C-V2X Centralized Resource Allocation with Spectrum Re-Partitioning in Highway Scenario

Cellular Vehicle-to-Everything communication is an important scenario of 5G technologies. Modes 3 and 4 of the wireless systems introduced in Release 14 of 3GPP standards are intended to support vehicular communication with and without cellular infrastructure. In the case of Mode 3, dynamic resource selection and semi-persistent resource scheduling algorithms result in a signalling cost problem between vehicles and infrastructure, therefore, we propose a means to decrease it. This paper employs Re-selection Counter in centralized resource allocation as a decremental counter of new resource requests. Furthermore, two new spectrum re-partitioning and frequency reuse techniques in Roadside Units (RSUs) are considered to avoid resource collisions and diminish high interference impact via increasing the frequency reuse distance. The two techniques, full and partial frequency reuse, partition the bandwidth into two sub-bands. Two adjacent RSUs apply these sub-bands with the Full Frequency Reuse (FFR) technique. In the Partial Frequency Reuse (PFR) technique, the sub-bands are further re-partitioned among vehicles located in the central and edge parts of the RSU coverage. The sub-bands assignment in the nearest RSUs using the same sub-bands is inverted concerning the current RSU to increase the frequency reuse distance. The PFR technique shows promising results compared with the FFR technique. Both techniques are compared with the single band system for different vehicle densities.

Radio Network Forensic with mmWave Using the Dominant Path Algorithm

For the last two decades, cybercrimes are growing on a daily basis. To track down cybercrimes and radio network crimes, digital forensic for radio networks provides foundations. The data transfer rate for the next-generation wireless networks would be much greater than today’s network in the coming years. The fifth-generation wireless systems are considering bands beyond 6 GHz. The network design of the next-generation wireless systems depends on propagation characteristics, frequency reuse, and bandwidth variation. This article declares the channel’s propagation characteristics of both line of sight (LoS) and non-LOS (NLoS) to construct and detect the path of rays coming from anomalies. The simulations were carried out to investigate the diffraction loss (DL) and frequency drop (FD). Indoor and outdoor measurements were taken with the omnidirectional circular dipole antenna with a transmitting frequency of 28 GHz and 60 GHz to compare the two bands of the 5th generation. Millimeter-wave communication comes with a higher constraint for implementing and deploying higher losses, low diffractions, and low signal penetrations for the mentioned two bands. For outdoor, a MATLAB built-in 3D ray tracing algorithm is used while for an indoor office environment, an in-house algorithmic simulator built using MATLAB is used to analyze the channel characteristics.

Toward Polymorphic Internet of Things Receivers Through Real-Time Waveform-Level Deep Learning

Wireless systems such as the Internet of Things (IoT) are changing the way we interact with the cyber and the physical world. As IoT systems become more and more pervasive, it is imperative to design wireless protocols that can effectively and efficiently support IoT devices and operations. On the other hand, today's IoT wireless systems are based on inflexible designs, which makes them inefficient and prone to a variety of wireless attacks. In this paper, we introduce the new notion of a deep learning-based polymorphic IoT receiver, able to reconfigure its waveform demodulation strategy itself in real time, based on the inferred waveform parameters. Our key innovation is the introduction of a novel embedded deep learning architecture that enables the solution of waveform inference problems, which is then integrated into a generalized hardware/software architecture with radio components and signal processing. Our polymorphic wireless receiver is prototyped on a custom-made software-defined radio platform. We show through extensive over-the-air experiments that the system achieves throughput within 87% of a perfect-knowledge Oracle system, thus demonstrating for the first time that polymorphic receivers are feasible.