Communication Networking: An Analytical Approach
Communication Networking: An Analytical Approach
Effective Capacity Channel Model for Frequency-selective Fading Channels
Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks
Capacity with explicit delay guarantees for generic sources over correlated Rayleigh channel
IEEE Transactions on Wireless Communications
Survey of deterministic and stochastic service curve models in the network calculus
IEEE Communications Surveys & Tutorials
Effective capacity: a wireless link model for support of quality of service
IEEE Transactions on Wireless Communications
The impact of QoS constraints on the energy efficiency of fixed-rate wireless transmissions
IEEE Transactions on Wireless Communications
On multivariate Rayleigh and exponential distributions
IEEE Transactions on Information Theory
Effective service capacity analysis of opportunistic multi-carrier OFDMA systems
Proceedings of the 8h ACM symposium on QoS and security for wireless and mobile networks
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The concept of the effective service capacity is an analytical framework for evaluating QoS-constrained queuing performance of communication systems. Recently, it has been applied to the analysis of different wireless systems like point-to-point systems or multi-user systems. In contrast to previous work, we consider in this work slot-based systems where a scheduler determines a packet size to be transmitted at the beginning of the slot. For this, the scheduler can utilize outdated channel state information. Based on a threshold error model, we derive the effective service capacity for different scheduling strategies that the scheduler might apply. We show that even slightly outdated channel state information leads to a significant loss in capacity in comparison to an ideal system with perfect channel state information available at the transmitter. This loss depends on the 'risk-level' the scheduler is willing to take which is represented by an SNR margin. We show that for any QoS target and average link state there exists an optimal SNR margin improving the maximum sustainable rate. Typically, this SNR margin is around 3 dB but is sensible to the QoS target and average link quality. Finally, we can also show that adapting to the instantaneous channel state only pays off if the correlation between the channel estimate and the channel state is relatively high (with a coefficient above 0.9).