We consider a communication channel whose input is modeled as a discrete random variable X with distribution pX. X is transmitted over a noisy channel and distorted by a continuous-valued noise to result in a continuous-valued output signal U at the receiver. A thresholding quantizer Q is applied to reconstruct a discrete signal V = Q(U) from the continuous-valued U. Our goal is to jointly design both the input distribution pX and the thresholding quantizer Q to maximize the mutual information I(X; V) between the input X and V since the accuracy of any decoding algorithm that estimates X from V fundamentally depends on I(X; V). In this paper, an alternating maximization algorithm is proposed that guarantees to achieve a locally optimal solution. In addition, we numerically show that by randomly selecting a set of initial starting points, the proposed algorithm is capable of achieving the globally optimal solution. Both the theoretical and numerical results are provided to justify our approach.
Capacity achieving quantizer design for multiple-input multiple-output thresholding channels
2023-06-01
1521624 byte
Conference paper
Electronic Resource
English
Initial Investigation of Multiple-Input Multiple-Output (MIMO) Channels in Indoor Environments
British Library Conference Proceedings | 2000
|Design of Multiple Input Multiple Output Volterra Filter Equalizer
British Library Online Contents | 2001
|