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In wireless sensor networks, transmission power has a significant impact on network throughput as wireless interference increases with transmission power, and interference negatively impacts the network throughput. In this paper, we try to improve the network throughput through cross-layer optimization. We first present two algorithms to compute the transmission power of each node with the objectives of minimizing the total transmission power and minimizing the total interference, respectively, from which we can obtain a network topology that ensures a connected path from each source to the sink; then, we compute the maximum achievable throughput from the obtained topology by using joint routing and link rate control. The power control algorithms can generate symmetric links or asymmetric links if so desired. Based on different link models, we use different algorithms to compute the maximum achievable throughput. Since computing the maximum throughput is an NP-hard problem, we use efficient heuristics that use a sufficient condition instead of the computationally expensive-to-get optimal condition to capture the mutual conflict relation in a collision domain. The formal proof for the sufficient condition is provided, and the proposed algorithms are compared with previous work. Simulation results show that the proposed algorithms improve the network throughput and reduce the energy consumption, with significant improvement over previous work on both aspects.