Enhancing the Efficiency of Constrained Dual-hop Variable-gain AF Relaying under Nakagami-m Fading

This paper studies power allocation for performance constrained dual-hop variable-gain amplify-and-forward (AF) relay networks in Nakagami-m fading. In this context, the performance constraint is formulated as a constraint on the end-to-end signal-to-noise-ratio (SNR) and the overall power consumed is minimized while maintaining this constraint. This problem is considered under two different assumptions of the available channel state information (CSI) at the relays, namely full CSI at the relays and partial CSI at the relays. In addition to the power minimization problem, we also consider the end-to-end SNR maximization problem under a total power constraint for the partial CSI case. We provide closed-form solutions for all the problems which are easy to implement except in two cases, namely selective relaying with partial CSI for power minimization and SNR maximization, where we give the solution in the form of a one-variable equation which can be solved efficiently. Numerical results are then provided to characterize the performance of the proposed power allocation algorithms considering the effects of channel parameters and CSI availability. Copyright (c) 2014 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to [email protected] This work has been presented in part at the IEEE Global Communications Conference (GLOBECOM’2013). A. Zafar and M.-S. Alouini are with the Computer, Electrical and Mathematical Sciences & Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah Province, Saudi Arabia. 23955-6900 (E-mail: {ammar.zafar, slim.alouini}@kaust.edu.sa). R. M. Radaydeh is with the College of Engineering, Alfaisal University, Riyadh, 11533, Saudi Arabia. (E-mail: [email protected]). Y. Chen is with the School of Engineering, University of Warwick, Coventry, UK. CV4 7AL (E-mail: [email protected]). This work was funded in part by a grant from King Abdulaziz City of Science and Technology (KACST). The work of Yunfei Chen is supported in part by the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China (No. IC14T40).