SNR estimation in Nakagami-m fading with diversity combining and its application to turbo decoding

We propose an online signal-to-noise ratio (SNR) estimation scheme for Nakagamifading channels with branch equal gain combining (EGC) diversity. We derive the SNR estimate based on the statistical ratio of certain observables over a block of data, and use the SNR estimates in the iterative decoding of turbo codes on Nakagamifading channels with branch EGC diversity. We evaluate the turbo decoder performance using the SNR estimate under various fading and diversity scenarios ( = 0 5 1 5 and = 1 2 3) and compare it with the performance using perfect knowledge of the SNR and the fade amplitudes.