Minimum mean-squared error (MMSE) equalizers are a viable solution to mitigate the frequency selectivity of the aeronautical telemetry channel. Because the MMSE equalizer filter coefficients are a function of the carrier frequency offset (CFO), the equivalent discrete-time channel, and the noise variance, reliable estimates of those parameters are required. The CFO is due primarily to the high velocity of the airborne transmitter. Because the equivalent discrete-time channel in aeronautical telemetry is sparse, the performance of the joint estimator based on a sparse channel estimator is superior to the performance of a traditional nonsparse maximum-likelihood-inspired joint estimator. The improvement is seen in lower estimator error variances for the parameters, particularly for the CFO and channel estimate, and in the postequalizer bit-error rate. Simulation results demonstrate that the postequalizer bit-error rate using the sparse estimator is almost as good as that using ideal estimators.


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    Title :

    On the Effects of Channel Sparsity on Joint Estimators in Aeronautical Telemetry


    Contributors:


    Publication date :

    2020-06-01


    Size :

    707947 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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