Resilience against radio jamming is a key feature for the trustworthiness of next-generation mobile radio access networks (RAN) and systems for detecting jamming attacks are required in order to notify operators and effectively deploy mitigation techniques. This paper proposes a novel approach for jamming detection in 5G new radio (NR) that leverages user equipment (UE) as distributed sensors by collecting and analyzing standardized UE measurement reports. We propose a detection method based on the signal-to-interference-and-noise ratio (SINR) measured at the UEs and analytically derive the corresponding error probabilities. Furthermore, we provide a method for positioning the jammer source based on information on the location of the UEs. We validate the effectiveness of the proposed method based on SINR measurements obtained from a static 5G network simulator. Our results show that the method accurately detects the jammer even at low transmit power and provides a coarse indication of the jammer position.

Cell-free multi-user multiple input multiple output networks are a promising alternative to classical cellular architectures, since they have the potential to provide uniform service quality and high resource utilisation over the entire coverage area of the network. To realise this potential, previous works have developed radio resource management mechanisms using various optimisation engines. In this work, we consider the problem of overall ergodic spectral efficiency maximisation in the context of uplink-downlink data power control in cell-free networks. To solve this problem in large networks, and to address convergence-time limitations, we apply scalable multi-objective Bayesian optimisation. Furthermore, we discuss how an intersection of multi-fidelity emulation and Bayesian optimisation can improve radio resource management in cell-free networks.

Wireless links use adaptive modulation and coding (AMC) to optimize data transmission over a dynamic channel. Traditional AMC schemes rely on simple heuristics to track the instantaneous channel state. While attractive for their low implementation and operational complexity, these schemes are known to be suboptimal in a large range of operating environments. Further, several such schemes require careful parameter tuning, which can be both expensive and error-prone. In this paper, we propose latent Thompson sampling (LTS) for AMC, which efficiently tracks the wireless channel by modeling a latent, low-dimensional, channel state. LTS features both a low computational complexity and fast learning dynamics, and requires minimal tuning effort. We evaluate LTS in stationary as well as fading wireless channels, where LTS improves the link throughput by up to 100% compared to state-of-the-art schemes.

In the context of wireless communications, we propose a deep learning approach to learn the mapping from the instantaneous state of a frequency selective fading channel to the corresponding frame error probability (FEP) for an arbitrary set of transmission parameters. We propose an abstract model of a bit interleaved coded modulation (BICM) orthogonal frequency division multiplexing (OFDM) link chain and show that the maximum likelihood (ML) estimator of the model parameters estimates the true FEP distribution. Further, we exploit deep neural networks as a general purpose tool to implement our model and propose a training scheme for which, even while training with the binary frame error events (i.e., ACKs / NACKs), the network outputs converge to the FEP conditioned on the input channel state. We provide simulation results that demonstrate gains in the FEP prediction accuracy with our approach as compared to the traditional effective exponential SIR metric (EESM) approach for a range of channel code rates, and show that these gains can be exploited to increase the link throughput.

During the last two years, the METIS project ("Mobile and wireless communications Enablers for the Twenty-twenty Information Society") has been conducting research on 5G-enabling technology components. This paper provides a summary of METIS work on 5G architectures. The architecture description is presented from different viewpoints. First, a functional architecture is presented that may lay a foundation for development of first novel 5G network functions. It is based on functional decomposition of most relevant 5G technology components provided by METIS. The logical orchestration & control architecture depicts the realization of flexibility, scalability and service orientation needed to fulfil diverse 5G requirements. Finally, a third viewpoint reveals deployment aspects and function placement options for 5G.

The wireless-access networks of today will have to evolve in several dimensions in order to address the challenges and expectations of the future. New technology components will be introduced as part of the evolution of current wireless-access technologies, such as HSPA and LTE. However, additional components may also constitute future new wireless-access technologies, which may complement the evolved technologies. Examples of such new technology components are new ways of accessing spectrum and substantially higher frequency ranges, the introduction of massive antenna configurations, direct device-to-device communication, and ultra-dense deployments.

In 2020, mobile and wireless traffic volume is expected to increase thousand-fold over 2010 figures. Moreover, an increase in the number of wirelessly-connected devices to counts in the tens of billions will have a profound impact on society. Massive machine communication, forming the basis for the Internet of Things, will make our everyday life more efficient, comfortable and safer, through a wide range of applications including traffic safety and medical services. The variety of applications and data traffic types will be significantly larger than today, and will result in more diverse requirements on services, devices and networks. METIS is set up by leading global players to prepare the migration towards tomorrow's multi-purpose global communication infrastructure, serving humans and things. The main objective of METIS is to lay the foundation for this future global mobile and wireless communications system, and to generate a global consensus here. In particular, METIS will provide new solutions which fit the needs beyond 2020.

In this paper we investigate reduced complexity decoders for LDPC codes over M-PSK modulation. Capacity calculations show only minor losses if only phase information is considered in the decoder. We device a decoder based on phase angle summation, which unfortunately does not work for codes over Galois fields (but shows promising results for codes over integer rings). For codes over Galois fields we construct table-based decoders which gives performance close to belief propagation decoders at substantially reduced complexity

We propose a serial concatenated trellis-coded modulation system using one or more inner rate-1 accumulate codes and a mapping to a higher order, Gray-labeled signal constellation. As outer codes, we consider repeat codes, single parity-check codes, and convolutional codes. We show that under maximum-likelihood decoding, there exists a signal-to-noise ratio threshold beyond which the bit-error probability goes to zero as the blocklength goes to infinity. We then evaluate the performance for finite blocklengths using a modified union bound. Computer simulations demonstrate that the proposed system, despite its use of a simple rate-1 inner code, achieves performance in additive white Gaussian noise and Rayleigh fading that is comparable to, or better than, that of more complex systems suggested in the literature.

In a companion paper, we showed the existence of decoding thresholds for maximum-likelihood (ML) decoding of a serial concatenated trellis-coded modulation (SCTCM) system with one or more inner accumulate codes. In this paper, we compute the decoding thresholds for an iterative, non-ML decoder by density evolution (DE), assuming infinite blocklengths. We also derive a stability condition for the particular case of an outer parity-check code and a single inner accumulate code. We show that, for equiprobable signaling, the bit-wise log-likelihood ratio densities for higher order constellations are symmetric. Furthermore, when used in DE, these densities can be averaged without significantly affecting the resulting threshold values. For an outer single parity-check code, the lowest decoding thresholds are achieved with two inner accumulate codes. For an outer repeat code, a single inner accumulate code gives the lowest thresholds. At code rates r/sub c/>2/3, the decoding thresholds for the SCTCM system are within 1 dB of the constellation-constrained channel capacity for additive white Gaussian noise channels, and within 1.5 dB for independent, identically distributed Rayleigh channels. Simulation results verify the computed thresholds.

In this paper we propose a serial concatenated trellis coded modulation system using an inner accumulate code and a Gray-labeled signal constellation. The simple inner code and the Gray labeling allow us to extend to higher-order constellations the coding theorems of Divsalar et al., (1998), and Pfister et al., (2000), stating that when the signal-to-noise ratio (SNR) exceeds a certain, system-specific threshold, the word error probability goes to zero as the blocklength goes to infinity. We also evaluate the performance for finite blocklengths using an improved union bound. Despite the simple inner code, the simulated performance in AWGN and Rayleigh fading is equal to the performance of more complex systems suggested in the literature.

We propose a serial concatenated trellis coded modulation system using one or more inner accumulate code(s) and a Gray-labeled signal constellation. We show the existence of a threshold, such that if the signal-to-noise ratio (SNR) exceeds this threshold, the bit error probability goes to zero as the blocklength goes to infinity. Tight numerical values for the thresholds for an iterative decoder are found by density evolution. Despite the simple inner code, the simulated performance in AWGN and Rayleigh fading is comparable to that of more complex systems suggested in the literature.