Effective Capacity Analysis of Cognitive Radio Channels for Quality of Service Provisioning
Sami Akin, Mustafa Cenk Gursoy

TL;DR
This paper analyzes the maximum data throughput of cognitive radio channels under QoS constraints, considering various transmission schemes and system parameters, to optimize performance in dynamic spectrum environments.
Contribution
It introduces an effective capacity framework for cognitive radio channels with QoS constraints, comparing fixed and variable transmission schemes under different CSI assumptions.
Findings
Variable-rate schemes outperform fixed-rate when detection probabilities are high.
Power and rate adaptation improve effective capacity, especially with good channel sensing.
Gains from adaptation decrease as QoS constraints become more stringent.
Abstract
In this paper, cognitive transmission under quality of service (QoS) constraints is studied. In the cognitive radio channel model, it is assumed that the secondary transmitter sends the data at two different average power levels, depending on the activity of the primary users, which is determined by channel sensing performed by the secondary users. A state-transition model is constructed for this cognitive transmission channel. Statistical limitations on the buffer lengths are imposed to take into account the QoS constraints. The maximum throughput under these statistical QoS constraints is identified by finding the effective capacity of the cognitive radio channel. This analysis is conducted for fixed-power/fixed-rate, fixed-power/variable-rate, and variable-power/variable-rate transmission schemes under different assumptions on the availability of channel side information (CSI) at the…
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Taxonomy
TopicsCognitive Radio Networks and Spectrum Sensing · Advanced MIMO Systems Optimization · Advanced Wireless Network Optimization
