The distributed power control algorithms available in this paper assume perfect estimation of interference power at the receivers and often, the availability of perfect local channel state information (CSI). However, perfect estimation of interference power or acquisition of channel information is impractical. In this paper, we consider a generic class of distributed power control algorithms and analyze the resulting performance loss when faced with errors in CSI and/or interference level estimation. We approximate such power control algorithms with linearized state space dynamics wherein the errors in the estimation of received interference or the CSI, can be modeled as additive observation noise. Based on the proposed model, we derive lower bounds on the norm of the errors in the transmit power vector and receive signal-to-interference-plus-noise ratio (SINR) vector. Our analysis suggests that when the target SINR vector approaches the Pareto-optimal bound, the errors in the transmit vectors could grow without bound. As a consequence, to maintain a performance loss within an acceptable range, either much longer estimation times or lower target SINRs are required. Our numerical results confirm the validity of our analysis and the validity of the proposed bounds.

Over the last decade, the development of resource allocation algorithms for cooperative communication networks has focused on optimal, or acceptable suboptimal, solutions assuming full knowledge of channel state information (CSI) in the network. This assumption is, unfortunately, unlikely to be satisfied in practice. Here we turn our attention to the effects of limited CSI on the performance of a cooperative network. We show that the performance gap between the fully centralized approaches and fully distributed algorithms falls exponentially with the number of CSI bits per link available at the central node. We use this to show that, for a large class of objective functions, a close-to-optimal solution is achievable with limited CSI. We also show that proper allocation of the CSI bits to different links in the network is a crucial issue. We propose a simple upper bound on the performance gap and a bit allocation algorithm that minimizes the upper bound. Our numerical results confirm that through optimal bit allocation considerable savings in CSI bits is achieved.

The authors propose a new analytical model based on BCMP closed queueing networks in order to evaluate the performance of IEEE 802.11 DCF MAC protocol when all nodes are in the transmission range of each other, that is, a single hop wireless ad hoc network. By the proposed model, some performance metrics such as saturation and non-saturation throughput, distributions of channel access delay and the number of packets in the MAC buffer are derived. An extension of the proposed model is used for the analysis of IEEE 802.11e EDCA and the same performance metrics are evaluated for this protocol. Analytical results on IEEE 802.11e prove that differentiation in service is possible and channel share for each service type may be well assigned by tuning the MAC protocol parameters. Simulation results show consistency with our analytical results.