  In this paper we initiate a study of distributed deterministic broadcasting
in ad-hoc wireless networks with uniform transmission powers under the SINR
model. We design algorithms in two settings: with and without local knowledge
about immediate neighborhood. In the former setting, our solution has almost
optimal O(Dlog2 n) time cost, where n is the size of a network, D is the
eccentricity of the network and {1,...,N} is the set of possible node IDs. In
the latter case, we prove an Omega(n log N) lower bound and develop an
algorithm matching this formula, where n is the number of network nodes. As one
of the conclusions, we derive that the inherited cost of broadcasting
techniques in wireless networks is much smaller, by factor around
min{n/D,Delta}, than the cost of learning the immediate neighborhood. Finally,
we develop a O(D Delta log2 N) algorithm for the setting without local
knowledge, where Delta is the upper bound on the degree of the communication
graph of a network. This algorithm is close to a lower bound Omega(D Delta).
