{'fraction_non_alphanumeric': 0.02172670097198399, 'fraction_numerical': 0.0011435105774728416, 'mean_word_length': 5.227758007117438, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Transmit Power Optimization for Amplify-and-Forward Relay Networks With Reduced Overheads

Transmit power optimization or power control plays an important role in implementing wireless relay networks since it can significantly improve system performance, such as transmission rate, power consumption, etc. However, power optimization introduces considerable control channel overheads due to exchanging channel state information (CSI) and optimization results. In this paper, we aim to design a new power optimization scheme to reduce overheads while avoiding a large performance loss. We consider a typical three-node amplify-and-forward relay network consisting of a source, a relay, and a destination. The power of source and that of relay are optimized to minimize the total power consumption under the constraint of a minimum transmission rate or nonviolation probability. We first define and analyze two schemes based on traditional routines, which are called Strategies I and II. In Strategy I, transmit power of both source and relay is optimized based on instantaneous CSI, whereas in Strategy II, transmit power is based on statistical CSI. We then propose a new partial CSI strategy, which is called Strategy III, where source power is based on statistical CSI, whereas relay power is based on instantaneous CSI. Strategy III is formulated and solved by the two-stage stochastic programming method. With this new strategy, the control channel overhead can be reduced by 50% compared with Strategy I, and at the same time, the potential significant performance degradation as in Strategy II can be avoided. Simulation results show that the proposed strategy results in near-optimal performance when the relay is located close to the source.