Scheduling for multiuser MIMO downlink channels with ranking-based feedback
EURASIP Journal on Advances in Signal Processing
On the uniform quantization of a class of sparse sources
IEEE Transactions on Information Theory
A linear encoding approach to index assignment in lossy source-channel coding
IEEE Transactions on Information Theory
Optimal vector quantization in terms of Wasserstein distance
Journal of Multivariate Analysis
| Hi-index | 754.96 |
Optimal scalar quantization subject to an entropy constraint is studied for a wide class of difference distortion measures including rth-power distortions with r>0. It is proved that if the source is uniformly distributed over an interval, then for any entropy constraint R (in nats), an optimal quantizer has N=[eR] interval cells such that N-1 cells have equal length d and one cell has length c⩽d. The cell lengths are uniquely determined by the requirement that the entropy constraint is satisfied with equality. Based on this result, a parametric representation of the minimum achievable distortion Dh (R) as a function of the entropy constraint R is obtained for a uniform source. The Dh(R) curve turns out to be nonconvex in general. Moreover, for the squared-error distortion it is shown that D h(R) is a piecewise-concave function, and that a scalar quantizer achieving the lower convex hull of Dh(R) exists only at rates R=log N, where N is a positive integer