Millimeter-wave (mmWave) multiple-input multiple-output (MIMO) has accelerated the efficiency of modern wireless systems, yet its performance is constrained by the propagation blocking effect and the receiver analog-to-digital converters (ADC) saturation. Motivated by these, this paper first attempted to study an intelligent reflecting surface (IRS)-aided downlink mmWave MIMO system equipped with a modulo ADC front end at the receiver and explicitly models receiver-side quantization error. We propose spectral efficiency (SE) maximization under total-power and constant-modulus constraints and develop a real-valued genetic algorithm-based scheme that, in each generation, (i) explores the IRS reflection matrix and (ii) updates the transceiver beamformers by performing singular value decomposition on the cascaded channel, updated with the IRS reflection matrix. Experimental results demonstrate that the modulo ADC achieves higher SE and lower bit error rates with fewer bit resolution, effectively mitigating saturation-induced clipping and outperforming conventional ADCs.

This research demonstrates how MATLAB's Reinforcement Learning Markov Decision Process (MDP) Example Model can be used to design Radio Link Control MDP Reinforcement Learning (RL) agent. Since the number of agents in MATLAB's RL toolbox is not scalable beyond one agent, then an agent scalability scheme is required to design RL agents in MATLAB's RL toolbox and then realize multiple lightweight simultaneously operable Python instances of it for each of the multiple user equipment UE in a network.

The terahertz-wave communications are sensitive to the propagation environment. Line-of-Sight (LOS) is considered crucial in maintaining reliable connections between transmitters and receivers, providing high quality of service and estimating the terminals’ locations accurately. Therefore, maximizing LOS availability improves performance and the localization process in the future systems. In this paper, we propose a general framework to investigate the impact of blockages’ characteristics on the probability of a terminal of interest provided with a number of LOS links simultaneously by taking into consideration the correlation among these links. A comparison among three scenarios, namely correlation, no correlation and two-dimensional is presented to validate the accuracy of these scenarios in different environment densities. The simulation results validate the accuracy of our analysis and show that considering different values of the base station (BS) number and height can improve the system performance. Maximizing the LOS availability can be achieved by considering a higher number of BSs in low and medium environment densities and by increasing the height of BSs for dense environments. Furthermore, unlike in the low environment densities, the correlation between links needs to be addressed carefully when studying LOS availability in dense environments in order to meet the future requirements.

Abstract In this paper, a deep learning integrated reinforcement learning (DLIRL) algorithm is proposed for comprehending intelligent beamsteering in Beyond Fifth Generation (B5G) networks. The smart base station in B5G networks aims to steer the beam towards appropriate user equipment based on the acquaintance of isotropic transmissions. The foremost methodology is to optimize beam direction through reinforcement learning that delivers significant improvement in signal to noise ratio (SNR). This includes alternate path finding during path obstruction and steering the beam appropriately between the smart base station and user equipment. The DLIRL is realized through supervised learning with deep neural networks and deep Q‐learning schemes. The proposed algorithm comprises of an online learning phase for training the weights and a working phase for carrying out the prediction. Results confirm that the performance of the B5G system is improved considerably as compared to its counterparts with a spectral efficiency of 11 bps/Hz at SNR = 10 dB for a bit error rate performance of 10 −5 . As compared to reinforced learning and deep neural network with a deviation of ±3 o and ±5°, respectively, the DLIRL beamforming displays a deviation of ±2 o . Moreover, the DLIRL can track the user equipment and steer the beam in its direction with an accuracy of 92%.

To improve data speed and reliability, hybrid wireless networks combine two different Radio Access Technologies (RATs), such as Visible Light Communications (VLC), millimetre wave (mmWave), Wireless Fidelity (WiFi), 4G Long Term Evolution (LTE), etc. The Internet of Radio Light (IoRL) is a cutting-edge system paradigm to combine three RATs for taking advantage the vast VLC and mmWave spectrum with the ubiquitous coverage of WiFi. In this respect, this work introduces a new convex optimisation-based solution method to optimise the three-dimensional (3D) Access Point Assignment (APA) problem of the IoRL system under individual user positioning, priority and minimum Quality-of-Service (QoS) constraints. We use both the IoRL real-world testbed and large-scale Maltab simulations to evaluate that our solution converges in linear time, and attains higher throughput-vs-fairness trade-off than existing efforts.

Visible Light Communication (VLC) is a powerful supplement, which has gained tremendous attention recently and has become a favorable technology in short-range communication scenarios for the Fifth Generation (5G) networks. VLC possesses a number of prominent features to address the highly demanding 5G system requirements for high capacity, high data rate, high spectral efficiency, high energy efficiency, low battery consumption, and low latency. However, this prominent performance is limited by the imperfect reception, since line of sight channel condition may not always exist in practice. This paper presents and experimentally validates a SDN-assisted VLC system, which is coupled with WiFi access technology in order to improve the reliability of VLC system, reassuring zero packet loss reception quality due to misalignment or path obstructions or when the user is moving between two consecutive VLC transmitters and experience “dead coverage zones”.

5G research shows more potential attention to mobile communications in information intensive industrial sectors such as power utility. In smart grid context, employing licensed assisted access (LAA) allows smart grid operators to transfer utility data between different sites using the unlicensed and licensed bands. This can play a crucial role in improving efficiency, sustainability, stability, and to meet the quality of service (QoS) requirements of different smart grid consumer requests. Considering the unlicensed band, there is a strong need to develop new LAA unlicensed access technology that can improve spectrum acceptability compared to conventional Wi-Fi to meet the high volumes of information in smart grids. In this paper, we investigate the spectrum allocation techniques required to exploit smart grid requirements by setting a minimum bit error rate (BER) threshold while evaluating the availability of white holes in the unlicensed band. Simulation results confirm the advantages of the proposed scheme in allocating more resources to LAA unlicensed users subject to their load requirements. This paper provides a new method for intelligent spectrum allocation to support the communication requirements of smart grid networks.

Automatic continuous affective state prediction from naturalistic facial expression is a very challenging research topic but very important in human-computer interaction. One of the main challenges is modeling the dynamics that characterize naturalistic expressions. In this paper, a novel two-stage automatic system is proposed to continuously predict affective dimension values from facial expression videos. In the first stage, traditional regression methods are used to classify each individual video frame, while in the second stage, a time-delay neural network (TDNN) is proposed to model the temporal relationships between consecutive predictions. The two-stage approach separates the emotional state dynamics modeling from an individual emotional state prediction step based on input features. In doing so, the temporal information used by the TDNN is not biased by the high variability between features of consecutive frames and allows the network to more easily exploit the slow changing dynamics between emotional states. The system was fully tested and evaluated on three different facial expression video datasets. Our experimental results demonstrate that the use of a two-stage approach combined with the TDNN to take into account previously classified frames significantly improves the overall performance of continuous emotional state estimation in naturalistic facial expressions. The proposed approach has won the affect recognition sub-challenge of the Third International Audio/Visual Emotion Recognition Challenge.

The newly released LTE-Advanced (LTE-A) is currently being introduced as a further step to LTE and as the real 4G cellular standard on cellular networks evolution. Alongside with the increasing demands in mobile networks, the customers' satisfaction with a ubiquitous heterogeneous network (HetNet) is going to be the main challenge for the network operators, and therefore planning a multi-layer network with different ranges of base stations seems to be an appropriate solution for this deficiency. Furthermore, the interference mitigation in such networks plays a critical role towards the appropriate bandwidth allocation to different categories of the network users -especially in case of sharing the available bandwidth- and needs to be highly considered when the network planning is under considerations. This paper proposes a novel multi-layer cells deployment with self-organizing approach, designated for the LTE/LTE-Advanced networks and the new releases beyond that. The proposed strategy focuses on femto application and implementation, to exploit the advantages of femtocell nodes, e.g. coverage enhancements, power consumption improvements, network satisfaction, etc. This paper presents the introduction, simulation and evaluation of a novel multi-layer LTE-A scenario, which allows both macro and femto applications to share the spectrum, taking into consideration interference management and network satisfaction.

This paper presents a new approach to pixel domain Wyner-Ziv (PDWZ) video coding by using weighted motion compensated refinement (WMCR) embedded into turbo decoder to efficiently optimize side information. The proposed system is designed by combining a relatively simple interpolation model for initial side information plus embedded refinement process to achieve better performance of system as a whole. In order to explore practical application of PDWZ in wireless environment, we adopt the 3GPP standardized turbo codec as Slepian-Wolf codec in PDWZ system. Experimental results showed that the proposed system have noticeable improvement in RD performance and reduced complexity of whole system.

This paper investigates the design and performance of an FIR echo canceller for on channel repeaters in DVB-T/H network within the framework of the PLUTO project. The possible approaches for echo cancellation are briefly reviewed and the main guidelines for the design of such systems are presented. The main system parameters are discussed. The performance of a FIR echo canceller based on an open loop approach for channel estimation is tested for different radio channel conditions and for different number of taps of the FIR filter. It is shown that a minimum number of taps is recommended to achieve a certain mean rejection ratio or isolation depending on the type of channel. The expected degradation in performance due to the use of fixed point rather than floating point arithmetic in hardware implementation is presented for different number of bits.

A major European Union IST project, SAVANT (synchronised and scalable AV content across networks: IST-2001-34814), has been launched bringing together key broadcasters, researchers, academics and industrialists across Europe, to drive the future convergence of broadcast and Internet. SAVANT is committed to develop integrated Internet/broadcast multimedia technologies in order to achieve added-value services to conventional digital and interactive television. The SAVANT project aims to provide an interactive digital framework for scalable broadcast television services converged with television oriented IP services. This work describes new services that can be developed using this framework.

Although some market research has predicted the rapid uptake of digital television by European householders, recent unsettling experiences in the UK digital television market has shown that consumers demand a more value added viewing experience. This is understood by the fact that terrestrial analogue broadcasting has enjoyed a reputation of providing a television service to a very high standard. It is thus necessary to find ways in which end-users can best exploit the increased flexibility and the advantages that digital television creates. For this to happen, the whole value of the broadcasting chain has to support seamless integration of the broadcast and telecommunication networks. The European Union IST project, SAVANT (synchronised and scalable AV content across networks), aims to provide an interactive digital framework for scalable broadcast television services converged with television oriented IP services. The paper describes the major architectural components of the project.

The scientific results of global archaeological excavations often take the form of books and papers, and on occasion, web sites and digital media. However, a large amount of the raw recorded data remains inaccessible to wider audiences. This paper proposes the development of a universal archaeological system that unites archaeological recordings from diverse sites, making easier the process of dissemination to both the wider public and the analysis and comparison of this data by the scientific community, enabling a more informed interpretation of our past. This is accomplished through a 3D cyber-world constructed from a variable level of detailed recordings from archaeological sites.

This letter presents the main statistical characterization of the underlying error process obtained in the case of the Digital European Cordless Telecommunications (DECT) radio system. By simulation of the transmission Link, error sequences are generated for different channel parameters. Relevant statistics are then computed for the purpose of efficient channel coding design and evaluation.

A method of characterizing video codec sources in asynchronous transfer mode (ATM) networks as an autoregressive moving average (ARMA) process is described. Measurements of long-term mean and the autocorrelation function of cell interarrival times allow the parameter estimation of the ARMA model. The video source is then described by ARMA model. Furthermore, it is shown that the multiplexed stream of video cells is also an ARMA process. Such a cell stream is then applied to a model of a queuing system to obtain performance measures of the system. Perturbation analysis is then performed on the functional behavior of the queuing system by appropriate perturbation of the model parameters to determine cell waiting time sensitivity due to slight variations of the input process.>