Many communication applications are event-triggered, but current applications still use the Shannon communication model to transmit and decode messages. Due to the ever-growing number of users in communication networks, this leads to a weakening of performance. To counteract this, it makes sense to use post-Shannon methods such as deterministic identification (DI) codes. The information theory analysis carried out so far has shown how performance can be increased through DI codes. In this paper we provide a new constructive proof of the capacity of deterministic identification codes for discrete memoryless channels (DMC), while so far only existence proofs exist. Based on this idea, we implement DI codes of finite length and analyze their performance both analytically and experimentally. For the latter, we build a prototype using software-defined radios and a noise generator.

This paper proposes a system architecture that embeds semantically-secure information-theoretic physical layer security (IT-PLS) non-intrusively into a 5G New Radio (NR) system in order to protect uplink transmissions via physical uplink control channels (PUCCH) against post-quantum eaves-dropping attacks. We implement a proof of concept of such system employing a code construction based on a modular coding scheme with a universal hash function that ensures semantic secrecy. We conduct link-level simulations of wiretap channels under different frequency-selective fading conditions and noise characteristics in order to evaluate the performance of such implementation for slow and fast fading scenarios. We model them using tapped delay line channel models involving rural and urban scenarios with line-of-sight (LOS) and non-LOS radio conditions, as specified by the 3GPP TR 38.901. We characterize such system by measuring the distinguishing error rate, block error rate, and secrecy outage probability under different time-varying fading channels. Our case study outlines how IT-PLS can be transparently embedded into future 6G systems as well.

This paper assesses the impact on the performance that information-theoretic physical layer security (IT-PLS) introduces when integrated into a 5G New Radio (NR) system. For this, we implement a wiretap code for IT-PLS based on a modular coding scheme that uses a universal-hash function in its security layer. The main advantage of this approach lies in its flexible integration into the lower layers of the 5G NR protocol stack without affecting the communication's reliability. Specifically, we use IT-PLS to secure the transmission of downlink control information by integrating an extra pre-coding security layer as part of the physical downlink control channel (PDCCH) procedures, thus not requiring any change of the 3GPP 38 series standard. We conduct experiments using a real-time open-source 5G NR standalone implementation and use software-defined radios for over-the-air transmissions in a controlled laboratory environment. The overhead added by IT-PLS is determined in terms of the latency introduced into the system, which is measured at the physical layer for an end-to-end (E2E) connection between the gNB and the user equipment.

In this paper we use a seeded modular coding scheme for implementing physical layer security in a wiretap scenario. This modular scheme consists of a traditional coding layer and a security layer. For the traditional coding layer, we use a polar code. We evaluate the performance of the seeded modular coding scheme in an experimental setup with software defined radios and compare these results to simulation results. In order to assess the secrecy level of the scheme, we employ the distinguishing security metric. In our experiments, we compare the distinguishing error rate for different seeds and block lengths.

Cellular vehicle-to-everything (C-V2X) communication is a key enabler for future cooperative automated driving and safety-related applications. The requirements they demand in terms of Quality of Service (QoS) performance vary according to the use case. For instance, Day-1 applications such as Emergency Brake Light warning have less strict requirements than remote driving. In this paper, we seek to answer two questions: Are current LTE networks ready to support Day-1 applications at all times? And, can underperforming situations be reliably predicted based on GPS and network-related information? To address these questions, we first implement a system that collects positioning data and LTE key performance indicators (KPIs) with a higher time resolution than commercial off-the-shelf LTE modems, while simultaneously measuring the end-to-end (E2E) delay of an LTE network. We then use this system to assess the readiness of multiple mobile network operators (MNOs) and a live Mobile Edge Computing (MEC) deployment in an urban scenario. For evaluating whether an adaptable operation is possible in adverse circumstances, e.g., by performing hybrid networking or graceful degradation, we finally use Machine Learning to generate a client-based QoS predictor and forecast the achievable QoS levels.