Vehicle-to-Vehicle technologies have enabled autonomous vehicles to share
information to see through occlusions, greatly enhancing perception
performance. Nevertheless, existing works all focused on homogeneous traffic
where vehicles are equipped with the same type of sensors, which significantly
hampers the scale of collaboration and benefit of cross-modality interactions.
In this paper, we investigate the multi-agent hetero-modal cooperative
perception problem where agents may have distinct sensor modalities. We present
HM-ViT, the first unified multi-agent hetero-modal cooperative perception
framework that can collaboratively predict 3D objects for highly dynamic
vehicle-to-vehicle (V2V) collaborations with varying numbers and types of
agents. To effectively fuse features from multi-view images and LiDAR point
clouds, we design a novel heterogeneous 3D graph transformer to jointly reason
inter-agent and intra-agent interactions. The extensive experiments on the V2V
perception dataset OPV2V demonstrate that the HM-ViT outperforms SOTA
cooperative perception methods for V2V hetero-modal cooperative perception. We
will release codes to facilitate future research.

该研究提出了一种新型的多智能体异态合作感知框架，名为 HM-ViT，可以在异构传感器模态下协同预测高度动态的自动驾驶交通中的三维物体。实验证明 HM-ViT 相比先前的合作感知方法具有更好的效果。

HM-ViT: 异模态车辆间合作感知的视觉变换器

HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with  vision transformer

Most existing work on adaptive allocation of subcarriers and power in
multiuser orthogonal frequency division multiplexing (OFDM) systems has focused
on homogeneous traffic consisting solely of either delay-constrained data
(guaranteed service) or non-delay-constrained data (best-effort service). In
this paper, we investigate the resource allocation problem in a heterogeneous
multiuser OFDM system with both delay-constrained (DC) and
non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate
of all the users with NDC traffic while maintaining guaranteed rates for the
users with DC traffic under a total transmit power constraint. Through our
analysis we show that the optimal power allocation over subcarriers follows a
multi-level water-filling principle; moreover, the valid candidates competing
for each subcarrier include only one NDC user but all DC users. By converting
this combinatorial problem with exponential complexity into a convex problem or
showing that it can be solved in the dual domain, efficient iterative
algorithms are proposed to find the optimal solutions. To further reduce the
computational cost, a low-complexity suboptimal algorithm is also developed.
Numerical studies are conducted to evaluate the performance the proposed
algorithms in terms of service outage probability, achievable transmission rate
pairs for DC and NDC traffic, and multiuser diversity.

本研究探讨在具有延迟容忍和非延迟容忍两种交通的多用户 OFDM 系统中的资源分配问题，通过对功率分配的分析，提出了一种多级注水原则的算法，并通过致力于求解这个凸解来提高算法的准确率，最后以计算实验的方式论证了本算法的性能。