High throughput and complexity reduction remain major requirements of future wireless communication system implementations. On the other hand, iterative processing is being widely investigated and proposed nowadays to cope with the increasing transmission quality requirement. However, these advanced techniques pose a real challenge in terms of achieving high throughput and reduced complexity implementations. A typical example in this domain is the significant performance improvement offered by the use of iterative demodulation with turbo decoding in severe channel conditions. For this iterative system, and targeting a highly parallel architecture for high throughput feature, we analyze the impact of computation scheduling on the complexity. We demonstrate that the adoption of advanced shuffled scheduling can lead to significant complexity reduction. Simulations show that applying the Butterfly-Replica schedule in the turbo decoder reduces the overall number of iterations by at least one iteration in the waterfall region with respect to the Butterfly schedule. This gain in number of iterations comes without any overhead in terms of area and without any lose in communication performance. However, it results in a throughput improvement around 25% and a complexity reduction up to 22% in arithmetic operations, 14.6% in read access memory, and -39.3% in write access memory for the considered configurations.