CQI Prediction Through Recurrent Neural Network for UAV Control Information Exchange Under URLLC Regime

Unmanned aerial vehicles (UAVs) control information delivery is a critical communication with stringent requirements in terms of reliability and latency. In this context, link adaptation plays an essential role in the fulfillment of the required performance in terms of decode error probability and delay. Link adaptation is usually based on channel quality indicator (CQI) feedback information from the user equipment that should represent the current state of the channel. However, measurement, scheduling and processing delays introduce a CQI aging effect, that is a mismatch between the current channel state and its CQI representation. Using outdated CQI values may lead to the selection of a wrong modulation and coding scheme, with a detrimental effect on performance. This is particularly relevant in ultra reliable and low latency communications (URLLC), where the control of the reliability can be negatively impacted, and it is more evident when the channel is fast varying as the case of UAVs. This paper analyzes the effects of CQI aging on URLLCs, considering transmissions under the finite blocklength regime, that characterizes such communications type. A deep learning approach is investigated to predict the next CQI from the knowledge of past reports, and performance in terms of decode error probability and throughput is given. The results show the benefit of CQI proposed prediction mechanism also in comparison with previously proposed methods

Adaptive OFDMA Systems

Modern wireless communications are based on the exploitation of channel behavior and/or user requirements by adapting one or more transmission parameters. Amongst several systems the OFDMA offers a lot of capabilities to the system designer allowing adapting in several ways the communications. This chapter deals with the introduction of the basic principle of an adaptive OFDMA system by focusing on those most important parameters that can be adjusted in order to have better performance. Finally, some techniques are presented also by showing some numerical results

An Efficient Two-tier MAC Scheme for Satellite Machine-to-Machine Communications

The use of satellite communications to support the Internet of Things paradigm is of paramount importance for application scenarios where machines are spread in remote and wide areas. In such context, this paper proposes an efficient hierarchical radio access scheme. Ground machines randomly access the radio channel to communicate with their cluster heads, which in turn relay the cluster's aggregated traffic toward the satellite. The aim is optimizing the resource allocation to different communication stages, allowing resource reuse among clusters, in order to minimize the packet drop probability, and hence, to maximize the system throughput. First, the optimal solution is derived for the single cluster, then it is extended to the multi-cluster scenario. Numerical results show the effectiveness of the proposed method, also in comparison with benchmark approaches

Efficient Spectrum Spatial Reuse Approach Based on Gibbs Sampling for Ultra Dense Networks

The ultra dense deployment of small cells is consid- ered a key technology to achieve the requested capacity in future cellular networks. However, the interference pattern becomes more unpredictable and challenging in these networks. Therefore, a suitable trade-off between spectrum spatial reuse and interfer- ence level has to be pursued to achieve good performance in terms of provided throughput. This paper proposes a new method to maximize the achievable throughput of an UDN with a suitable level of spatial spectrum reuse. In particular, the focus is on the small cells tier where the available spectrum is divided into sub-bands and each cell can use some of these to communicate with its associated users. The goal is to find the sub-bands allocation among cells that maximizes the system throughput. However, to limit complexity and signaling overhead that could result unaffordable in an UDN, a new metric to approximate the cell throughput to be optimized is defined. Moreover, the newly defined problem is solved using the Gibbs Sampling approach. The method effectiveness is proven by comparing the achieved results with those of the maximization of the effective system throughput and the optimal solution

The communication infrastructure for emergency management

Wireless communications have achieved a great attention during the last decades due to the easy implementation, possibility of delivering multimedia services to rural communities, suitability for public safety and emergency communications. In particular, a wireless network designed for an emergency scenario has to be capable of managing all the phases of an emergency situation, from the prevention to the post-emergency management. This paper discusses the main features of a wireless network aiming to interconnect several heterogeneous systems and providing multimedia access to groups of people by introducing the main outcome of the In.Sy.Eme. (Integrated System for Emergency) project. Particular attention will be devoted to the approach of the project, aiming to consider a communication infrastructure strictly connected with an information processing side

Adaptive subcarrier allocation schemes for wireless ofdma systems in wimax networks

WiMax is one of the most important technologies for providing a broadband wireless access (BWA) in a metropolitan area. The use of OFDM transmissions has been proposed to reduce the effect of multipath fading in wireless communications. Moreover, multiple access is achieved by resorting to the OFDMA scheme. Adaptive subcarrier allocation techniques have been selected to exploit the multiuser diversity, leading to an improvement of performance by assigning subchannels to the users accordingly with their channel conditions. A method to allocate subcarriers is to assign almost an equal bandwidth to all users (fair allocation). However, it is well known that this method limits the bandwidth efficiency of the system. In order to lower this drawback, in this paper, two different adaptive subcarrier allocation algorithms are proposed and analyzed. Their aim is to share the network bandwidth among users on the basis of specific channel conditions without loosing bandwidth efficiency and fairness. Performance comparisons with the static and the fair allocation approaches are presented in terms of bit error rate and throughput to highlight the better behavior of the proposed schemes in particular when users have different distances from the BS

Higher Order Impulsive Signals for UWB Communications

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