C-POD: An AWS Cloud Framework for Edge Pod Automation and Remote Wireless Testbed Sharing

This paper presents C-POD, a cloud-native framework that automates the deployment and management of edge pods for seamless remote access and sharing of wireless testbeds. C-POD leverages public cloud resources and edge pods to lower the barrier to over-the-air (OTA) experimentation, enabling researchers to share and access distributed testbeds without extensive local infrastructure. A supporting toolkit has been developed for C-POD to enable flexible and scalable experimental workflows, including containerized edge environments, persistent Secure Shell (SSH) tunnels, and stable graphical interfaces. We prototype and deploy C-POD on the Amazon Web Services (AWS) public cloud to demonstrate its key features, including cloud-assisted edge pod deployment automation, elastic computing resource management, and experiment observability, by integrating two wireless testbeds that focus on RF signal generation and 5G(B) communications, respectively.

A study on the ideal magnitude and phase of reconstructed point targets in SAR imaging

In this paper, the magnitude and phase of the reconstructed point targets in SAR imaging are studied quantitatively by using inverse crime. Two scenarios, one with single point target in the imaging area and the other with two point targets, are considered. The theorems on the magnitude and phase are established and proved for each scenario. In addition, several numerical examples are presented and the numerical results show that they agree with the corresponding theorems. This study is useful for appreciating the limitations of formulating inversion algorithms based on simplistic point target building blocks.