POLAR QUANTIZATION OF A COMPLEX GAUSSIAN RANDOM VARIABLE

We solve numerically the optimum fixed-level non-uniform and uniform quantization of a circularly symmetric complex (or bivariate) Gaussian random variable for the mean absolute squared error criterion. For a given number of total levels, we determine its factorization into the product of numbers of magnitude and phase levels that produces the minimum distortion. We tabulate the results for numbers of “useful” output levels up to 1024, giving their optimal factorizations, minimum distortion, and entropy. For uncoded quantizer outputs, we find that the optimal splitting of rate between magnitude and phase, averaging to 1.52 and 1.47 bits more in the phase angle than magnitude for optimum and uniform quantization, respectively, compares well with the optimal polar coding formula of 1.376 bits of Pearlman and Gray [3]. We also compare the performance of polar to rectangular quantization by real and imaginary parts for both uncoded and coded output levels. We find that, for coded outputs, both polar quantizers are outperformed by the rectangular ones, whose distortion-rate curves nearly coincide with Pearlman and Gray's polar coding bound. For uncoded outputs, however, we determine that the polar quantizers surpass in performance their rectangular counterparts for all useful rates above 6.0 bits for both optimum and uniform quantization. Below this rate, the respective polar quantizers are either slightly inferior or comparable. Copyright © 1979 by The Institute of Electrical and Electronics Engineers, Inc.