Joint Adaptive Reception Algorithm with Ant Colony Optimization for Asynchronous Cooperation Transmission Systems

Abstract

A joint adaptive reception algorithm is proposed for asynchronous cooperation systems, which is aiming at reducing the interference caused by the asynchronous relays, where ant colony optimization algorithm is adopted to enhance the adaptive training process. The coordination node is usually needed for cooperative communication systems, which is employed to apply relays timing synchronization as well as relay selections, thus achieving the diversity order. However, it could be difficult to choose the center, when the requirement is too rigor for some certain system, such as the complexity-limited ones. For this kind of non-centered systems, the relaying nodes usually work asynchronously, so it is necessary to remove the inter-symbol interference (ISI) in the received signal, in order not to degrade the whole transmission performance. As an effective means, equalizer is usually utilized to carry out ISI cancelations, where zero forcing and minimum mean square error are known as the criterions. When channel state information is unavailable, adaptive equalizer can be considered, with which to train the weightings of equalizer. In this paper, to improve the training process of conventional adaptive algorithms, we investigate and modify ant colony optimization to propose a hybrid and combined adaptive architecture, and the converging property can be guaranteed. Computer simulations show that under Rayleigh fading cooperation communication channels, the proposed algorithm has faster convergence speed and can achieve better detecting performance than conventional adaptive equalizer.