Search

In order to overcome spectrum scarcity and provide higher data rates, the sixth-generation (6G) wireless communication network is expected to perform data transmission using terahertz (THz) frequencies. However, the effective implementation of these communication systems is hampered by severe levels of signal degradation to which the THz bandwidth is subject to. Recent improvements and advancements in the fabrication process of electromagnetic (EM) metamaterials have made reconfigurable intelligent surfaces (RIS) a very promising solution to address these THz-related attenuation issues. Additionally, the adoption of non-orthogonal multiple access (NOMA) transmissions represents an effective way to improve spectrum efficiency for 6G networks. In this paper, we investigate the problem of downlink aggregated sum-rate maximisation for a multiple-input multiple-output (MIMO) system assisted by a RIS panel in performing NOMA transmission within the THz bandwidth. More specifically, we propose an optimization algorithm that jointly optimizes the transmitting power at the access point (AP) and the phase-shift coefficients for the RIS elements iteratively. Through simulation results, we demonstrate that the proposed method outperforms conventional benchmark schemes in terms of achieved aggregated throughput.

Many organisations suffer from a self-inflicted wound – they attempt to do too much! As a result, nothing is done well and profits suffer. Our article addresses this problem by suggesting that managers should focus on a subset of their current initiatives – a subset selected to maximise returns without overstraining resources. We address the following issues: What are the symptoms of work overload? How does an excessive workload adversely impact the bottom line? How can managers determine the throughput capacity of their organisation? What can be done to address the problem of excessive workload? Many, if not most, organisations attempt to operate beyond their capacity, with the result that inefficiencies abound, deadlines are missed and profitability drops. Based on research and consulting experience in many companies, our paper explains the basic concepts of ‘the 25/25’ approach to project portfolio management – an approach designed to increase profitability by concentrating only on the work that is essential to the survival and profitability of the organisation. The approach has been successfully applied to dozens of public and private sector organisations companies. [ABSTRACT FROM PUBLISHER]

The authors address an important aspect of spectrum sensing that has been often overlooked in the cognitive radio (CR) research. Although CR is supposed to be aware of its surrounding, most existing articles do not consider the characteristics of secondary users in the optimisation of sensing period. In this study, based on a continuous‐time Markov chain model for cognitive sensor networks and energy detection method, the authors propose an application‐specific spectrum sensing method that obtains the optimal sensing period according to the characteristics of both 'primary and secondary' users (hybrid scheme). The authors define and analytically derive two parameters, the interference ratio and the undetected opportunity ratio, and analytically find the optimum sensing period. Numerical and simulation results indicate that our proposed method is able to provide an optimal sensing period, that is customised for different cognitive networks. The proposed method significantly increases the system throughput by up to 11% and reduces the network's power consumption by as low as 33%. Finally, the trade‐off between the throughput maximisation and power consumption minimisation is discussed. [ABSTRACT FROM AUTHOR]

We evaluate the average-case performance of eight offline heuristic algorithms to solve the routing and wavelength assignment (RWA) problem and the related throughput maximisation (TM) problem in wavelength division multiplexing optical networks. These algorithms are first-fit-decreasing (FFD), first-fit-increasing (FFI), best-fit-decreasing (BFD), best-fit-increasing (BFI), densest-fit-decreasing (DFD), densest-fit-increasing (DFI), random-fit-decreasing (RFD) and random-fit-increasing (RFI). Our experimental performance evaluation is conducted by extensive simulations on a wide range of WDM optical networks, including a mesh network, four real networks and three types of random networks. We find offline RWA algorithms and TM algorithms which perform better than previously studied online algorithms, namely, first-fit (FF), best-fit (BF), densest-fit (DF) and random-fit (RF). In particular, algorithm FFD (BFD, DFD and RFD, respectively) has better performance than algorithm FF (BF, DF and RF, respectively) for RWA, and algorithm FFI (BFI, DFI and RFI, respectively) has better performance than algorithm FF (BF, DF and RF, respectively) for TM. [ABSTRACT FROM AUTHOR]

We consider the multi-objective optimization of a multi-service arrayed-waveguide grating-based single-hop metro WDM network with the two conflicting objectives of maximizing throughput while minimizing delay. We develop and evaluate a genetic algorithm based methodology for finding the optimal throughput-delay tradeoff curve, the so-called Pareto-optimal frontier. Our methodology provides the network architecture (hardware) and the medium access control (MAC) protocol parameters that achieve the Pareto-optima in a computationally efficient manner. The numerical results obtained with our methodology provide the Pareto-optimal network planning and operation solutions for a wide range of traffic scenarios. The presented methodology is applicable to other networks with a similar throughput-delay tradeoff. [ABSTRACT FROM PUBLISHER]