Publications

While 5G is being rolled out in different parts of the globe, several research groups around the world have already started posing the question: What will the sixth generation (6G) be? The 6G vision is a data-driven society, enabled by near instant unlimited wireless connectivity. Driven by the impetus to provide vertical-specific wireless network solutions, machine type communication encompassing both its mission critical and massive connectivity aspects is foreseen to be an important cornerstone of 6G development. An over-arching vision for machine type communication in 6G networks is presented in paper. In this regard, some relevant performance indicators are first discussed, followed by a presentation of key enablers.

A hard-decision parallel interference cancellation receiver suitable for closed-loop power controlled CDMA uplink is introduced. Receiver algorithms for cancellation and SIR estimation are presented. A simple model for inter-cell interference is proposed to gain insight into the detector performance in cellular CDMA networks. Multiantenna diversity reception with maximal-ratio combining is employed in reception. The receiver performance is evaluated in fading multipath environments with simulations. Performance gains with regard to the conventional receiver are found in both pico- and macro-cellular environments. Gain from cancellation is found to be larger in more rapidly fading vehicular environments, where power control has less effect on the fluctuation of the received power. Results suggest the utilisation of the near-far robustness of the HD-PIC in power control algorithm design.

In this paper, assuming a bidirectional network, the performance of two-way half-duplex (HD) relaying systems based on physical-layer network coding is compared with oneway full-duplex (FD) relaying schemes. Specifically, the outage probability and system throughput of the considered schemes are investigated. Our results show that unidirectional FD relaying can outperform bidirectional HD relaying, even in the presence of self-interference at the FD relay.

Radio spectrum is a scarce natural resource, whose efficient management calls for a thorough understanding of its value. A number of spectrum valuation approaches has emerged considering different elements, some with potentially high uncertainty as future profits, total cost of ownership and societal benefits. Spectrum valuation is important in regulators' 5G spectrum decisions and will face a new situation, where location specific services and higher carrier frequencies give rise to local network operator models. This paper analyzes the existing spectrum management and spectrum valuation approaches and identifies key elements to consider, when defining and assessing the value of spectrum especially in the context of future local 5G networks. The growing pressure to open the mobile market for location and vertical specific 5G networks promotes new sharing-based spectrum access models, to allow the emergence of local 5G operators. We characterize the identified spectrum valuation elements in the context of these new local 5G networks from the perspectives of the different stakeholder roles including regulators, mobile network operators (MNOs) and entrant local 5G operators. We further present a spectrum valuation case study of the recent 5G spectrum decisions in the 3.5-GHz band in different countries.

This paper discusses a multi-probe anechoic chamber setup, capable of reconstructing non-stationary radio propagation environments for testing of millimetre wave and massive Multiple-Input-Multiple-Output devices. The test setup is aimed for evaluation of end to end performance of devices, including hybrid beamforming operations of antenna arrays and base band processing, in highly time variant channel conditions. In this work we present simulated comparison of an ideal reference radio channel model and corresponding model implemented with limited resources of multi-probe anechoic chamber components. We give a qualitative analysis of the results with non-line of sight channel models, without quantitative evaluation. The example device under test is a 8 × 8 planar array with half wavelength inter-element spacing.

In this paper, we consider a femtocell deployment scenario in which radio resources are shared among self-organized femtocells. We propose a distributed Admission Control Mechanism (ACM) for traffic load balancing among sub-carriers when there are multiple Quality of Service (QoS) classes. Furthermore, we propose a mechanism based on Reinforcement Learning (RL) for slot allocation to the traffic streams on different sub-carriers, which is employed by each Femto Access Point (FAP) to mitigate interference among femtocells and the underlaid macrocell. Through simulations, the performance of the proposed scheme is evaluated where it is shown that femtocells are able to coexist with the overlay macrocell network with no information exchange and by relying only on local information.

This paper investigates the outage performance of a cooperative relaying network, where the relay node is considered to be an energy-constrained device so that a power splitting-based simultaneous wireless information and power transfer scheme is employed. The relay is considered to operate in full-duplex (FD) mode so that both energy recycling and information decoding can be performed. For this purpose, the relay is assumed to be provided with two batteries which switch between the power supplying mode and charging mode at each transmission block. In particular, we assume that the self-interference inherent to FD mode is not completely suppressed; it is subject only to passive interference cancellation for self-energy recycling, while it is subject to both passive and active cancellation for information decoding. We derive a tight closed-form approximation to the outage probability for the considered FD mode-based scheme, as well as for the HD mode-based counterpart. We validate the obtained expressions via Monte Carlo simulations. The impact of self-energy recycling in FD mode on the system performance is assessed.

We model the scenarios of network slicing allocation for the micro-operator (MO) network. The MO creates the slices "as a service" of wireless resource and then allocates these slices to multiple mobile network operators (MNOs). We propose the slice allocation problem of multiple MNOs with the goal of maximizing the social welfare of the network defined as sum rate of all MNOs. The many-to-one matching game framework is adopted to solve this problem. Then, the generic Markov Chain Monte Carlo (MCMC) method is introduced for the computation of game theoretical solution. After the MNOs obtain the slices, for each small cell base station (SBS), we investigate the role of power allocation using Q-learning and uniform power. We numerically show that the solution of the matching game leads to two-sided stable matching. Furthermore, for each MNO, we explore the problem of infrastructure cost minimization constrained on the latency at the user equipment (UE). The optimal solution is given by a greedy fractional knapsack algorithm. We illustrate that it is sufficient for the MNO to use a small fraction of the SBS to serve the UE while satisfying the latency constraint. For the problem of overall data rate maximization, we numerically show that the power allocation has significant effect on the social welfare of the system.

This paper presents a framework to evaluate the probability that a decision error event occurs in wireless sensor networks, including sensing and communication errors. We consider a scenario where sensors need to identify whether a given event has occurred based on its periodic, noisy, and observations of a given signal. Such information about the signal needs to be sent to a fusion center that decides about the actual state at that specific observation time. The communication links-single-or multi-hop-are modeled as binary symmetric channels, which may have different error probabilities. The decision at the fusion center is based on OR, AND, K-OUT-OF-N, and MAJORITY Boolean operations on the received signals associated to individual sensor observations. We derive closed-form equations for the average decision error probability as a function of the system parameters (e.g., number of sensors and hops) and the input signal characterization. Our analyses show the best decision rule is closely related to the frequency that the observed events occur and the number of sensors. In our numerical example, we show that the AND rule outperforms MAJORITY if such an event is rare and there is only a handful number of sensors. Conversely, if there are a large number of sensors or more evenly distributed event occurrences, the MAJORITY is the best choice. We further show that, while the error probability using the MAJORITY rule asymptotically goes to 0 with increasing number of sensors, it is also more susceptible to higher channel error probabilities.

The paradigm of the Next Generation cellular network (6G) and beyond is machine-type communications (MTCs), where numerous Internet of Things (IoT) devices operate autonomously without human intervention over wireless channels. IoT's autonomous and energy-intensive characteristics highlight effective energy efficiency (EEE) as a crucial key performance indicator (KPI) of 6G. However, there is a lack of investigation on the EEE of random arrival traffic, which is the underlying platform for MTCs. In this work, we explore the distinct characteristics of F-composite fading channels, which specify the combined impact of multipath fading and shadowing. Furthermore, we evaluate the EEE over such fading under a finite blocklength regime and QoS constraints where IoT applications generate constant and sporadic traffic. We consider a point-to-point buffer-aided communication system model, where (1) an uplink transmission under a finite blocklength regime is examined; (2) we make realistic assumptions regarding the perfect channel state information (CSI) available at the receiver, and the channel is characterized by the F-composite fading model; and (3) due to its effectiveness and tractability, application data are found to have an average arrival rate calculated using Markovian sources models. To this end, we derive an exact closed-form expression for outage probability and the effective rate, which provides an accurate approximation for our analysis. Moreover, we determine the arrival and required service rates that satisfy the QoS constraints by applying effective bandwidth and capacity theories. The EEE is shown to be quasiconcave, with a trade-off between the transmit power and the rate for maximising the EEE. Measuring the impact of transmission power or rate individually is quite complex, but this complexity is further intensified when both variables are considered simultaneously. Thus, we formulate power allocation (PA) and rate allocation (RA) optimisation problems individually and jointly to maximise the EEE under a QoS constraint and solve such a problem numerically through a particle swarm optimization (PSO) algorithm. Finally, we examine the EEE performance in the context of line-of-sight and shadowing parameters.

Interference mitigation is a major design challenge in wireless systems, especially in the context of ultra-reliable low-latency communication (URLLC) services. Conventional average-based interference management schemes are not suitable for URLLC as they do not accurately capture the tail information of the interference distribution. This letter proposes a novel interference prediction algorithm that considers the entire interference distribution instead of only the mean. The key idea is to model the interference variation as a discrete state space discrete-time Markov chain. The state transition probability matrix is used to estimate the state evolution in time, and allocate radio resources accordingly. The proposed scheme is found to meet the target reliability requirements in a low-latency single-shot transmission system considering realistic system assumptions, while requiring only ~25% more resources than the optimum case with perfect interference knowledge.

No abstract is provided for this article.