11,195 research outputs found
Random Linear Network Coding For Time Division Duplexing: Energy Analysis
We study the energy performance of random linear network coding for time
division duplexing channels. We assume a packet erasure channel with nodes that
cannot transmit and receive information simultaneously. The sender transmits
coded data packets back-to-back before stopping to wait for the receiver to
acknowledge the number of degrees of freedom, if any, that are required to
decode correctly the information. Our analysis shows that, in terms of mean
energy consumed, there is an optimal number of coded data packets to send
before stopping to listen. This number depends on the energy needed to transmit
each coded packet and the acknowledgment (ACK), probabilities of packet and ACK
erasure, and the number of degrees of freedom that the receiver requires to
decode the data. We show that its energy performance is superior to that of a
full-duplex system. We also study the performance of our scheme when the number
of coded packets is chosen to minimize the mean time to complete transmission
as in [1]. Energy performance under this optimization criterion is found to be
close to optimal, thus providing a good trade-off between energy and time
required to complete transmissions.Comment: 5 pages, 6 figures, Accepted to ICC 200
A Practical Scheme for Wireless Network Operation
In many problems in wireline networks, it is known that achieving capacity on each link or subnetwork is optimal for the entire network operation. In this paper, we present examples of wireless networks in which decoding and achieving capacity on certain links or subnetworks gives us lower rates than other simple schemes, like forwarding. This implies that the separation of channel and network coding that holds for many classes of wireline networks does not, in general, hold for wireless networks. Next, we consider Gaussian and erasure wireless networks where nodes are permitted only two possible operations: nodes can either decode what they receive (and then re-encode and transmit the message) or simply forward it. We present a simple greedy algorithm that returns the optimal scheme from the exponential-sized set of possible schemes. This algorithm will go over each node at most once to determine its operation, and hence, is very efficient. We also present a decentralized algorithm whose performance can approach the optimum arbitrarily closely in an iterative fashion
- …