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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Alaoui, N. Cances, J. Meghdadi, V. |
| Copyright Year | 2011 |
| Description | Author affiliation: University of Limoges, Dpt - C2S2 UMR CNRS 6172, France (Alaoui, N.; Cances, J.; Meghdadi, V.) |
| Abstract | Optimizing architecture of sensor networks is a current topic of research. This research field can be applied in several contexts such as environmental monitoring or body area network. Performance improvement in terms of bit error rate is a major challenge. Reducing processing time and simplifying the operations of the network are the two main key points to be improved. A number of architectures have been designed to optimize the BER at destination. These architectures are mainly based on the LDPC codes (Low Density Parity Check) which have the disadvantage of the floor effect. The challenge is to find an optimal distribution of links between the sensors and relays to optimize the matrix H of the dual code and to avoid this floor effect. In this paper, we propose and simulate an efficient architecture for sensor network in a quasi-static Rayleigh fading channel environment. The new main idea is to enable communications between relays. Simulation results clearly show that the floor effect is significantly reduced with this kind of architecture. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 135612 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781457715686 |
| e-ISBN | 9781457715709 |
| e-ISBN | 9781457715693 |
| DOI | 10.1109/IWCLD.2011.6123089 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-11-30 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | belief propagation Bit error rate architecture of network mobile sensor networks Tanner graph Parity check codes Encoding Decoding LDPC code Relays Floors Belief propagation |
| Content Type | Text |
| Resource Type | Article |
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