Channel quality estimation with convolution code for airborne communications

Both efficient utilization of network resources and providing Qualities of Service (QoS) are dependent on channel quality parameters. In particular, QoS is a challenging issue since radio and physical resources are seldom perfect. For example, channel fading and receiver noise are such constraints. Communication and networking resources including power, modulation and coding can be adaptively adjusted provided that accurate channel or link quality estimation is available. Traditionally, channel qualities are measured by packet error rate or bit error rate which is usually a function of average channel signal to noise ratio (SNR), as is extensively used in power control, adaptive transmission and QoS routing tasks. For airborne applications, dynamic channel condition such as time selective fading makes the estimation a crucially tough issue to attack. In this work, we propose channel quality estimation techniques employing convolution code for use in highly dynamic airborne environments. The estimates are achieved by measuring Euclidean and Hamming distances between received channel symbols and paths of decoder trellis. Performance analysis on estimators is presented by using probabilistic method and modified Gallager bounds. In the simulations, typical airborne scenarios are considered for wide range of parameters.