Amplify-and-Forward Cooperative Diversity Wireless Networks: Model, Analysis, and Monotonicity Properties

This paper models and analyzes the performance of an amplify-and-forward cooperative diversity wireless network. We propose a Markov-based model, which encompasses the following aspects: 1) the transmission using amplify-and-forward cooperative diversity at the physical layer; 2) a flow control protocol, finite and infinite transmitting buffers, and an ARQ-based error recovery mechanism at the radio link layer; and 3) a bursty traffic pattern at the application layer. We derive expressions for packet delivery probability and distribution of packet delivery delay. We numerically quantify improvement in terms of packet delivery probability and packet delivery delay for increasing SNR and/or cooperative nodes. For an additional cooperative node, we quantify the amount of SNR which can be reduced (i.e., SNR saving) without degrading the system performance. Also, the minimum SNR and cooperative nodes which satisfy a probabilistic delay bound are computed. We then derive a sufficient condition that ensures an increase in packet delivery probability. Unlike numerical evaluation of the model, this sufficient condition does not require computation of stationary distribution of the Markov chain. It only involves parameter adjustment at physical, radio link, and application layers, hence substantially reducing the computation effort. Based on the developed model, we design a power allocation algorithm, which computes the minimum transmission power under a packet delivery probability constraint. We then use the derived sufficient condition to reduce complexity of the power allocation algorithm.