  In this paper, we consider a distributed reception scenario where a
transmitter broadcasts a signal to multiple geographically separated receive
nodes over fading channels, and each node forwards a few bits representing a
processed version of the received signal to a fusion center. The fusion center
then tries to decode the transmitted signal based on the forwarded information
from the receive nodes and possible channel state information. We show that
there is a strong connection between the problem of minimizing a symbol error
probability at the fusion center in distributed reception and channel coding in
coding theory. This connection allows us to design a unified framework for
coded distributed diversity reception. We focus linear block codes such as
simplex codes or first-order Reed-Muller codes that achieve the Griesmer bound
with equality to maximize the diversity gain. Due to its simple structure, no
complex offline optimization process is needed to design the coding structure
at the receive nodes for the proposed coded diversity technique. The proposed
technique can support a wide array of distributed reception scenarios, i.e.,
arbitrary $M$-ary symbol transmission at the transmitter and received signal
processing with multiple bits at the receive nodes. Numerical studies show that
the proposed coded diversity technique can achieve practical symbol error rates
even with moderate signal-to-noise ratio and numbers of the receive nodes.
