🤖 AI Summary
This work investigates the channel capacity of multiple-input multiple-output optical wireless communication (MIMO-OWC) systems under a total average power constraint. By formulating a non-negative basis pursuit (NN-BP) model, the capacity is expressed as a function of the input optical intensity distribution. Computable upper and lower bounds on capacity are derived for scenarios with mismatched numbers of transmit and receive antennas. As the first study to characterize MIMO-OWC capacity using the NN-BP framework, the proposed bounds are asymptotically tight at high signal-to-noise ratios (SNR), thereby closing the constant-gap limitation present in existing results. Numerical evaluations in representative indoor and outdoor settings demonstrate that the new bounds significantly outperform prior art and provide a tight approximation of capacity in the high-SNR regime.
📝 Abstract
This paper investigates the capacity of multipleinput multiple-output (MIMO) optical wireless communication (OWC) channels under a total average-power constraint. Since different nonnegative input vectors can be mapped to the same image vector and thus induce the same output distribution, we formulate a nonnegative basis pursuit (NN-BP) problem to identify the minimum-l1-norm input vector for each image vector. Based on the NN-BP characterization, we derive an equivalent expression for the channel capacity in terms of the image-vector distribution. We then establish computable lower and upper capacity bounds for both nT >= nR and nT < nR cases, and prove that the proposed bounds are asymptotically tight in the high signal-to-noise ratio (SNR) regime. Numerical results for indoor and outdoor OWC scenarios demonstrate that the proposed bounds improve upon existing ones and close the constant gap in the high-SNR regime.