Communication systems engineering
Communication systems engineering
Link-sharing and resource management models for packet networks
IEEE/ACM Transactions on Networking (TON)
Next century challenges: mobile networking for “Smart Dust”
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
A unified wireless LAN architecture for real-time and non-real-time communication services
IEEE/ACM Transactions on Networking (TON)
Principles of Mobile Communication
Principles of Mobile Communication
A Hierarchical Model for Distributed Collaborative Computation in Wireless Sensor Networks
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
Delay-bounded packet scheduling of bursty traffic over wireless channels
IEEE Transactions on Information Theory
Exploiting wireless channel State information for throughput maximization
IEEE Transactions on Information Theory
On adaptive transmission for energy efficiency in wireless data networks
IEEE Transactions on Information Theory
Sensor networks with mobile access: optimal random access and coding
IEEE Journal on Selected Areas in Communications
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Reliability of data in energy-constrained sensor networks is limited due to low powered transmissions. Improvement in transmission reliability through channel-state based scheduling is proposed. In a cluster, a time-shared channel between sensor nodes to the cluster head is considered in a Rayleigh fading environment. A 2-state Markov model is presented to partition the received envelope into fade and non-fade states. The state-partitioning threshold is derived as a function of bit error probability and average duration of transmission, in addition to other channel and transmission parameters. It is shown that the channelstate based scheduling can guarantee bit error probability, arbitrarily close to zero at the cost of increasing idle channel time. Increasing the number of sensor nodes in the cluster can offset the increase in idle channel time.