A low complexity resource allocation algorithm for multicast service delivery in OFDMA networks

Allocating and managing radio resources to multicast transmissions in Orthogonal Frequency-Division Multiple Access (OFDMA) systems is the challenging research issue addressed by this paper. A subgrouping technique, which divides the subscribers into subgroups according to the experienced channel quality, is considered to overcome the throughput limitations of conventional multicast data delivery schemes. A low complexity algorithm, designed to work with different resource allocation strategies, is also proposed to reduce the computational complexity of the subgroup formation problem. Simulation results, carried out by considering the Long Term Evolution (LTE) system based on OFDMA, testify the effectiveness of the proposed solution, which achieves a near-optimal performance with a limited computational load for the system

RACH preamble repetition in NB-IoT network

NarrowBand-Internet of Things (NB-IoT) is a radio access technology recently standardized by 3GPP. To provide reliable connections with extended coverage, a repetition transmission scheme is applied in both Random Access CHannel (RACH) procedure and data transmission. In this letter, we model RACH in the NB-IoT network taking into account the repeated preamble transmission and collision using stochastic geometry. We derive the exact expression of RACH success probability under time correlated interference, and validate the analysis with different repetition values via independent simulations. Numerical results have shown that the repetition scheme can efficiently improve the RACH success probability in a light traffic scenario, but only slightly improves that performance with very inefficient channel resource utilization in a heavy traffic scenario

Self-organising comprehensive handover strategy for multi-tier LTE-advanced heterogeneous networks

Long term evolution (LTE)-advanced was introduced as real fourth generation (4G) with its new features and additional functions, satisfying the growing demands of quality and network coverage for the network operators' subscribers. The term muti-tier has also been recently used with respect to the heterogeneity of the network by applying the various subnetwork cooperative systems and functionalities with self-organising capabilities. Using indoor short-range low-power cellular base stations, for example, femtocells, in cooperation with existing long-range macrocells are considered as the key technical challenge of this multi-tier configuration. Furthermore, shortage of network spectrum is a major concern for network operators which forces them to spend additional attentions to overcome the degradation in performance and quality of services in 4G HetNets. This study investigates handover between the different layers of a heterogeneous LTE-advanced system, as a critical attribute to plan the best way of interactive coordination within the network for the proposed HetNet. The proposed comprehensive handover algorithm takes multiple factors in both handover sensing and decision stages, based on signal power reception, resource availability and handover optimisation, as well as prioritisation among macro and femto stations, to obtain maximum signal quality while avoiding unnecessary handovers

Beta-Conversion, Efficiently

Type-checking in dependent type theories relies on conversion, i.e. testing given lambda-terms for equality up to beta-evaluation and alpha-renaming. Computer tools based on the lambda-calculus currently implement conversion by means of algorithms whose complexity has not been identified, and in some cases even subject to an exponential time overhead with respect to the natural cost models (number of evaluation steps and size of input lambda-terms). This dissertation shows that in the pure lambda-calculus it is possible to obtain conversion algorithms with bilinear time complexity when evaluation is carried following evaluation strategies that generalize Call-by-Value to the stronger case required by conversion

Softwarization and virtualization in 5G mobile networks:benefits, trends and challenges

The promise behind the effective deployment of 5G networks is an architecture able to provide flexibility, reconfigurability and programmability in order to support, with fine granularity, a wide and heterogeneous set of 5G use cases. This dictates a radical change in the design of mobile systems which, being usually based on the use of static deployment of vendor equipment characterized by monolithic functionality deployed at specific network locations, fail in providing the above mentioned features. By decoupling network functionalities from the underlying hardware, softwarization and virtualization are two disruptive paradigms considered to be at the basis of the design process of 5G networks. This paper analyses and summarizes the role of these two paradigms in enhancing the network architecture and functionalities of mobile systems. With this aim, we analyze several 5G application scenarios in order to derive and classify the requirements to be taken into account in the design process of 5G network. We provide an overview on the recent advances by standardization bodies in considering the role of softwarization and virtualization in the next-to-come mobile systems. We also survey the proposals in literature by underlining the recent proposals exploiting softwarization and virtualization for the network design and functionality implementation of 5G networks. Finally, we conclude the paper by suggesting a set of research challenges to be investigated

A Multi-Criteria Approach for Multicast Resource Allocation over LTE and Beyond Cellular Systems

The fast growing of multimedia applications and enhanced device (i.e., in capacity and computing) leads the network infrastructure to manage a number of users with different channel qualities, application requirements, and service constraints. In such a scenario, is evident the need to find a resource scheduling procedure able to guarantee good levels of performance not only on the network-side but also to the user side. To this end, this paper introduces a novel approach for multicast resource allocation based on the idea of exploiting a multi-criteria decision method (i.e., namely TOPSIS) properly designed to simultaneously take into account both provider and user benefits during the spectrum allocation process. In particular, we compared a promising multicast radio resource strategy, i.e., subgrouping, tailored to exploit different cost functions represented by (i) local throughput, (ii) local fairness, and (iii) subgroup minimum dissatisfaction index. The obtained results, performed for the delivery of scalable multicast video flows in a Long Term Evolution (LTE) macrocell, demonstrate the effectiveness of the TOPSIS-based radio resource management scheme, which outperforms existing approaches from the literature. Indeed, it succeeds to provide higher data rate and an improved user satisfaction when considering multicast users experiencing different levels of channel and service quality

The Active Ingredients of Integral Stimulation Treatment: The Efficacy of Auditory, Visual, and Auditory-Visual Cues for Treatment of Childhood Apraxia of Speech

The purpose of this study was to determine the relative efficacy of cueing modalities employed in Integral Stimulation (IS) treatment for childhood apraxia of speech (CAS). Previous literature has supported the use of IS for children with CAS, though there are no studies that evaluate the active ingredients of IS. This study aimed to examine the efficacy of single- and multi-modality cues in IS treatment. The experiment was administered as a single-case, alternating treatments design consisting of three conditions (auditory-only, visual-only, and simultaneous auditory and visual). Two participants with CAS received IS treatment in every condition during each session. Probes were administered prior to starting every other session (once per week), consisting of practiced and control targets that were balanced for complexity and functionality. Perceptual accuracy of productions was rated on a 3-point scale and standardized effect sizes were calculated for each condition. Each participant demonstrated different effects in regard to modality and treatment effects. The visual-only condition yielded the greatest effect for one participant, followed by the auditory-only cues. The other participant displayed no significant effects in any condition nor a treatment effect. The results of this study suggest that single-modality cues may be more beneficial for some children with CAS than the clinically used simultaneous auditory-visual multi-modality cue. The significant effect of the visual-only condition in one participant indicates that visual-only cues may bypass an impaired auditory feedback system and support speech motor learning, though more research is required.Public Healt

Analysis of a contention-based approach over 5G NR for Federated Learning in an Industrial Internet of Things scenario

The growing interest in new applications involving co-located heterogeneous requirements, such as the Industrial Internet of Things (IIoT) paradigm, poses unprecedented challenges to the uplink wireless transmissions. Dedicated scheduling has been the fundamental approach used by mobile radio systems for uplink transmissions, where the network assigns contention-free resources to users based on buffer-related information. The usage of contention-based transmissions was discussed by the 3rd Generation Partnership Project (3GPP) as an alternative approach for reducing the uplink latency characterizing dedicated scheduling. Nevertheless, the contention-based approach was not considered for standardization in LTE due to limited performance gains. However, 5G NR introduced a different radio frame which could change the performance achievable with a contention-based framework, although this has not yet been evaluated. This paper aims to fill this gap. We present a contention-based design introduced for uplink transmissions in a 5G NR IIoT scenario. We provide an up-to-date analysis via near-product 3GPP-compliant network simulations of the achievable application-level performance with simultaneous Ultra-Reliable Low Latency Communications (URLLC) and Federated Learning (FL) traffic, where the contention-based scheme is applied to the FL traffic. The investigation also involves two separate mechanisms for handling retransmissions of lost or collided transmissions. Numerical results show that, under some conditions, the proposed contention-based design provides benefits over dedicated scheduling when considering FL upload/download times, and does not significantly degrade the performance of URLLC

Network slicing management & prioritization in 5G mobile systems

—5G mobile network is expected to serve flexiblerequirements hence dynamically allocate network resources accordingto the demands. Network slicing, where network resourcesare packaged and assigned in an isolated manner to setof users according to their specific requirements, is consideredas a key paradigm to fulfil diversity of requirements. Therewill clearly be conflicting demands in allocation of such slices,and the effective provisioning of network slicing poses severalchallenges. Indeed, network slicing has a twofold impact in termsof user/traffic prioritization as it dictates for the simultaneousmanagement of the priority among different slices (i.e., interslice)and the priority among the users belonging to the sameslice (i.e., intra-slice). In this paper, we propose a novel heuristic basedadmission control mechanism able to dynamically allocatenetwork resources to different slices in order to maximizethe satisfaction of the users while guaranteeing to meet therequirements of the slices they belong to. Through simulations, wedemonstrate how our proposal provides (i) higher user experiencein individual slices, (ii) increased utilization of network resourcesand (iii) higher scalability when the number of users in each sliceincreases

Network slicing in 5G:An auction-based model

The 5G mobile network is expected to meet the diverse demands from multiple types of business services. At the same time, some of the 5G use cases come with hard, and often expensive to meet, requirements in terms of latency andbandwidth. It is a common understanding that one system can not fit all and there is a need for customizing network according to the requirements of specific business use cases. Network slicing is introduced to partition the physical network to different slices to be configured for providing different quality of service as requested by the slice’ operator and required by the slice’ users. Since these slices will be used by the businesses, e.g. verticals,allocating physical resources to the network slices, is not anymore only a matter of performance but also a matter of revenue and business model. In this paper, we address a joint resource and revenue optimization a novel auction based model. Through extensive simulation study, we demonstrate our proposed auction model can allocate network resources to network slices for providing (i) higher satisfaction of requirements per network slice, and (ii) increased network revenue.<br clear="none"/