. Ind. Appl. Math. In: Proceedings of the GLOBECOM 2001, vol. 8, pp. 300–304 (June 1960)Google Scholar
- 5.Sankarasubramaniam, Y., Akyildiz, I.F., McLaughlin, S.W.: Energy efficiency based packet size optimization in wireless sensor networks. In: Proceedings of the 1st IEEE International Workshop on Sensor Network Protocols and Applications (SNPA), pp. 1–8 (May 2003)Google Scholar
- 8.Rockliff, S.: Reed-Solomon (RS) codes program (1989), http://www.eccpage.com
- 9.Rappaport, T.S.: Wireless communications principles and practice. Prentice Hall, Upper Saddle River (2002)Google Scholar
- 10.Wang, A., Cho, S.H., Sodini, C.G., Chandrakasan, A.P.: Energy Efficient Modulation and MAC for Asymmetric RF Microsensor Systems. In: Proceedings of International Symposium on Low Power Electronics and Design (ISLPED), pp. 106–111 (August 2001)Google Scholar
- 12.Ganesan, D., Krishnamachari, B., Woo, A., Culler, D., Estrin, D., Wicker, S.: Protocols and Architectures for Wireless Sensor Networks, Technical Report UCLA/CSDTR 02-0013 (February 2002)Google Scholar
- 14.Bougard, B., Daly, D., Chandrakasan, A.P., Catthoor, F., Dehaene, W.: Energy Efficiency of the IEEE 802.15.4 Standard in Dense Wireless Microsensor Networks: Modeling and Improvement Perspectives. In: Proceedings of Design, Automation and Test in Europe (DATE), pp. 196–201 (March 2005)Google Scholar