Publications

The design of energy-efficient mechanisms is one of the key challenges in emerging wireless small cell networks. In this paper, a novel approach for opportunistically switching ON/OFF base stations to improve the energy efficiency in wireless small cell networks is proposed. The proposed approach enables the small cell base stations to optimize their downlink performance while balancing the load among each another, while satisfying their users' quality-of-service requirements. The problem is formulated as a noncooperative game among the base stations that seek to minimize a cost function which captures the tradeoff between energy expenditure and load. To solve this game, a distributed learning algorithm is proposed using which the base stations autonomously choose their optimal transmission strategies. Simulation results show that the proposed approach yields significant performance gains in terms of reduced energy expenditures up to 23% and reduced load up to 40% compared to conventional approaches.

Ultra-reliable vehicle-to-everything (V2X) communication is essential for enabling the next generation of intelligent vehicles. V2X communication refers to the exchange of information between vehicle and infrastructure (V2I) or between vehicles (V2V). Network slicing is one of the promising technologies for the next generation of connected devices, creating several logical networks on a common and programmable physical infrastructure. Following this idea, we propose a network slicing based communication model for vehicular networks. In this paper, we have modelled a multi-lane highway scenario with vehicles having heterogeneous traffic requirements. Autonomous driving slice (exchanges safety messages) and infotainment slice (provides video stream) are the two logical slices created on a common infrastructure. In addition, a relaying approach is utilized to improve the performance of low signal-to-interferenceplus-noise-ratio (SINR) video streaming vehicles. These low SINR vehicles are served by other infotainment vehicles, which have high quality V2V and V2I link and are not serving as autonomous driving slice access point. An extensive Long Term Evolution Advanced (LTE-A) system level simulator is used to evaluate the performance of the proposed method, in which it is shown that the proposed network slicing approach increases the packet reception ratio (PRR) from 31.15% to 99.47%.

In this paper we present system level simulation results for a cooperative moving relay node (MRN) system deployed on a high speed train (HST). Recently interest has grown in using MRNs to provide enhanced cellular coverage to users in public transport, particularly HSTs, of which the modern construction materials and techniques cause high vehicle penetration loss (VPL) when signals propagate into the train. MRNs utilising antenna arrays on the exterior and interior of the train are a promising solution to overcoming this VPL in order to provide onboard users with improved service. We show that a cooperative system of 8 MRNs onboard a HST is able to provide significant improvements to achievable throughput of onboard users when compared to direct transmission, as well as indirectly improving the throughput of other users located in cells the HST is passing through.

Spot beamfocusing (SBF) is the process of focusing the signal power in a small spot-like region in the 3D space, which can be either hard-tuned (HT) using traditional tools like lenses and mirrors or electronically reconfigured (ER) using modern large-scale intelligent surface phased arrays. ER-SBF can be a key enabling technology (KET) for the next-generation 6G wireless networks offering benefits to many future wireless application areas such as wireless communication and security, mid-range wireless chargers, medical and health, physics, etc. Although near-field HT-SBF and ER-beamfocusing have been studied in the literature and applied in the industry, there is no comprehensive study of different aspects of ER-SBF and its future applications, especially for nonoptical (mmWave, sub-THz, and THz) electromagnetic waves in the next generation wireless technology, which is the aim of this paper. The theoretical concepts behind ER-SBF, different antenna technologies for implementing ER-SBF, employing machine learning (ML)-based schemes for enabling channel-state-information (CSI)-independent ER-SBF, and different practical application areas that can benefit from ER-SBF will be explored.

This paper addresses the establishment of secure communication links between smart-meters (Alice) and an aggregator (Bob) in the presence of an eavesdropper (Eve). The proposed scenario assumes: (i) MIMOME wiretap channel; (ii) transmit antenna selection at the Alice; (iii) no channel state information at the transmitter; (iv) fixed Wyner codes; and (v) guarantee of secure throughput by both quality of service and secrecy outage constraints. We propose a simple protocol to enhance security via transmit antenna selection, and then assess its performance in closed-form by means of secrecy outage and successful transmission probabilities. We assume these probabilities are our constraints and then maximize the secure throughput, establishing a security-reliability trade-off for the proposed scenario. Our numerical results illustrate the effect of this trade-off on the secure throughput as well as on the number of antennas at Alice, Bob and Eve. Interestingly, a small sacrifice in reliability allows secrecy enhancement in terms of secure bps/Hz. We apply this idea in our smart grid application to exemplify that, although Eve may acquire some samples of the average power demand of a household, it is not enough to properly reconstruct such curve.

The millimeter wave (mmWave) communication uses directional antennas. Hence, achieving fine alignment of transmit and receive beams at the initial access phase is quite challenging and time-consuming. In this paper, we provide a dynamic-weight based beam sweeping direction and synchronization signal block (SSB) allocation algorithm to optimize the cell search of the initial access in mmWave 5G NR networks. The number of SSBs transmitted in each beam sweeping direction depends on previously learned experience which is based on the number of detected UEs (user equipment) per SSB for each sweeping direction. Overall, numerical simulation results indicate that the proposed algorithm is shown to be capable of detecting more users with a lower misdetection probability. Furthermore, it is possible to achieve the same performance with a smaller number of dynamic resource (i.e., SSB) allocation, compared to constant resource allocation.

While 5G is being rolled out in different parts of the globe, few research groups around the world $-$ such as the Finnish 6G Flagship program $-$ have already started posing the question: \textit{What will 6G be?} The 6G vision is a data-driven society, enabled by near instant unlimited wireless connectivity. Driven by 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. This article presents an over-arching vision for machine type communication in 6G. In this regard, some relevant performance indicators are first anticipated, followed by a presentation of six key enabling technologies.

This letter presents analysis of diffraction over multiple shadowing screens at frequency range of 10-18 GHz. Up to ten pieces of thin metal sheets with dimensions of 130 × 100 cm at variable spacing were used as diffraction screens. The aim of this study is to investigate the total shadowing effect of multiple knife-edge diffractions at frequencies above the legacy cellular systems. The results show the necessity to adjust the Walfisch-Bertoni path loss model for the higher frequencies in the future fifth-generation systems.

In this paper, a novel cluster-based approach for optimizing the energy efficiency of wireless small cell networks is proposed. A dynamic mechanism based on the spectral clustering technique is proposed to dynamically form clusters of small cell base stations. Such clustering enables intra-cluster coordination among the base stations for optimizing the downlink performance through load balancing, while satisfying users' quality-of-service requirements. In the proposed approach, the clusters use an opportunistic base station sleep-wake switching mechanism to strike a balance between delay and energy consumption. The inter-cluster interference affects the performance of the clusters and their choices of active or sleep state. Due to the lack of inter-cluster communications, the clusters have to compete with each other to make decisions on improving the energy efficiency. This competition is formulated as a noncooperative game among the clusters that seek to minimize a cost function which captures the tradeoff between energy expenditure and load. To solve this game, a distributed learning algorithm is proposed using which the clusters autonomously choose their optimal transmission strategies. Simulation results show that the proposed approach yields significant performance gains in terms of reduced energy expenditures up to 40% and reduced load up to 23% compared to conventional approaches.

The problem of robust weighted sum-rate maximization (WSRMax) in multicell downlink multi-input single-output systems is considered. We assume that the channel state information (CSI) of all users is imperfectly known at the base stations. The problem is known to be NP-hard even in the case of perfect CSI. Assuming a bounded ellipsoidal model for the CSI errors, we maximize the worst-case weighted sum-rate and proposed a fast but possibly suboptimal algorithm. The proposed algorithm is based on alternating optimization technique and sequential convex programming. Numerical results show that the convergence speed of the proposed algorithm is fast, and it finds a close-to-optimal solution in only a few iterations.

Wireless networks are becoming extremely pervasive while traffic demand is ever increasing. In order to cope with the forecast increase in traffic volume for the upcoming years, as well as the number of connected devices, new technologies, practices and spectrum rearrangements are required. In this context, a key question arises: how to provide extensive backhaul connectivity and capacity for pervasive ultra dense networks? The answer is rather complex, if feasible. To shed some light into this issue we overview potential technologies, either wired or wireless, and identify technical challenges. Moreover, we evaluate an illustrative scenario of a ultra-dense network that operates with hybrid wired-wireless backhaul. We assume multiple radio access technologies at small and macro base stations (BSs), and we discuss optimal traffic splitting and routing solutions for different topologies and traffic profiles.

No abstract is provided for this article.

No abstract is provided for this article.

No abstract is provided for this article.