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).