Minimum energy coding for wireless nanosensor networks

Abstract

Wireless nanosensor networks (WNSNs), which are collections of nanosensors with communication units, can be used for sensing and data collection with extremely high resolution and low power consumption for various applications. In order to realize WNSNs, it is essential to develop energy-efficient communication techniques, since nanonodes are severely energy-constrained. In this paper, a novel minimum energy coding scheme (MEC) is proposed to achieve energy-efficiency in WNSNs. Unlike the existing minimum energy codes, MEC maintains the desired Hamming distance, while minimizing energy, in order to provide reliability. It is analytically shown that, with MEC, codewords can be decoded perfectly for large code distance, if source set cardinality, M is less than inverse of symbol error probability, 1/ps. Performance analysis shows that MEC outperforms popular codes such as Hamming, Reed-Solomon and Golay in average energy per codeword sense.