Amitabh Mishra | Searcharxiv

arXiv2026

Elevation- and Tilt-Aware Shadow Fading Correlation Modeling for UAV Communications

Future wireless networks demand a more accurate understanding of channel behavior to enable efficient communication with reduced interference. Uncrewed Aerial Vehicles (UAVs) are poised to play an integral role in these networks, offering versatile applications and flexible deployment options. However, accurately characterizing the shadow fading (SF) behavior in UAV communications remains a challenge. Traditional SF correlation models rely on spatial distance and neglect the UAV's 3D orientation and elevation angle. Yet even slight variations in pitch angle (5 to 10 degrees) can significantly affect the signal strength observed by a UAV. In this study, we investigate the impact of UAV pitch and elevation geometry on SF and propose an elevation- and tilt-aware spatial correlation model. We use a real-world fixed-altitude UAV measurement dataset collected in a rural environment at 3.32 GHz with a 125 kHz bandwidth. Results show that a 10-degree tilt-angle separation and a 20-degree elevation-angle separation can reduce the SF correlation by up to 15% and 40%, respectively. In addition, integrating the proposed correlation model into the ordinary Kriging (OK) framework for signal strength prediction yields an approximate 1.5 dB improvement in median RMSE relative to the traditional correlation model that ignores UAV orientation and elevation.

eess.SP↗

arXiv2010

DynaChanAl: Dynamic Channel Allocation with Minimal End-to-end Delay for Wireless Sensor Networks

With recent advances in wireless communication, networking, and low power sensor technology, wireless sensor network (WSN) systems have begun to take significant roles in various applications ranging from environmental sensing to mobile healthcare sensing. While some WSN applications only require a lim- ited amount of bandwidth, new emerging applications operate with a notice- ably large amount of data transfers. One way to deal with such applications is to maximize the available capacity by utilizing the use of multiple wireless channels. This work proposes DynaChannAl, a distributed dynamic wireless channel algorithm with the goal of effectively distributing nodes on multiple wireless channels in WSN systems. Specifically, DynaChannAl targets applica- tions where mobile nodes connect to a pre-existing wireless backbone and takes the expected end-to-end queuing delay as its core metric. We use the link qual- ity indicator (LQI) values provided by IEEE 802.15.4 radios white-list potential links with good link quality and evaluate such links with the aggregated packet transmission latency at each hop. Our approach is useful for applications that require minimal end-to-end delay (i.e., healthcare applications). DynaChannAl is a light weight and highly adoptable scheme that can be easily incorporated with various pre-developed components and pre-deployed applications. We eval- uate DynaChannAl in on a 45 node WSN testbed. As the first study to consider end-to-end latency as the core metric for channel allocation in WSN systems, the experimental results indicate that DynaChannAl successfully distributes multi- ple (mobile) source nodes on different wireless channels and enables the nodes to select wireless channel and links that can minimize the end-to-end latency.

cs.NI↗