Multi-source physiological signals are valuable for quantitative pain assessment, but their high dimensionality, nonlinearity, and strong inter-variable correlations present challenges for clinical decision-making. To improve diagnostic accuracy and efficiency, we propose a novel feature selection framework based on an enhanced Rime optimization algorithm (b-CDRIME), which incorporates a co-adaptive hunting strategy and a dispersed foraging strategy. The framework discretizes the original continuous CDRIME algorithm by introducing a V-shaped binary coding strategy, and constructs a multi-objective weighted fitness function that integrates classification accuracy, feature dimension and AUC, which is combined with the dynamic feedback mechanism of the classifier to achieve efficient feature screening and classification performance optimization. On a multi-source physiological signal public pain dataset, this paper utilizes 10 classical classifiers to test our methods on feature selection and performance improvement. The comparative experiments results show that the pain assessment model constructed based on CDRIME with XGBoost has an average classification accuracy of 81.6% while significantly reducing feature dimensionality. These findings validate the good performance and application potential of this study in the task of processing high-dimensional multi-source pain physiological signals.

This paper studies the secrecy capacity of the visible light communication (VLC) wiretap channel under a per-antenna peak-intensity constraint and a per-antenna average-intensity constraint. The focus is on the scenario with one transmitter, one legitimate user, and one eavesdropper, all equipped with multiple antennas. Considering various quantity configurations of the number of transmitting and receiving antennas, we first derive a closed-form secrecy rate exploiting the truncated exponential distribution. Based on this, full-connected and sub-connected precoding architectures are proposed to enhance the confidentiality of this multiple-input multiple-output (MIMO) VLC wiretap channel. Simulation results demonstrate that the proposed precoding schemes significantly improve the secrecy performance of the MIMO-VLC wiretap channel.

This paper investigates the capacity region of the optical intensity broadcast channels (OI-BCs), where the input is subject to a peak-intensity constraint, an average-intensity constraint, or both. By leveraging the decomposition results of several random variables, i.e., uniform, exponential, and truncated exponential random variables, and adopting a superposition coding (SC) scheme, the inner bound on the capacity region is derived. Then, the outer bound is derived by applying the conditional entropy power inequality (EPI). In the high signal-to-noise ratio (SNR) regime, the inner bound asymptotically matches the outer bound, thus characterizing the high-SNR asymptotic capacity region. The bounds are also extended to the general$K$-user BCs without loss of high-SNR asymptotic optimality.

The diversity-multiplexing tradeoff (DMT) provides a fundamental performance metric for different multiple-input multiple-output (MIMO) schemes in wireless communications. In this paper, we explore the block fading optical wireless communication (OWC) channels and characterize the DMT in the presence of both optical peak- and average-power constraints. Three different fading distributions are considered, which reflect different channel conditions. In each channel condition, we obtain the optimal DMT when the block length is sufficiently large, and we also derive the lower and upper bounds of the DMT curve when the block length is small. These results are dramatically different from the existing DMT results in radio-frequency (RF) channels. These differences may be due to the fact that the optical input signal is real and bounded, while its RF counterpart is usually complex and unbounded.

This paper studies the diversity-multiplexing tradeoff (DMT) for the block fading optical wireless communication (OWC) channel when the number of transmit antennas is not less than that of receive antennas. Inputs in this channel represent optical intensities, and hence are real-valued and non-negative. Moreover, inputs are subject to a per-antenna peak-power and a total average-power constraint. Considering these input constraints and assuming the channel fading follows the negative exponential distribution, we establish the outage diversity and average error probability bounds by using a random truncated exponential coding argument. By these derived bounds, we characterize the optimal DMT curve. Interestingly, the DMT result is fundamentally different from its counterpart in traditional radio frequency (RF) channels. This is due to the fact that inputs in this channel are real-valued and bounded, while in RF channels inputs are usually complex-valued and unbounded.