  Non-adaptive joint source network coding of correlated sources is discussed
in this paper. By studying the information flow in the network, we propose
quantized network coding as an alternative for packet forwarding. This
technique has both network coding and distributed source coding advantages,
simultaneously. Quantized network coding is a combination of random linear
network coding in the (infinite) field of real numbers and quantization to cope
with the limited capacity of links. With the aid of the results in the
literature of compressed sensing, we discuss theoretical and practical
feasibility of quantized network coding in lossless networks. We show that, due
to the nature of the field it operates on, quantized network coding can provide
good quality decoding at a sink node with the reception of a reduced number of
packets. Specifically, we discuss the required conditions on local network
coding coefficients, by using restricted isometry property and suggest a
design, which yields in appropriate linear measurements. Finally, our
simulation results show the achieved gain in terms of delivery delay, compared
to conventional routing based packet forwarding.
